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| 1073 | Comparison of Gadolinium- and Iron-Oxide-based Perfusion Imaging Metrics in Glioblastoma | |
| Ashley M. Stokes1, Sudarshan Ragunathan1, Laura Bell1, Ekokobe Fonkem2, John Karis3, and C. Chad Quarles1 | ||
1Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ, United States, 2Neuro-Oncology, Barrow Neurological Institute, Phoenix, AZ, United States, 3Neuroradiology, Barrow Neurological Institute, Phoenix, AZ, United States |
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Relative cerebral blood volume (rCBV) maps are adversely impacted by contrast agent leakage effects when acquired using gadolinium-based contrast agents, and these effects can be corrected using standard leakage correction methods. In a cohort of high-grade glioma patients, we compared leakage-corrected rCBV maps acquired using gadolinium-based contrast agents to rCBV acquired using an intravascular iron-oxide-based contrast agent. The rCBV maps from both contrast agents were similar, with high voxel-wise agreement, suggesting that leakage effects are appropriately removed from rCBV maps using standard leakage correction methods. |
| 1074 | Do You Double-Dose? Clinical Validation of Single-Dose, Dual-Echo Perfusion Protocols in Glioma Patients | |
| Ashley M. Stokes1, Taylor Olvey1, Leland S. Hu2, Leslie C. Baxter2, Laura C. Bell1, C. Chad Quarles1, and Lea Alhilali3 | ||
1Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ, United States, 2Mayo Clinic Arizona, Phoenix, AZ, United States, 3Neuroradiology, Barrow Neurological Institute, Phoenix, AZ, United States |
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Relative cerebral blood volume (rCBV) obtained from dynamic susceptibility contrast (DSC) MRI is adversely impacted by contrast agent leakage effects in enhancing brain tumors, often necessitating multiple contrast doses. The purpose of this study is to compare dual-echo rCBV maps (single-dose) with standard rCBV maps (double-dose) in patients with high-grade gliomas using commercially available software. High agreement was observed between rCBV maps with single- and double-doses, with substantial flexibility across pulse sequence parameters. This protocol could be used to lower costs and contrast dose in clinical settings, as well as eliminate variability in perfusion methods related to contrast timing schemes. |
| 1075 | Identification of IDH and TERT Mutation Status in Glioma Patients using Dynamic Susceptibility Contrast MRI | |
| Buse Buz Yalug1, Ayca Ersen Danyeli2,3, Cengiz Yakicier3,4, M. Necmettin Pamir3,5, Koray Ozduman3,5, Alp Dincer3,6, and Esin Ozturk-Isik1,3 | ||
1Institute of Biomedical Engineering, Bogazici University, Istanbul, Turkey, 2Department of Medical Pathology, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey, 3Center for Neuroradiological Applications and Reseach, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey, 4Department of Molecular Biology and Genetics, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey, 5Department of Neurosurgery, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey, 6Department of Radiology, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey |
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The main purpose of this study was to identify isocitrate dehydrogenase (IDH) and telomerase reverse transcriptase (TERT) promoter mutations in glioma patients using classical machine learning and convolutional neural networks (CNN) on dynamic susceptibility contrast MRI (DSC-MRI). Relative cerebral blood volume (rCBV) maps of glioma patients with different genotypes including IDH-mutant, IDH-wildtype, TERT-mutant, and TERT-wildtype were compared in tumor areas. Classical machine learning classification results were over 85% for both IDH and TERT mutations. On the other hand, CNNs were able to classify IDH mutation status with 83% and TERT mutation status with 72% accuracies. |
| 1076 | Application of Multiband SENSE SAGE EPI towards DSC MRI of Brain Tumors | |
| Sudarshan Ragunathan1, Laura C Bell1, Ashley M Stokes1, Ekokobe Fonkem1, John P Karis1, and C Chad Quarles1 | ||
1Barrow Neurological Institute, Phoenix, AZ, United States |
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Multi-echo acquisition strategies have the advantage of simultaneous quantification of T1/T2* values in DCR MRI, and when combined with multiband strategies, could provide comparable spatiotemporal coverage as a single shot EPI dynamic scan. While there has been some work on SMS – SAGE acquisitions, this is potentially the first work that utilizes a SENSE reconstruction framework. We demonstrated that the CNR of MBSAGE with SENSE is similar to SAGE acquisitions, and that the dynamic CNR with respect to NAWM is on the order of or slightly higher than reported by some of the SMS-SAGE implementations in literature. |
| 1077
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Investigating Relationships Between Multi-Scale Perfusion and Myelin Integrity in Patients with Relapsing-Remitting MS | |
| Nicholas J Sisco1, Aimee Borazanci1, Richard Dortch1, and Ashley M Stokes1 | ||
1Neuroimaging Research, Barrow Neuroimaging Innovation Center, Phoenix, AZ, United States |
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The objective of this study is to develop magnetic resonance imaging (MRI) biomarkers that can probe complementary vascular function and myelin content. The development of biomarker assays to quantitatively probe both perfusion and myelin content is critical to assessing acute inflammatory activity and regenerative potential. We anticipate that this biomarker will give insight into the underlying pathophysiology of reversible and irreversible myelin damage. |
| 1078 | The relative cerebral blood volume in normal-appearing white and grey matter remains almost constant following radio(chemo)therapy | |
| Katharina Witzmann1,2, Felix Raschke1,2, Tim Wesemann3, Mechthild Krause1,2,4,5,6, Jennifer Linn3, and Esther G.C. Troost1,2,4,5,6 | ||
1Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiooncology – OncoRay, Dresden, Germany, 2OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany, 3Institute of Neuroradiology, University Hospital Carl Gustav Carus and Medical Faculty of Technische Universität Dresden, Dresden, Germany, 4Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany, 5National Center for Tumor Diseases (NCT), Partner Site Dresden, Germany: German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany, and; Helmholtz Association / Helmholtz-Zentrum Dresden - Rossendorf (HZDR), Dresden, Germany, 6German Cancer Consortium (DKTK), Partner Site Dresden, and German Cancer Research Center (DKFZ), Heidelberg, Germany |
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In adjuvant radio(chemo)therapy of glioma patients, irradiation of tumor-surrounding normal tissue is unavoidable, potentially leading to long-term side-effects. We analyzed radiation-induced perfusion changes measured as relative cerebral blood volume (rCBV) in supraventricular grey and white matter regions of 17 glioma patients before and 3, 6 and 9 months after radiotherapy. After treatment, perfusion remained constant in the entire regions and after dose-separation, except for a statistically significant rCBV decrease in low-dose white matter volumes 6 months after the end of radiotherapy (p=0.008) and a trend towards increasing white and grey matter perfusion in high-dose volumes at 9 months (p<0.1). |
| 1079 | Aberrant cerebral perfusion pattern in amnestic mild cognitive impairment and Parkinson’s disease with mild cognitive impairment | |
| Song'an Shang1, Weiqiang Dou2, and Jingtao Wu3 | ||
1Nanjing First Hospital, Nanjing Medical University, Nanjing, China, 2GE Healthcare, MR Research China, Beijing, China, 3Northern Jiangsu People’s Hospital, Yangzhou, China |
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We investigated the aberrations in regional perfusion properties among amnestic mild cognitive impairment (aMCI) patients, patients with Parkinson’s disease with MCI (PD-MCI), and healthy control (HC) by using 3D arterial spin labeling (ASL) imaging. Our results showed that normalized cerebral blood flow (CBF) as measured by 3D ASL revealed different patterns of perfusion between aMCI and PD-MCI, probably linked to distinct neural mechanisms. Therefore, this preliminary study demonstrates that normalized CBF might provide specific perfusion information for further pathological and neuropsychological studies. |
| 1080 | Simultaneous Effects of tDCS on Cerebral Blood Flow and Metabolic Response in Healthy Controls | |
| Marco Muccio, MSc1, Lillian Walton Masters1, Giuseppina Pilloni, PhD1, Lauren Krupp, MD1, Abhishek Datta, PhD2, Marom Bikson, PhD3, Leigh Charvet, PhD1, and Yulin Ge, MD1 | ||
1Department of Radiology, NYU Grossman School of Medicine, New York City, NY, United States, 2Soterix Medical Inc., New York City, NY, United States, 3Department of Biomedical Engineering, City College of New York, New York City, NY, United States |
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The underlying biological mechanisms of transcranial direct current stimulation (tDCS) remain relatively uncharacterized. In this report, MRI measures for cerebral blood flow (CBF) and cerebral metabolic rate of oxygen (CMRO2) of healthy controls was acquired before and during tDCS to better understand real-time neuronal response. We observed a significant increase in global CBF suggesting an increase of neuronal activity during compared to before tDCS. CMRO2 showed an increase of ~7% during tDCS compared to before tDCS. We suggest that the reported cortical excitability increase may also serve as a potential biomarker for neuronal reactivity or plasticity in many neurodegenerative diseases. |
| 1081
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Evaluation of Brain Glioma Using Non-Contrast Cerebral Blood Volume Mapping: Correlations between Vascular proliferation and Perfusion MR | |
| Yaoming Qu1, Qin Qin1,2, Haitao Wen1, Xiaochan Ou1, Yingjie Mei3, Weibo Chen4, and Zhibo Wen1 | ||
1Radiology, Zhujiang hospital of southern medical university, Guangzhou, China, 2F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States, 3Philips Healthcare, Guangzhou, China, 4Philips Healthcare, Shanghai, China |
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Cerebral blood volume (CBV) mapping employing velocity-selective saturation pulse trains is an emerging velocity-selective arterial spin labeling (VSASL) based method for quantifying perfusion with higher SNR. Its utility was assessed for glioma patients at 3T and corelation between histopathologic vascular proliferation and perfusion MR Imaging. VSASL based CBV mapping, in good agreement with DSC-PWI and VSASL based cerebral blood flow (CBF) mapping, showed great promise for accurate quantitative assessment and preoperative grading of brain gliomas, and further potential in the IDH genotype and vascular proliferation status predicting. |
| 1082 | Characterization of Microcirculatory Regulation in Skeletal Muscle using Wavelet Coherence Analysis of Resting-State BOLD MRI | |
| Jingting Yao1, Benjamin Risk1, Marijn Brummer1, Adam Daniel Singer1, Jeanie Park1, and David Reiter1 | ||
1Emory University, Atlanta, GA, United States |
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Microcirculatory regulation in the musculoskeletal system ensures tissue oxygenation and nutrient supply that are essential for maintaining normal muscular functions. BOLD MRI-derived mapping indices M0 and T2* have previously been established as markers of blood volume and blood oxygenation in healthy subjects. This study assesses dynamic resting-state microcirculation in the calf of healthy subjects using the wavelet coherence analysis, a time-frequency approach. Quantitative wavelet-based metrics characterizing the dynamic relationship between M0 and T2* may serve as markers of blood perfusion control and useful for characterizing degraded peripheral microvascular control in diseased population. |
| 1083 | Evaluating the Effects of Motion Compensation to IVIM Fitting in In-Vivo DW-MRI of the Muscle | |
| Jaume Coll-Font1,2,3, Or Perlman2,3, Shi Chen1, Robert A Eder1, Christian T. Farrar2,3, and Christopher T. Nguyen1,2,3 | ||
1Cardiovascular Research Center, Cardiology Division, Massachusetts General Hospital, Charlestown, MA, United States, 2Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States, 3Harvard Medical School, Boston, MA, United States |
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In order to acquire diffusion-weighted images (DWI) of the heart, motion compensated (M2) techniques are needed. However, these reduce the sensitivity to perfusion (D*) and hence hamper the accurate estimation of IVIM parameters. Here, we evaluate the effects of M2 to the IVIM estimates in the lower leg muscle and assess feasibility of an approach to combine DWI acquired with and without M2 to fit IVIM models. Our results show that M2 underestimates D* in the IVIM model. On the other hand, the combined approach resulted in IVIM parameter estimates similar to those obtained with standard DW MR. |
| 1084 | Comparing Preservation of Ex-Vivo Lungs for Transplantation, Using 31P MRS: Extended Ex-Vivo Lung Perfusion and Cold Static Storage | |
| Jonathan Snow1, Mehrdad Pourfathi1, Ian Duncan1, Harrilla Profka1, Stephen Kadlecek1, Yi Xin1, Mostafa Ismail1, Sarmad Siddiqui1, Luis Loza1, Tahmina Achekzai1, Xiaoling Jin1, Hooman Hamedani1, Faraz Amzajerdian1, Federico Sertic1, Kai Ruppert1, Ryan Baron1, Gabriel Unger1, Maurizio Cereda1, Shampa Chatterjee1, and Rahim Rizi1 | ||
1University of Pennsylvania, Philadelphia, PA, United States |
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Due to a shortage of transplantable lungs, careful preservation of viable donor lungs is of paramount importance. Ex-Vivo Lung Perfusion (EVLP) and cold static storage are two clinical techniques used to preserve donor lungs prior to transplantation. In this study, magnetic resonance spectroscopy was used to compare the ability of un-ventilated normothermic EVLP vs. cold static storage to preserve rat lungs’ ATP energy status over a 5-hour ischemic period. The EVLP model was slightly better than cold static storage at sustaining the lungs’ ATP. |
| 1085 | High resolution BBB water exchange rate mapping with multi-delay diffusion prepared pseudo-continuous arterial spin labeling | |
| Xingfeng Shao1 and Danny JJ Wang1,2 | ||
1Laboratory of FMRI Technology (LOFT), Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States, 2Department of Neurology, University of Southern California, Los Angeles, CA, United States |
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A segmented 3D diffusion prepared pseudo-continuous arterial spin labeling (DP-pCASL) sequence is proposed to acquire high resolution whole brain map of water exchange rate (kw) across the blood-brain barrier. And a new acquisition protocol is proposed which acquires DP-pCASL signals at multiple long post-labeling delays (PLDs) and allows kw to be quantified with a robust regression step and without the need for signal division or additional physiological parameter as inputs. |
| 1086 | Short-term reproducibility of cerebral metabolism using magnetic resonance imaging | |
| Ulrich Lindberg1, Signe Sloth Madsen2, Karsten Skovgaard Olsen2, Kirsten Møller2,3, Mohammad Sohail Asghar2, Henrik Bo Wiberg Larsson1,3, and Mark Bitsch Vestergaard1 | ||
1Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, Copenhagen, Denmark, 2Department of Neuroanaesthesiology, Rigshospitalet, Copenhagen, Denmark, 3Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark |
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The aim of this study was to investigate the short-term physiological variation in global cerebral perfusion, oxygen consumption and metabolite concentration, measured by MRI. Global cerebral oxygen consumption as well as N-acetyl-aspartate concentration remain stable over a one-week period. Global cerebral perfusion and lactate concentration was correlated, though showed decreasing within-subject correlation with increasing delay between scan session during the one-week follow-up period. These results should be carefully considered when performing longitudinal studies. In conclusion MRI does provide robust reliable measurements of global cerebral metabolism. |
| 1087 | The use of a DSC-MRI perfusion atlas for cerebral blood volume normalization and its impact in improving prognostic estimation. | |
| Elies Fuster-Garcia1, Javier Juan Albarracín2, Ivar T Hovden3, Maria del Mar Ávarez-Torres2, Alex Rovira4, Laura Oleaga5, Antonio J. Revert6, Silvano Filice7, Juan Miguel García-Gómez2, and Kyrre Eeg Emblem8 | ||
1Diagnostic Phyisics, Oslo University Hospital, Oslo, Norway, 2Universitat Politècnica de València, València, Spain, 3Oslo University Hospital, Olso, Norway, 4Hospital Universitari Vall d'Hebron, Barcelona, Spain, 5Hospital Clínic, Barcelona, Spain, 6Hospital de Manises, Manises, Spain, 7Azienda Ospedaliero-Universitaria di Parma, Parma, Italy, 8Diagnostic Physics, Oslo University Hospital, Oslo, Norway |
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In this work we present a method to improve the normalization of CBV maps by using a CBV atlas of the brain. This CBV atlas was generated using 134 non-linearly registered CBV maps from NCT03439332 clinical study. The proposed normalization method generates CBV values that better correlate with the patients’ OS, reaching smaller more significant p-values (p=0.034) based on Cox regression analysis, that better differentiate between high and low survivors (AUC=0.60, p=0.007) based on Kaplan Meier analysis. |
| 1088 | Prediction of Pial Collaterals using Delay and Dispersion Corrected MR Perfusion in Ischemic Stroke | |
| Yong Ik Jeong1, Gregory Christoforidis1, Niloufar Saadat1, Steven Roth2, Marek Niekrasz1, and Timothy Carroll1 | ||
1University of Chicago, Chicago, IL, United States, 2University of Illinois College of Medicine, Chicago, IL, United States |
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After the onset of an ischemic stroke, blood flow may be restored to the affected territory via pial collateral blood vessels. In this study we investigate whether delay and dispersion corrected MR DSC perfusion can accurately measure the additional blood flow to estimate pial collaterals. The percent difference between non-corrected and corrected CBF is compared against measured pial collateral scores. The percent difference in CBF is found to be predictive of pial collateral scores. With more research, corrected MR DSC CBF may be used in the clinical setting for stroke patient management. |
| 1089 | Dependency of R2(*) Relaxation on Gd-DTPA Concentration in Arterial Blood: Influence of Hematocrit and Magnetic Field Strength | |
| Daniëlle van Dorth1, Krishnapriya Venugopal2, Dirk H. J. Poot2, Marion Smits2, Jeroen H. J. M. de Bresser3, Juan A. Hernandez-Tamames2, and Matthias J. P. van Osch1 | ||
1C. J. Gorter Center for High-Field MRI, Radiology, Leiden University Medical Center, Leiden, Netherlands, 2Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, Netherlands, 3Radiology, Leiden University Medical Center, Leiden, Netherlands |
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In quantitative dynamic susceptibility contrast (DSC) MRI measurement of the arterial input function (AIF) is required. Generally, a linear relation between the R2(*) relaxation and the arterial contrast agent concentration is assumed (or the AIF is measured outside of an artery), although this is invalid for gradient-echo. In this study an open-source simulation tool is adapted to determine how R2(*) depends on contrast concentration for different physiological and MR parameters and this tool is validated by previously acquired in vitro data. The results show that sequence type (gradient-echo versus spin-echo), hematocrit and field strength all affect the relation. |
| 1090 | Comparison of the arterial-voxel discriminatory power of DSC-MRI signal features and creation of a framework for determining optimal thresholds | |
| Rashed Sobhan1, Donnie Cameron1,2, and Glyn Johnson1 | ||
1Norwich Medical School, University of East Anglia, Norwich, United Kingdom, 2C.J. Gorter Centre for High Field MRI, Department of Radiology, Leiden University Medical Centre, Leiden, Netherlands |
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To estimate brain perfusion from DSC-MRI, tissues’ arterial inputs are detected considering different features of the concentration time curve (CTC) collectively. No study has explored the individual AV-discriminatory power and optimal tissue-voxel-elimination thresholds for these features. Here, the area-under-the-receiver-operating-characteristic(ROC)-curves evaluated the former, while ROC cut-offs gave the latter. Three features were more effective than others: their optimal thresholds discarded tissue-voxels with high specificity and sensitivity. The knowledge of individual AV-discriminatory powers will allow Radiologists to make more informed choices while assessing the arterial candidacy of a CTC; other sites can use this threshold detection technique as a general framework. |
| 1091 | Blood-brain barrier water exchange estimation using optimised contrast-enhanced ASL | |
| Elizabeth Powell1, Ben Dickie2, Yolanda Ohene2, Geoff JM Parker1,3,4, and Laura M Parkes2 | ||
1Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom, 2Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom, 3Department of Neuroinflammation, Queen Square Institute of Neurology, University College London, London, United Kingdom, 4Bioxydyn Limited, Manchester, United Kingdom |
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Contrast-enhanced ASL (CE-ASL) has been proposed as a method for measuring blood-brain barrier (BBB) water exchange. Altering the T1 of blood using a gadolinium-based contrast agent should allow the label location to be identified as a function of post-labelling delay time; however, the shorter T1 of blood water leads to a trade-off between contrast dose and SNR. We show using simulations that there is an optimal T1 of blood post-contrast that balances this trade-off. Using this information we estimate the expected accuracy and precision of BBB water exchange measurements using CE-ASL. Finally, we demonstrate the method in vivo. |
| 1092 | Diffusion-filtered exchange measurements of blood-brain barrier permeability to water | |
| Elizabeth Powell1, Marco Battiston2, and Geoff JM Parker1,3,4 | ||
1Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom, 2Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom, 3Department of Neuroinflammation, Queen Square Institute of Neurology, University College London, London, United Kingdom, 4Bioxydyn Limited, London, United Kingdom |
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We propose a method for quantifying water exchange across the blood-brain barrier (BBB) using diffusion-filtered exchange imaging. Careful design of the diffusion filter mitigates confounding effects from in-flowing blood water spins, and use of a two-compartment model aims to avoid known biases in the apparent exchange rate approximation. Using this approach, we optimise an acquisition protocol to provide maximum sensitivity to BBB water exchange and estimate the expected accuracy and precision of the method using simulations. The technique is then validated in a human volunteer. |
| 1093 | The Open Source Initiative for Perfusion Imaging (OSIPI): Contrast-based perfusion lexicon and reporting recommendations | |
| Ina Nora Kompan1, Ben Dickie2, Steven Sourbron3, Petra van Houdt4, Laura Bell5, Rianne van der Heijden6, Andrey Fedorov7, Jonathan Arvidsson8, Charlotte Debus9, David Clunie10, Ingomar Gutmann11, Chad Quarles5, Zaki Ahmed12, Ralf Floca1, and David Buckley13 | ||
1Medical Image Computing, German Cancer Research Center, Heidelberg, Germany, 2Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, United Kingdom, 3Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom, 4Department of Radiation Oncology, Netherlands Cancer Institute, Amsterdam, Netherlands, 5Barrow Neurological Institute, Phoenix, AZ, United States, 6Department of Radiology, Erasmus MC, Rotterdam, Netherlands, 7Brigham and Women’s Hospital, Boston, MA, United States, 8Department of Radiation Physics, University of Gothenburg, Gothenburg, Sweden, 9Steinbuch Centre for Computing, Karlsruhe Institute for Technology, Karlsruhe, Germany, 10PixelMed Publishing, LLC, Bangor, PA, United States, 11University of Vienna, Vienna, Austria, 12Mayo Clinic, Rochester, MN, United States, 13University of Leeds, Leeds, United Kingdom |
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As part of the Open Source Initiative for Perfusion Imaging (OSIPI), the aim of this work is to develop guidelines for reporting of contrast-based perfusion analysis in order to improve reproducibility, reusability and interoperability of perfusion analysis. For this, a perfusion analysis lexicon is developed, which provides standardized nomenclature for perfusion parameters and analysis processes, as well as a framework for reporting of analysis pipelines. The lexicon is intended to be a dynamically growing inventory updated by the perfusion community. For that, a variety of public feedback and review cycles are planned during the development process. |
| 1094
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The Open Source Initiative for Perfusion Imaging (OSIPI): DCE-MRI Challenge | |
| Anahita Fathi Kazerooni1, Laura C. Bell2, Floris Van den Abeele3, Ruben Verhack3, Xinze Zhou4, Salman Rezaei5, Zaki Ahmed6, Rianne Van Der Heijden7, Seyed Ali Nabavizadeh4, Leland S. Hu8, Hamidreza Saligheh Rad5, and Steven Sourbron9 | ||
1Department of Radiology, UPenn, Philadelphia, PA, United States, 2Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, PA, United States, 3Hyperfusion.ai, Gent, Belgium, 4University of Pennsylvania, Philadelphia, PA, United States, 5Quantitative MR Imaging and Spectroscopy Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran (Islamic Republic of), 6Mayo Clinic, Rochester, MN, United States, 7Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, Netherlands, 8Neuroradiology Division, Department of Radiology, Mayo Clinic, Phoenix, AZ, United States, 9University of Sheffield, Sheffield, United Kingdom |
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Dynamic contrast enhanced (DCE-) MRI is widely acquired as a part of neuroimaging protocol for evaluation of glioblastoma tumors before the start of therapy or monitoring and assessment of treatment response in longitudinal scans. Nonetheless, lack of a standardized quantification method has limited its application in clinical settings, multi-institutional studies and clinical trials. These challenges have motivated efforts to validate DCE-MRI using benchmark biomedical image analysis methods. The Open-Source Initiative for Perfusion Imaging (OSIPI) has designed the OSIPI-DCE challenge to evaluate and compare DCE tools in terms of accuracy, repeatability, and reproducibility of Ktrans estimation in the brain. |
| 1095
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Differentiation Between Active Tumor and Radiation Necrosis in Patients with Glioblastoma Based on Model Free DCE Analysis | |
| Idan Bressler1,2, Dafna Ben Bashat1,3,4, Orna Aizenstein3,5, Dror Limon3,6, Felix Bokestein3,7, Deborah T. Blumenthal3,7, Uri Nevo2,4, and Moran Artzi1,3,4 | ||
1Sagol Brain Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel, 2The Iby and Aladar Fleischman Faculty of Engineering Tel Aviv University, Tel Aviv, Israel, 3Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel, 4Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel, 5Division of Radiology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel, 6Division of Oncology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel, 7Neuro-Oncology Service, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel |
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A DCE based method for differentiation between active tumor tissue and radiation necrosis in patients with Glioblastoma is proposed. The study included 31 MRI scans of patients with Glioblastoma (6 patients with 4 longitudinal scans and 7 scans with biopsy results). The system is comprised of automatic, feature based discrimination of DCE dynamic data based on population analysis. Differentiation results show correlation to theoretical DCE models, and agreement with biopsy results in in the majority of cases. RANO based assessment of the differentiated results demonstrate potential for early detection of tumor progression. |
| 1096 | Effect of Normalization of DCE-MRI derived Tracer Kinetic Parameters on Glioma Grading | |
| Dinil Sasi S1, Rakesh K Gupta2, Rana Patir2, Suneeta Ahlawat2, and Anup Singh1,3 | ||
1Indian Institute of Technology Delhi, New Delhi, India, 2Fortis Memorial Research Institute, Gurugram, India, 3All India Institute of Medical Science, New Delhi, India |
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Arterial-Input-Function(AIF) is a pre-requisite in fitting generalized-tracer-kinetic-model(GTKM) to dynamic-contrast-enhanced(DCE) MRI data for computing tracer-kinetic-parameters(TKP). TKP are highly sensitive to peak and shape of AIF, and this results in variation in computed parameter values across studies. These variations can reduce accuracy of TKP in glioma grading. We hypothesize that propagation of these AIF related errors to TKP can be mitigated using normalization w.r.t. corresponding average TKP values of healthy tissue and normalized TKP might improve glioma grading. The proposed normalization w.r.t. healthy gray-matter tissue has significantly reduced variations of TKP and improved accuracy of glioma grading particularly using Ktrans. |
| 1097 | Repeatability of contrast kinetic parameters of whole tumor with isotropic resolution measured by 3D-UTE-GRASP method | |
| Jin Zhang1, Ayesha Bharadwaj Das1, James Tranos2, Karl Kiser1, Youssef Zaim Wadghiri2, and Gene Kim1,2 | ||
1Weill Cornell Medicine, New York, NY, United States, 2NYU Langone Health, New York, NY, United States |
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The repeatability of dynamic contrast enhanced (DCE)-MRI has not been fully studied, particularly with contrast kinetic parameters including intracellular water lifetime (τi). The purposes of this study were: (1) to investigate the repeatability of DCE-MRI with the newly proposed technique, 3D-UTE-GRASP (Golden angle Radial Sparse Parallel), which can provide isotropic high-resolution images for quantitative pharmacokinetic model analysis; and (2) to investigate the repeatability of intracellular water lifetime estimation using the two-flip angle DCE-MRI approach. |
| 1098 | Combination study of spectral CT and DCE-MRI quantitatively predicting vascular invasion of rectal cancer preoperatively | |
| Wan Dong1, Ailian Liu1, Anliang Chen1, Yuhui Liu1, and Lizhi Xie2 | ||
1Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, China, 2GE Healthcare, MR Research, Beijing, China |
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Vascular tumor thrombus has been proved to be closely related to the poor prognosis of rectal cance, of which the current gold standard for the diagnosis of is postoperative pathology. In this work, we explored the feasibility of spectral CT and DCE-MRI in quantitatively predicting vascular invasion of rectal cancer. Results showed that the arterial NIC combined with Ktrans can differentiate the vascular invasion from normal status more accurately. Therefore, spectral CT combined with DCE-MRI may serve as a feasible and non-invasive way in predicting vascular invasion of rectal cancer preoperatively, that is of great significance for clinical diagnosis. |
| 1099
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Tumor intracellular water residence time measured by DCE-MRI negatively correlates with the standard update value of 18F-FDG-PET | |
| Karl Kiser1, Jin Zhang1, and S. Gene Kim1,2 | ||
1Radiology, Weil Cornell Medical College, New York, NY, United States, 2Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, NY, United States |
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Intracellular water residence time (τi) is an important property of solid tumors, with implications in cellular energy turnover. Measurement of τi using the active contrast encoding MRI method offers insight into tumor microenvironment heterogeneity and potentially metabolic activity. Our study compares τi, measured using ACE-MRI, in mouse gliomas with the standardized uptake value (SUV) from 18F-FDG PET in order to investigate the feasibility of using τi as an imaging marker for cellular metabolic activity. |
| 1100 | A new image clustering method for assessing tumor heterogeneity induced by a drug treatment in DCE-MRI | |
| Kazuyuki Makihara1, Kazuya Sakaguchi1, Masayuki Yamaguchi2, Ken Ito3, Yusaku Hori3, Taro Semba3, Yasuhiro Funabashi3, Hirofumi Fujii2, and Yasuhiko Terada1 | ||
1Faculty of Pure and Applied Sciences, University of Tsukuba, Tsukuba, Ibaraki, Japan, 2National Cancer Center, EPOC, Division of Functional Imaging, Kashiwa, Chiba, Japan, 3Eisai Co.,Ltd. Oncology Business Group, Bunkyo City, Tokyo, Japan |
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Dynamic contrast-enhanced (DCE) -MRI has been widely used to assess tumor responses to anticancer drugs. Ktrans, one of the pharmacokinetic parameters of DCE-MRI, reflects blood perfusion and permeability in tumor tissue and is a good indicator of perfusion assessment. However, conventional analyses of DCE-MRI do not reflect drug response well, since tumor is extremely heterogeneous. In this study, we have developed a new method for quantitatively assessing the heterogeneous response of tumors during anticancer treatment, and applied it to examine the drug response of E7130, a novel anti-cancer agent with spatiotemporal variation in human breast cancer xenograft model. |
| 1101
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Two compartment quantitative transport mapping: evaluating tracer exchange rate between vascular and extravascular space | |
| Qihao Zhang1, Jin Zhang2, Gene Kim2, John Morgan2, Thanh Nguyen2, Pascal Spincemaille2, and Yi Wang1 | ||
1Cornell University, New York, NY, United States, 2Weill Cornell Medical College, New York, NY, United States |
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In this study, we introduce compartment modeling into quantitative transport mapping (QTM), with the goal of mapping both the blood flow and the tracer exchange between vascular space and extravascular space. The nonlinear optimization problem is solved using the Levenberg–Marquardt method. We validate two compartment QTM (2c-QTM) in a porous media simulation and apply this method to dynamic PET data. |
| 1102 | tMB Whole Heart Perfusion Imaging with Iterative Reconstruction at 3.0T | |
| Lixian Zou1,2, Changjun Tie1, Jian Xu3, Hairong Zheng1, Xin Liu1, and Yuan Zheng3 | ||
1Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Science, Shenzhen, China, 2Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, China, 3UIH America Inc., Houston, TX, United States |
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Auto-calibrated multiband CAIPIRINHA with through-time encoding (tMB) has been proposed to acquire multiple slices simultaneously without extra reference scans. Reference images are estimated from the consecutive cardiac phases at a lower temporal resolution for subsequent slice separation. We implemented the tMB method in a myocardial perfusion sequence and demonstrated the feasibility of whole heart perfusion imaging with tMB and iterative reconstruction using in a clinical setting. |
| 1103 | High-resolution Spiral First-pass Myocardial Perfusion Imaging using DEep learning-based rapid Spiral Image REconstruction (DESIRE) | |
| Junyu Wang1, Daniel Weller2, Patricia Rodriguez Lozano3, and Michael Salerno1,3,4 | ||
1Biomedical Engineering, University of Virginia, Charlottesville, VA, United States, 2Electrical and Computer Engineering, University of Virginia, Charlottesville, VA, United States, 3Medicine, University of Virginia, Charlottesville, VA, United States, 4Radiology, University of Virginia, Charlottesville, VA, United States |
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First-pass contrast-enhanced myocardial perfusion imaging is valuable for evaluating coronary artery disease (CAD). Spiral perfusion imaging techniques, using a motion-compensated L1-SPIRiT based reconstruction, are capable of whole-heart high-resolution perfusion imaging. However, this reconstruction is performed off-line and takes ~1 hour per slice. To address this limitation, we developed a DEep learning-based Spiral Image REconstruction technique (DESIRE) for spiral first-pass myocardial perfusion imaging, for both single-slice (SS) and simultaneous multi-slice (SMS) MB=2 acquisitions, to provide fast and high-quality image reconstruction and make rapid online reconstruction feasible. High image quality was demonstrated using the proposed technique for healthy volunteers and patients. |
| 1104 | Calibration of myocardial perfusion quantification using a dedicated two-compartment cardiac phantom | |
| Xenios Milidonis1, Richard Crawley1, and Amedeo Chiribiri1 | ||
1School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom |
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Myocardial perfusion quantification by cardiovascular MR imaging has shown great promise in the detection of coronary artery disease. However, the lack of true standardization of methods across centers hinders the effective comparison and pooling of measurements. We sought to develop a novel cardiac phantom mimicking dynamic contrast exchange between two myocardial compartments and use it for the calibration of perfusion measured using three common quantification methods. Without calibration, perfusion measurements differed significantly between methods. Calibration led to accurate and non-significantly different measurements, suggesting that it could be an effective and reliable approach for the universal standardization of quantification methods. |
| 1105 | Associate Focused Ultrasound-induced MR Signal Changes With Gd-Enhancement and Ktrans | |
| Tzu-Ming Hung1, Yu-Ting Jiang1, Cheng-Tao Ho1, Po-Hung Hsu2, Hao-Li Liu3, Chih-Kuang Yeh1, and Hsu-Hsia Peng1 | ||
1Department of Biomedical Engineering and Environmental Sciences, National Tsing Hua University, Hsinchu, Taiwan, 2Center for Advanced Molecular Imaging and Translation, Chang Gung Memorial Hospital, Taoyuan, Taiwan, 3Department of Electrical Engineering, Chang-gung University, Taoyuan, Taiwan |
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Blood brain barrier (BBB) can be opened transiently by the cavitation effect with the assist of focused ultrasound (FUS) and microbubble (MB). A previous study proved that FUS-induced MR signal changes can monitor cavitation effect in in vitro phantom experiments. However, whether MR signal changes can reflect BBB opening levels in vivo remains uncertain. In this study, a cavitation index (CI) map was employed to evaluate MR signal changes during FUS sonication in in vivo experiments. We aim to examine the relationship between MR signal change and BBB opening levels by associating CI map with Gd-enhancement and Ktrans maps. |
| 1106 | Assessment of Fatty liver disease in rats using quantitative transport mapping (QTM) method against pathology validation | |
| Qihao Zhang1, Xianfu Luo2, Thanh Nguyen2, Pascal Spincemaille2, and Yi Wang1 | ||
1Cornell University, New York, NY, United States, 2Weill Cornell Medical College, New York, NY, United States |
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We propose to assess the severity of Nonalcoholic fatty liver disease (NAFLD) using quantitative transport mapping (QTM), a recently introduced flow quantification method. A numerical simulation was performed to compare QTM with traditional kinetic modeling. QTM successfully reconstructed blood flow with high accuracy (relative root mean square error = 0.27). Using DCE MRI in 5 adult rats with methionine choline-deficient diet-induced NAFLD (grade F3) and in 13 untreated control rats, only the QTM derived velocity |u| showed a significant difference between NAFLD and healthy controls. |
| 1107 | Use of Reference Region Model to Improve Arterial Input Function Selection for Estimating Kidney Function with DCE-MRI | |
| Cemre Ariyurek1, Onur Afacan1, Jeanne Chow1, Simon K Warfield1, and Sila Kurugol1 | ||
1Radiology, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States |
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Estimating glomerular filtration rate (GFR) is crucial for diagnostic purposes. DCE-MRI is capable of measuring tracer kinetic parameters of kidney function. Tracer kinetic models require arterial input function to find tracer kinetic parameters such as filtration rate. However, determining the arterial input function concentration is challenging and important for estimating GFR accurately. Here, we propose to use reference region model to improve arterial input function selection to estimate GFR more accurately. Comparing the GFR values estimated using the improved arterial input function with the ground truth GFR, we have observed a significant decrease in the mean absolute error in GFR. |
| 1108 | Personalized DCE-MRI Parametric Mapping using GRASP and Iterative Joint Estimation of Arterial Input Function and Pharmacokinetic Parameters | |
| Yousef Mazaheri1, Nathanael Kim1, Yuliya Lakhman2, Ramin Jafari1, Hebert Vargas Alvarez2, and Ricardo Otazo1 | ||
1Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States, 2Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States |
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To develop a personalized DCE-MRI parametric mapping technique using high spatial and temporal resolution golden-angle radial sparse parallel MRI (GRASP) and patient specific iterative estimation of the arterial input function (AIF) and pharmacokinetic parameters. |
| 1109 | Significance of 3D Isotropic Resolution for Image Texture Analysis of Pharmacokinetic Model Parametric Maps | |
| Karl Kiser1, Jin Zhang1, and S. Gene Kim1,2 | ||
1Radiology, Weil Cornell Medical College, New York, NY, United States, 2Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, NY, United States |
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Quantitative analysis of MRI image features for estimating tumor grading and treatment response is a growing area of research, however a lack of reproducibility and validation present a major challenge in the field. Our study investigates how spatial resolution affects texture features of DCE-MRI images by comparing features generated from 3D isotropic high resolution kinetic parameter maps with typical thick slice maps. We demonstrate that 3D textural features can differ by several orders of magnitude when extracted from isotropic versus thick slice images. These findings have potentially significant implications in the predictive capabilities of texture features. |
| 1110 | Simulation and clinical validation of an algorithm for retrospective Arterial Input Function peak saturation correction | |
| Jean-Sébastien Louis1, Jacques Felblinger1,2, Olivier Huttin3, and Marine Beaumont1,2 | ||
1IADI, Inserm U1254, Université de Lorraine, Nancy, France, 2CIC-IT, Inserm 1433, Université de Lorraine and CHRU Nancy, Nancy, France, 3Pôle cardiologie, CHRU Nancy, Nancy, France |
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Arterial Input Function (AIF) is fundamental for quantitative perfusion analysis. However, AIF peak is underestimated when using common perfusion sequence such SR-turboFLASH due to signal saturation effect. This leads to biased perfusion parameters estimation. Accurate AIF sampling requires specific sequence or protocol imaging not widely available. We proposed a solution to correct AIF peak retrospectively from standard perfusion data. We evaluated the proposed algorithm in simulation on more than 90000 different AIF sampling scenarios. Eventually, we tested our algorithm on clinical data and compared the population AIF estimated from our solution to literature population AIF. |
| 1111 | High spatial-temporal resolved perfusion imaging: simultaneously DCE- and DSC-MRI acquisition using improved Spiral-Out-In (iSOI) sequence | |
| Yupeng Cao1,2, Jun Zhao1,2, Weinan Tang3, Wentao Liu1, and Dong Han1,2 | ||
1National Center for Nanoscience and Technology, Beijing, China, 2University of Chinese Academy of Sciences, Beijing, China, 3Wandong Medical Technology, Beijing, China |
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The combination of DCE and DSC MRI contribute to the higher accuracy of diagnosis than either alone. However, high spatial-temporal resolution sequences for DCE and DSC are absent in the clinical use. Herein, we propose an improved Spiral-Out-In (iSOI) sequence to simultaneously sample DCE and DSC signal with high spatial resolution. A model-based strategy for reconstruction of 8-fold accelerated MRI were employed to realize high temporal resolution imaging. The in-plane spatial resolution is 0.78 mm and the temporal resolution is 0.52 s. The perfusion parameters were calculated to verify the proposed method which has potential to benefit the accurate diagnosis. |
| 1112 | Correlation assessment between quantitative multimodality imaging metrics using a community detection algorithm | |
| Ramesh Paudyal1, Milan Grkovski1, Jung Hun Oh1, Heiko Schoder2, David Aramburd Nunez1, Vaios Hatzoglou2, Joseph O Deasy1, John L Hum1, Nancy Lee3, and Amita Shukla-Dave1,2 | ||
1Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States, 2Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States, 3Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States |
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This study aims to assess the correlation between the pre-treatment quantitative imaging metrics obtained from multimodality imaging (MMI) techniques such as 18[F]-FMISO PET/CT, 18[F]-FDG PET/CT, DW- and DCE- MRI describing tumor metabolism, hypoxia, diffusion, perfusion, and cell metabolic activity, using a community detection algorithm. The method partitioned the network into four groups with strong and weak connections. The community connection results show complementary, rather than competitive, information about tumor metabolism, hypoxia, diffusion, and perfusion. |
| 1312 | Whole-brain Diffusion Tensor Imaging Using Single-Shot Spiral Sampling | |
| Guangqi Li1, Xin Shao1, Xinyu Ye1, Xiaodong Ma2, and Hua Guo1 | ||
1Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China, 2Center for Magnetic Resonance Research, Radiology, Medical School, University of Minnesota, Minneapolis, MN, United States |
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Single-shot acquisition techniques are commonly used to acquire diffusion weighted images. Single-shot spiral sampling allows shorter TE acquisition, thus provides higher SNR compared to EPI acquisition. However, spiral acquisition is sensitive to field inhomogeneity. Blurring effects degrade the quality of spiral images. In this study, compared to previous studies, a relatively large acceleration factor was used to reduce the spiral readout duration, and off-resonance correction was implemented for deblurring. The results show that the proposed single-shot spiral sampling can achieve whole-brain diffusion tensor imaging. |
| 1313 | Dynamic parallel transmission for diffusion MRI at 7T | |
| Belinda Ding1, Iulius Dragonu2, Patrick Liebig3, Robin M Heidemann3, and Christopher T Rodgers1 | ||
1Wolfson Brain Imaging Centre, University of Cambrige, Cambridge, United Kingdom, 2Siemens Healthcare Limited, Firmley, United Kingdom, 3Siemens Healthineers, Erlangen, Germany |
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In this study, we showed the novel application of dynamic pTx pulses for diffusion MRI on a Siemens 7T Terra scanner, with an 8Tx32Rx Nova head coil. We compared the performance of subject-specific spokes pulses against traditional circularly polarised pulses in a healthy volunteer. We observed that pTx pulses improves the signal across the whole brain, especially in lower brain regions like the cerebellum. This leads to improved definition of diffusion tracts and higher FA values in the regions of interest. In conclusion, this work demonstrated the feasibility and benefits of using pTx pulses for diffusion MRI at 7T. |
| 1314 | Noise reduction in diffusion tensor imaging of the brachial plexus using single-shot DW-EPI with Compressed SENSE | |
| Takayuki Sada1, Hajime Yokota2, Takafumi Yoda1, Ryuna Kurosawa1, Koji Matsumoto1, Takashi Namiki3, Masami Yoneyama3, Yoshitada Masuda1, and Takashi Uno2 | ||
1Department of Radiology, Chiba University Hospital, Chiba, Japan, 2Diagnostic Radiology and Radiation Oncology, Graduate School of Medicine, Chiba University, Chiba, Japan, 3Philips Japan, Tokyo, Japan |
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The brachial plexus is a difficult region to obtain high-quality DTI. In DTI with SENSE, noise-like artifacts appear in the center of the image, resulting in poor image quality. It has been reported that C-SENSE (EPICS), which combines parallel imaging and compressed sensing, can reduce parallel imaging-derived artifacts and may be a more robust method for quantitative imaging than SENSE. This study compared EPICS with SENSE and SENSE×2 (same conditions as SENSE with increased NEX) in the brachial plexus region, and EPICS was a robust imaging method producing better reproducibility of ADC and FA values than SENSE and SENSE×2. |
| 1315 | Inversion-recovery prepared 3D oscillating gradient sequence (IR-OGprep-GRASE) improves time-dependency measurements in the human brain | |
| Haotian Li1, Yi-Cheng Hsu2, Tao Zu1, Zhiyong Zhao1, Ruibin Liu1, Yi Sun2, Yi Zhang1, and Dan Wu1 | ||
1Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China, 2MR Collaboration, Siemens Healthcare China, Shanghai, China |
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Oscillating gradient diffusion MRI enables diffusion measurement at short diffusion-time (td), but it is challenging on the clinical system. Here we proposed an inversion-recovery prepared 3D oscillating gradient (IR-OGprep-GRASE) sequence to improve td–dependency measurements in the human brain. The result indicated that in brain regions that are possibly contaminated by CSF signals, such as the hippocampus, td-dependent ADC changes were not evident with OGprep-GRASE but can be recovered by adding the IR module. With IR-OGprep-GRASE, we identified different td-dependent patterns between the gray and white matter, as well as between the head, body, and tail of hippocampus. |
| 1316 | ACcelerated Echo-train shifted EPTI (ACE-EPTI) for fast distortion-blurring-free high-resolution diffusion imaging with minimal echo time | |
| Zijing Dong1,2, Fuyixue Wang1,3, Lawrence L. Wald1,3, and Kawin Setsompop4,5 | ||
1Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States, 2Department of Electrical Engineering and Computer Science, MIT, Cambridge, MA, United States, 3Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, United States, 4Department of Radiology, Stanford University, Stanford, CA, United States, 5Department of Electrical Engineering, Stanford University, Stanford, CA, United States |
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ACcelerated Echo-train shifted EPTI (ACE-EPTI) is proposed for fast and high-fidelity dMRI and diffusion-relaxometry. Distortion- and blurring-free imaging at high resolution is achieved using the time-resolved imaging approach, which recovers sharp multi-contrast images at each echotime across a continuous readout window. A new spatiotemporal encoding is proposed for rapid acquisition, requiring only 3 shots for submillimeter imaging with the capability of self-navigated physiological phase correction. An echo-training shifting acquisition is also incorporated into ACE-EPTI to enable shortest possible TE, which provides 30-40% higher SNR-efficiency over single-shot EPI. High-quality diffusion images and diffusion-weighted quantitative maps acquired by ACE-EPTI are demonstrated in-vivo. |
| 1317 | Creating parallel-transmission-style MRI with deep learning (deepPTx): a feasibility study using high-resolution whole-brain diffusion at 7T | |
| Xiaodong Ma1, Kamil Uğurbil1, and Xiaoping Wu1 | ||
1Center for Magnetic Resonance Research, Radiology, Medical School, University of Minnesota, Minneapolis, MN, United States |
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Parallel transmission (pTx) has proven capable of addressing two RF-related challenges at ultrahigh fields (≥7 Tesla): RF non-uniformity and power deposition in tissues. However, the conventional pTx workflow is tedious and requires special expertise. Here we propose a novel deep-learning framework, dubbed deepPTx, which aims to train a deep neural network to directly predict pTx-style images from images obtained with single transmission (sTx). The feasibility of deepPTx is demonstrated using 7 Tesla high-resolution, whole-brain diffusion MRI. Our preliminary results show that deepPTx can substantially enhance the image quality and improve the downstream diffusion analysis. |
| 1318 | Distortion-Free Diffusion-Relaxometry Imaging with Self-navigated Cartesian-based Echo-Planar Time Resolved Acquisition (cEPTI) | |
| Erpeng Dai1, Philip K Lee1,2, Zijing Dong3,4, Fanrui Fu1, Kawin Setsompop1,2, and Jennifer A McNab1 | ||
1Department of Radiology, Stanford University, Stanford, CA, United States, 2Department of Electrical Engineering, Stanford University, Stanford, CA, United States, 3Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States, 4Department of Electrical Engineering and Computer Science, MIT, Cambridge, MA, United States |
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Recently, there has been a growing interest in developing distortion-free EPI acquisitions for high-fidelity diffusion, relaxometry and/or functional MRI. Point spread function (PSF)-based techniques have been proposed for distortion-free diffusion imaging. Another technique, echo-planar time resolved imaging (EPTI), has been demonstrated for distortion-free relaxometry with an EPI readout. Additionally, a combination of PROPELLER and EPTI has been reported for motion-robust simultaneous diffusion and relaxometry imaging. In this study, we develop a self-navigated Cartesian-based EPTI (cEPTI) acquisition for distortion-free diffusion-relaxometry imaging. In vivo human brain data demonstrate that high-quality distortion-free diffusion and relaxometry images can be acquired with the proposed cEPTI. |
| 1319 | Distortionfree multishot 3D diffusion weighted turbo spin echo imaging using cartesian spiral acquisition and data rejection | |
| Tim Schakel1, Tom Bruijnen1,2, and Marielle Philippens1 | ||
1Department of Radiotherapy, University Medical Center Utrecht, Utrecht, Netherlands, 2Computational Imaging Group for MRI diagnostics and therapy, Centre for Image Science, Utrecht, Netherlands |
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In this work a multishot 3D turbo spin echo (TSE) sequence is combined with a diffusion preparation module and a modified implementation of the cartesian spiral (CASPR) k-space sampling pattern. CASPR samples the center of k-space in each shot, providing redundancy and enabling self-navigated identification of corrupt data. Using low resolution reconstructions per shot, weights are assigned for each shot enabling a soft-weighted compressed sense reconstruction. Results are obtained in a phantom and healthy volunteers, demonstrating the feasibility in acquiring undistorted 3D diffusion images.
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| 1320 | Highly Segmented Multishot Diffusion Imaging With Spiral Readouts | |
| Yoojin Lee1, Franz Patzig1, and Klaas P. Pruessmann1 | ||
1Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zürich, Switzerland |
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Multi-shot acquisition for diffusion MRI is challenging due to shot-to-shot phase variations caused by motion. Multiplexed sensitivity-encoding (MUSE) tackles this problem by extracting phase estimates from reconstruction of individual shot images. In this approach, the feasible number of shots is limited by increasing g-factor noise penalty. Against this background, the present work studies the feasibility of highly segmented MUSE with spiral acquisition, which offers particularly benign g-factor behavior. To stabilize reconstruction, we explore the utility of moving from separate estimation of phase offsets to joint optimization of phase biases and image content. |
| 1321 | Simple improvement of Multi-Dimensional diffusion MRI(MD-dMRI) image quality by double-sampled EPI | |
| Nicolas Geades1, Oscar Jalnefjord2,3, Guillaume Gilbert4, and Maria Ljungberg2,3 | ||
1MR Clinical Science, Philips, Gothenburg, Sweden, 2Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden, 3Department of Radiation Physics, University of Gothenburg, Gothenburg, Sweden, 4MR Clinical Science, Philips, Markham, ON, Canada |
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This study presents a novel implementation of established methods to eliminate ghosting artifacts in Multi Dimensional diffusion MRI (MD-dMRI) images. By replacing scan time used for acquiring images purely used for averaging (when applicable), with EPI acquisitions at opposing readout directions, ghost artifacts can be eliminated. The implementation provides ghost-free images with a small increase in SNR and a minimal (7%) increase in scan time. |
| 1322 | Navigator-Free Submillimeter Diffusion MRI using Multishot-encoded Simultaneous Multi-slice (MUSIUM) Imaging | |
| Wei-Tang chapel Chang1, Khoi Minh Huynh2, Pew-Thian Yap1, and Weili Lin2 | ||
1Radiology, UNC at Chapel Hill, Chapel Hill, NC, United States, 2BRIC, UNC at Chapel Hill, Chapel Hill, NC, United States |
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One major challenge in submillimeter dMRI is the inherently low signal-to-noise ratio (SNR). to To address this issue, the simultaneous multislab (SMSlab) approaches were proposed but susceptible to slab boundary artifacts and require additional navigators for phase estimation. The gSlider sequences require relatively high RF power and peak amplitude, increasing SAR and complicating RF excitation. Here, we introduce a navigator-free approach called multishot-encoded simultaneous multi-slice (MUSIUM) imaging for enhanced SNR, low RF power and peak amplitude, and freedom from slab boundary artifacts. |
| 1323 | Motion-Insensitive Brain Diffusion MRI using Intra-Sequence Motion Updates: Interaction between TE and Tracking Frame Rate | |
| Artan Kaso1 and Thomas Ernst1 | ||
1Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, United States |
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Uncorrected head movement during DWI acquisitions can cause signal dropouts, due to rotation-induced imbalances in gradient moments. Using a fast optical tracking system, signal losses can be reversed by the realignment of the scanner’s gradient axes with the moving head. However, while experimentally the lost signals were recovered to a great extent, the residual gradient moments were larger than anticipated by simulations. We demonstrated that this was due to the discretized nature and asynchronous application of motion updates in relation to the pulse sequence, which can effectively cause bias in the correction of gradient moments. |
| 1324 | Multi-shot diffusion MRI of the human brain with motion-compensated oscillating gradients | |
| Eric Seth Michael1, Franciszek Hennel1, and Klaas Paul Pruessmann1 | ||
1Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland |
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High-resolution multi-shot acquisitions are commonly avoided in diffusion MRI because motion-related phase instability, which can result from diffusion encoding schemes with a nonzero first moment, often hampers image reconstruction. This issue can be circumvented through the use of motion-compensated diffusion gradient shapes derived from oscillating gradient spin-echo (OGSE) methodologies. The utility of this solution is demonstrated here for interleaved spiral scans performed using a high-performance gradient system. The robustness against motion of OGSE sequences provided a notable advantage compared to a standard diffusion sensitization sequence for the phase stability and subsequent quality of multi-shot acquisitions. |
| 1325 | Highly Accelerated Multi-shot EPI based Diffusion MRI Using SMS and Joint k-q Under-sampling Enabled Using Deep Learned Manifold Priors | |
| Merry Mani1, Vincent Magnotta1, and Mathews Jacob1 | ||
1University of Iowa, Iowa City, IA, United States |
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We propose a new acceleration and reconstruction method for highly accelerated multi-shot dMRI. The acceleration makes use of multi-band excitation in combination with joint k-q undersampling. We develop new iterative reconstruction with deep learned q-space manifold priors to enable the recovery for the DWIs from 12-fold under-sampled data. The reconstruction error is shown to be less than 3%. The proposed method enables utilization of multi-shot EPI trajectories for diffusion microstructure and connectivity studies requiring high q-space coverage, without prolonging scan time. |
| 1326 | Optimising spiral diffusion tensor cardiovascular magnetic resonance for high resolution ex-vivo STEAM imaging on a clinical scanner | |
| Malte Roehl1,2, Peter D Gatehouse1,2, Pedro F Ferreira1,2, Sonya V Babu-Narayan1,2, David N Firmin1,2, Dudley J Pennell1,2, Sonia Nielles-Vallespin1,2, and Andrew D Scott1,2 | ||
1National Heart and Lung Institute, Imperial College London, London, United Kingdom, 2Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, London, United Kingdom |
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We demonstrate STEAM spiral diffusion tensor cardiovascular magnetic resonance (DT-CMR) for high resolution ex-vivo imaging (1x1x2mm2) on a clinical 3T scanner. We optimized the coil combination method, diffusion weighting, number of spiral interleaves and averages. A comparison in ex-vivo porcine myocardium shows substantial improvements in image quality when using the spiral method over a single-shot STEAM EPI protocol acquired with matched duration, spatial resolution and diffusion encoding. |
| 1327 | The Influence of Navigator Acquisition on 3D Multi-slab DWI Reconstruction: A Comparison between 2D, 3D Acquired and Synthesized Navigator | |
| Simin Liu1, Erpeng Dai2, and Hua Guo1 | ||
1Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China, 2Department of Radiology, Stanford University, Stanford, CA, United States |
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3D multi-slab is SNR-efficient for isotropic high-resolution diffusion imaging. It can be combined with simultaneous multi-slice, namely SMSlab, for optimal SNR efficiency. In multi-slab, either 2D or 3D navigators can be acquired for inter-shot phase correction, while in SMSlab, only 2D navigators can be acquired. One study has proposed to synthesize a 3D navigator from a 2D navigator in SMSlab, yet lacking a comparison. This study compares the performance of 2D, 3D acquired and synthesized navigators. The synthesized 3D navigator shows similar performance with the acquired 3D navigator in multi-slab and outperforms the 2D navigator in both multi-slab and SMSlab. |
| 1328 | Four-shot Navigator-free Spiral Acquisition Strategy for High-resolution Diffusion Imaging | |
| Guangqi Li1, Xinyu Ye1, Xin Shao1, Xiaodong Ma2, and Hua Guo1 | ||
1Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China, 2Center for Magnetic Resonance Research, Radiology, Medical School, University of Minnesota, Minneapolis, MN, United States |
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Multi-shot acquisition is widely used for high-resolution diffusion weighted imaging (DWI). For multi-shot spiral DWI, one of the challenges is correcting shot-to-shot phase variations. Uniform density spiral (UDS) is a navigator-free acquisition scheme with high efficiency of spatial encoding. Previous studies indicated that POCS-ICE algorithm can iteratively solve the phase errors for navigator-free acquisitions in multi-shot diffusion imaging. Another challenge is off-resonance correction. In this study, we proposed two acquisition strategies to reduce spiral readout duration for alleviating blurring effects. High-resolution diffusion-weighted images can be acquired using a 4-shot navigator-free spiral acquisition. |
| 1329 | Super-resolution and distortion-corrected diffusion-weighted imaging using 2D super-resolution generative adversarial network | |
| Pu-Yeh Wu1, Weiqiang Dou1, Hongyuan Ding2, Jiulou Zhang3, Yong Shen1, Guangnan Quan1, Zhangxuan Hu1, and Bing Wu1 | ||
1GE Healthcare, Beijing, China, 2Radiology Department, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China, 3Artificial Intelligence Imaging Laboratory, School of Medical Imaging, Nanjing Medical University, Nanjing, China |
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We proposed a deep learning-based method for super-resolution and distortion-corrected DWI reconstruction with a visual perception-sensitive super-resolution network SRGAN and multi-shot DWI as target. Our preliminary results demonstrated that the proposed model could produce satisfactory reconstruction of super-resolution diffusion images at b = 0 and 1000 s/mm2, and the geometric distortions in prefrontal cortex and temporal pole were well corrected. Furthermore, SRGAN reconstructed images provide comparable texture details to that of multi-shot DWI. With these findings, this developed model may be considered an effective tool for detecting subtle alterations of diffusion properties with only regular T2WI and DWI as inputs. |
| 1330 | Evaluation of Saturation Effects in Simultaneous Multi-Contrast (SMC) Imaging | |
| Nora-Josefin Breutigam1, Daniel Christopher Hoinkiss1, Mareike Alicja Buck 1,2, Klaus Eickel1,2, Matthias Günther1,2, and David Porter3 | ||
1Imaging Physics, Fraunhofer MEVIS, Bremen, Germany, 2Faculty 01 (Physics/Electrical Engineering), University Bremen, Bremen, Germany, 3Imaging Centre of Excellence (ICE), University of Glasgow, Glasgow, Scotland |
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Simultaneous multi-contrast imaging (SMC) can be used to combine acquisition of diffusion-weighted (DW) and T2*-weighted (T2*W) images into a single scan. Compared to conventional single-contrast imaging, SMC reduces the total scan time and improves image registration. However, saturation effects can reduce SNR and alter contrast. In this study, these effects are investigated in simulations, in phantoms, and in vivo. By using the results of this study to control saturation effects in SMC, the method enables rapid acquisition of distortion-matched, high-quality, well-registered DW and T2*W imaging, which could support rapid diagnosis and treatment of acute stroke. |
| 1331 | Distortion-free high-resolution diffusion weighted imaging of mouse brain using diffusion-prepared 3D VF-RARE | |
| Qiang Liu1,2, Yuanbo Yang1,2, Xinyuan Zhang1,2, Yingjie Mei1,2,3, Qiqi Lu1,2, Guoxi Xie4, and Yanqiu Feng1,2 | ||
1School of Biomedical Engineering, Southern Medical University, Guangzhou, China, 2Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China, 3Philips Healthcare, Guangzhou, China, 4Department of Biomedical Engineering, School of Basic Sciences, Guangzhou Medical University, Guangzhou, China |
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The purpose of the present work was to achieve three-dimensional (3D) high spatial resolution diffusion weighted imaging (DWI) of mouse brain using diffusion-prepared 3D VF-RARE (DP 3D VF-RARE) sequence at 7 Tesla. To employ long echo trains while prospectively controlling signal variation during acquisition, variable flip angles (VF) were implemented in the refocusing pulse train. The results showed improved image quality with less distortion over 2D single-shot EPI and comparable signal-to-noise ratio (SNR). With the application of the presented sequence, undistorted diffusion-weighted mouse brain images were obtained with high spatial resolution and potential SNR efficiency. |
| 1332 | Improved Super-Resolution reconstruction for DWI using multi-contrast information | |
| Xinyu Ye1, Pylypenko Dmytro1, Yuan Lian1, Yajing Zhang2, and Hua Guo1 | ||
1Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China, 2MR Clinical Science, Philips Healthcare, Suzhou, China |
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In clinical scans, the acquired DWI images usually has limited resolution. Super resolution method has the potential to improve the image resolution without adding scan time. Here we propose a deep-learning based multi-contrast super resolution network with gradient-map guidance and a novel FA loss function to reconstruct high-resolution DWI images from low-resolution DWI images and high–resolution anatomical images. In-vivo DWI data are used to test the proposed method. The results show that the image quality can be improved. |
| 1333 | A Model-driven Deep Learning Method Based on Sparse Coding to Accelerate IVIM Imaging in Fetal Brain | |
| Tianshu Zheng1, Cong Sun2, Guangbin Wang2, Weihao Zheng1, Wen Shi1, Yi Sun3, Yi Zhang1, Chuyang Ye4, and Dan Wu1 | ||
1Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China,, Zhengjiang University, Hangzhou, China, 2Department of Radiology, Shandong Medical Imaging Research Institute, Cheeloo College of Medicine, Shandong University, 324, Jingwu Road, Jinan, Shandong, 250021, People's Republic of China, Shandong University, Jinan, China, 3Department of Radiology 2MR Collaboration, Siemens Healthcare China, Shanghai, China, Siemens Healthcare China, Shanghai, China, 4chool of Information and Electronics, Beijing Institute of Technology, Beijing Institute of Technology, Beijing, China |
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Intravoxel incoherent motion (IVIM) can be used to assess microcirculation in the brain, however, conventional IVIM requires long acquisition to obtain multiple b-values, which is challenging for fetal brain MRI due to excessive motion. Q-space learning helps to accelerate the acquisition but it is hard to be interpreted. In this study, we proposed a sparsity coding deep neural network (SC-DNN), which is a model-driven network based on sparse representation and unfold the parameter optimization process. Compared to conventional IVIM fitting, SC-DNN took only 50% of the data to reach the comparable accuracy for parameter estimation, which outperformed the multilayer perceptron. |
| 1334 | Jointly Denoise Diffusion-weighted Images Using a Weighted Nuclear Norm Minimization Approach | |
| Yujiao Zhao1,2, Linfang Xiao1,2, Zhe Zhang3, Yilong Liu1,2, Hua Guo4, and Ed X. Wu1,2 | ||
1Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong, China, 2Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China, 3China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China, 4Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China |
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Diffusion MRI intrinsically suffers from low signal-to-noise ratio (SNR), especially when spatial resolution or b-value is high. A typical diffusion MRI scanning session produces image sets with same geometries but different diffusion directions and b-values, thus these diffusion-weighted (DW) images often share strong structural similarities. In this study, we developed a joint denoising method for DW images based on low-rank matrix approximation. This denoising method exploits structural similarities of DW image set. Both simulation and in vivo brain experiments demonstrate significant noise reduction in all DW images, revealing more microstructural details in quantitative diffusion maps. |
| 1335 | SuperDTI: Superfast Deep-learned Diffusion Tensor Imaging | |
| Hongyu Li1, Zifei Liang2, Chaoyi Zhang1, Ruiying Liu1, Jing Li3, Weihong Zhang3, Dong Liang4, Bowen Shen5, Peizhou Huang6, Sunil Kumar Gaire1, Xiaoliang Zhang6, Yulin Ge2, Jiangyang Zhang2, and Leslie Ying1,6 | ||
1Electrical Engineering, University at Buffalo, State University of New York, Buffalo, NY, United States, 2Center for Biomedical Imaging, Radiology, New York University School of Medicine, New York, NY, United States, 3Radiology, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China, 4Paul C. Lauterbur Research Center for Biomedical Imaging, Medical AI research center, SIAT, CAS, Shenzhen, China, 5Computer Science, Virginia Tech, Blacksburg, VA, United States, 6Biomedical Engineering, University at Buffalo, State University of New York, Buffalo, NY, United States |
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The main factor that prevents diffusion tensor imaging (DTI) from being incorporated in clinical routines is its long acquisition time of a large number of diffusion-weighted images (DWIs) required for reliable tensor estimation. This abstract presents SuperDTI to learn the nonlinear relationship between DWIs (reduced in q-space and k-space) and the corresponding tensor-derived quantitative maps as well as fiber tractography. Experimental results show that the proposed method can generate fractional anisotropy and mean diffusivity maps, as well as fiber tractography, from as few as six undersampled raw DWIs with quality comparable to results from 90 DWIs using conventional tensor fitting. |
| 1336 | Deep learning for synthesizing high-b-value DWI of the prostate: A tentative study based on generative adversarial networks | |
| lei hu1, jungong Zhao1,2, Caixia fu3, and Thomas Benkert4 | ||
1Department of Diagnostic and Interventional Radiology, Shanghai Jiao Tong University Affiliated Sixt, 上海, China, 2Department of Diagnostic and Interventional Radiology, Shanghai Jiao Tong University Affiliated Sixt, shanghai, China, 3MR Application Development, Siemens Shenzhen magnetic Resonance Ltd, shanghai, China, 4MR Application Predevelopment, Siemens Healthcare, Erlangen, Gernmany, Erlangen, Germany |
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A deep learning framework based on a generative adversarial network (GAN) to synthesize high-b-value DWI (syn-DWIb1500) with high quality using the acquired standard b-value DWI (a-DWIb800-1000) was developed. Reader ratings for image quality and PCa detection were performed on the a-DWI b1500, syn-DWIb1500, and optimized syn-DWIb1500 sets. Wilcoxon signed-rank tests and MRMC-ROC were used to compare the readers’ scores and diagnostic capabilities of each DWI set, respectively. Optimized syn-DWIb1500 resulted in significantly better image quality (all P≤0.001) and a higher mean AUC than a-DWIb1500 and cal-DWIb1500 (all P≤0.042). |
| 1337 | IVIM Imaging of Lung Cancer: A Comparison Between Gradient-and Spin-Echo, Turbo Spin-Echo and Echo-Planar Imaging Techniques | |
| Tianyu Zhang1, Yishi Wang2, Chengxiu Yuan1, Xiaoyu Wang1, Jia Zhao1, and Huaqiang Sheng1 | ||
1The First Affiliated Hospital of Shandong First Medical University, Jinan, China, 2Philips Healthcare, Beijing, China |
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The aim of the study was to compare intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) for evaluating lung cancer using single-shot gradient- and spin-echo (SS-GRASE), single-shot turbo spin-echo (SS-TSE) and single-shot echo-planar imaging (SS-EPI) on a 3.0T MRI scanner. The signal-to-noise ratio (SNR), contrast signal-to-noise ratio (CNR), image distortion of lesions, ADC and IVIM parameters from the three sequences were compared. We found that GRASE-IVIM had the characteristics of short scan time and small distortion, relatively low SNR but high CNR. Our study showed that GRASE-IVIM has great potential for lung cancer. |
| 1338 | Flip-angle optimization for the diffusion-weighted SPLICE sequence for applications in brain imaging | |
| Sofie Rahbek1, Tim Schakel2, Faisal Mahmood3,4, Kristoffer H. Madsen5,6, Marielle E.P. Philippens2, and Lars G. Hanson1,5 | ||
1Department of Health Technology, Technical University of Denmark, Kgs. Lyngby, Denmark, 2Department of Radiotherapy, University Medical Center Utrecht, Utrecht, Netherlands, 3Laboratory of Radiation Physics, Odense University Hospital, Odense, Denmark, 4Department of Clinical Research, University of Southern Denmark, Odense, Denmark, 5Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark, 6Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kgs. Lyngby, Denmark |
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The RARE-based diffusion-weighted MRI sequence, SPLICE, provides diffusion-weighted images free of geometric distortions. However, the image quality in terms of spatial resolution and SNR needs to be improved. We suggest a framework based on optimization of the flip-angles in the refocusing pulse train to improve the SNR for a chosen spatial point-spread-function. Simulations based on EPG calculations indicate superiority of the optimized flip-angle scheme and experimental recordings on a 1.5 T scanner demonstrate the improvements in a practical setting. |
| 1339 | Validating the Accuracy of Multi-Spectral Metal Artifact Suppressed Diffusion-Weighted Imaging | |
| John Neri1, Matthew F Koff1, Kevin M Koch2, and Ek Tan1 | ||
1Radiology and Imaging, Hospital for Special Surgery, New York, NY, United States, 2Medical College of Wisconsin, Wauwatosa, WI, United States |
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Diffusion-weighted MAVRIC is a novel pulse sequence that can obtain quantitative diffusion values in regions with high susceptibility. The goal of this work is to compare the quantitative accuracy of DWI-MAVRIC with sequences currently available on clinical MR scanners, using a diffusion phantom and images acquired at different orientation and spatial offsets in the scanner. Overall, good linearity with diffusivity was observed, with a large positive ADC bias at low diffusivity in both axial and coronal DWI-MAVRIC noted. Right and left spatial offsets increased ADC errors that can be mitigated by gradient nonlinearity correction. |
| 1340 | Quantitative Accuracy of Diffusion-Weighted Imaging Techniques as a Function of Susceptibility Artifact Resilience | |
| Volkan Emre Arpinar1,2, Alexander D Cohen1, Sampada Bhave3, and Kevin M Koch1,2 | ||
1Radiology, Medical College of Wisconsin, Milwaukee, WI, United States, 2Center for Imaging Research, Medical College of Wisconsin, Milwaukee, WI, United States, 3Canon Medical Research USA, Cleveland, OH, United States |
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Diffusion weighted imaging(DWI) is a workhorse sequence for many clinical and research applications of MRI. Beyond the role in neuroimaging, DWI has also been deployed for use other anatomies outside the head. However, in some anatomies with air-tissue susceptibility boundaries or proximity to metallic implants, DWI assessment may be challenging due to substantial susceptibility artifacts. In this study, the diffusion quantification accuracy of several DWI sequences within increasing resilience to susceptibility artifacts were compared using an established DWI phantom. In addition, a controlled test of two sequences with substantial differences in susceptibility artifact reduction was performed on spinal cord DWI. |
| 1341 | Simultaneous Reconstruction of High-resolution Multi b-value DWI with Single-shot Acquisition | |
| Fanwen Wang1, Hui Zhang1, Fei Dai1, Weibo Chen2, Chengyan Wang3, and He Wang1,3 | ||
1Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China, 2Philips Healthcare, Shanghai, China, 3Human Phenome Institute, Fudan University, Shanghai, China |
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Compared with the standard imaging method, i.e. single-shot echo planar imaging for diffusion MRI, Multi-Shot EPI (MS-EPI) is featured with high spatial resolution, though suffering from longer scanning time and severer phase variations. This study proposed a novel method to reconstruct four-shot high-resolution DWIs from one-shot data for multiple b-values simultaneously, enabling the physiological feature transformation through different b-values. Trained on healthy volunteers, we succeeded in recovering the aliasing images which violates the Nyquist-Shannon theorem from one-shot DWI both on healthy people and tumor patients, showing great clinical generalization. |
| 1342 | Robust method for Whole Body DWIBS applied both Image based B0 Shimming and Blip-up Blip-down Distortion Correction | |
| Hiroshi Hamano1, Masami Yoneyama1, Yasutomo Katsumata2, Kazuhiro Katahira3, and Kenji Iinuma1 | ||
1Philips Japan, Tokyo, Japan, 2Philips Healthcare, Tokyo, Japan, 3Department of Radiology, Kumamoto Chuo Hospital, Kumamoto, Japan |
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DWIBS based on single shot echo-planar imaging (EPI) is a first-choice sequence in routine clinical examinations. However, it sometimes suffers from sever image distortion due to the presence of air within and/or at edge of the FOV, especially at the border of chest and abdomen. On the other hand, image based B0 shimming and blip-up blip-down distortion correction improved for image qualities of DWI. We demonstrated that whole body DWIBS applied both image based B0 shimming and blip-up blip-down distortion correction to provide higher robustness. |
| 1343 | Is Perfect Filtering Enough Leading to Perfect Phase Correction? | |
| Feihong Liu1,2, Junwei Yang2,3, Zhiming Cui2,4, Xiaowei He1,5, Jun Feng1,5, and Dinggang Shen2,6,7 | ||
1School of Information Science and Technology, Northwest University, Xi'an, China, 2School of Biomedical Engineering, ShanghaiTech University, Shanghai, China, 3Department of Computer Science and Technology, University of Cambridge, Cambridge, United Kingdom, 4Department of Computer Science, The University of Hong Kong, Hong Kong, China, 5State-Province Joint Engineering and Research Center of Advanced Networking and Intelligent Information Services, Xi'an, China, 6Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China, 7Department of Artificial Intelligence, Korea University, Seoul, Korea, Republic of |
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We cautiously analyze phase correction procedures, unveiling why they falsely introduce dark holes to diffusion-weighted images, and calibrate them with the goal of unbiased white matter microstructure estimation. The calibrated procedures properly rotate image contents to be negative, hence, dark hole issue is effectively avoided. |
| 1344 | Optimal Diffusion Sampling Scheme for High Performance Gradients | |
| Nastaren Abad1, Luca Marinelli1, Radhika Madhavan1, James Kevin DeMarco2, Robert Y Shih2,3, Vincent B Ho2,3, Gail Kohls2, and Tom K.F Foo1 | ||
1General Electric Global Research, Niskayuna, NY, United States, 2Walter Reed National Military Medical Center, Bethesda, MD, United States, 3Uniformed Services University of the Health Sciences, Bethesda, MD, United States |
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In order to establish a benchmark for future studies, we utilize a data driven approach towards optimizing diffusion sampling for an ultra-high-performance gradient MRI sub-system as a means to establish minimal discrepancy compared to a fully sampled, defined superset. This study focused on b-value contribution and the impact of decreased sampling on uncertainty of diffusion and kurtosis tensor estimates, and fiber orientation to resolve sub-voxel information. |
| 1345 | Highly-Accelerated Multi-shot Diffusion Imaging with High Angular Resolution Enabled by k-d SVD | |
| Shihui Chen1 and Hing-Chiu Chang1 | ||
1Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, Hong Kong |
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High angular resolution diffusion imaging (HARDI) is a useful tool for neuroscience research, but the widespread clinical applications are limited by its long scan time and low spatial resolution. Multiple strategies have been proposed to achieve in-plane acceleration to improve the scan efficiency and geometric fidelity for HARDI. However, the feasible in-plane acceleration factor is still limited by the number of coils and the noise amplification associated with parallel imaging reconstruction. In this study, we proposed a reconstruction method based on SVD for HARDI to achieve superior reconstruction performance, even when acceleration factor is greater than number of coils. |
| 1346 | Improved multi-shot EPI ghost correction for high gradient strength diffusion MRI using Structured Low-Rank Modeling k-space reconstruction | |
| Gabriel Ramos-Llordén1, Rodrigo A. Lobos2, Tae Hyung Kim1, Qiyuan Tian1, Slimane Tounetki1, Thomas Witzel3, Boris Keil4, Anatasia Yendiki1, Berkin Bilgic1,5, Justin P. Haldar2, and Susie Huang1,5 | ||
1Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Masachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States, 2Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, United States, 3Q Bio Inc, San Carlos, CA, United States, 4Institute of Medical Physics and Radiation Protection, Mittelhessen University of Applied Sciences, Giessen, Germany, 5Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States |
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Multi-shot EPI diffusion MRI acquired using high diffusion-encoding gradient strengths suffers from severe ghosting artifacts, which can bias and confound the estimation of diffusion microstructural MRI measures at high b-values. In this work, we show that conventional EPI ghost correction techniques fall short in ghosting reduction when high diffusion-encoding gradient strengths ~250mT/m are used, and that advanced reconstruction algorithms based on structured low-rank matrix modeling can substantially reduce ghosting without introducing additional artifacts. |
| 1347 | Quantitative Evaluation of Multiband Diffusion MRI Data | |
| Arun Venkataraman1, Benjamin Risk2, Deqian Qiu3,4, Jianhui Zhong1,5, Feng (Vankee) Lin6,7, and Zhengwu Zhang8 | ||
1Physics and Astronomy, University of Rochester, Rochester, NY, United States, 2Biostatistics and Bioinformatics, Emory University, Atlanta, GA, United States, 3Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, United States, 4Biomedical Engineering, Emory University, Atlanta, GA, United States, 5Imaging Sciences, University of Rochester Medical Center, Rochester, NY, United States, 6Brain and Cognitive Sciences, University of Rochester, Rochester, NY, United States, 7Neuroscience, University of Rochester Medical Center, Rochester, NY, United States, 8Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY, United States |
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We sought to understand the implications of slice and phase acceleration factors on diffusion MRI (dMRI) data quality. As part of an on-going study about the impact of acceleration on dMRI quality, reconstruction, and data analysis, we acquired data from young and old, healthy subjects as well as mild cognitive impairment (MCI) subjects. From our study results, we found that there appears to be a trade-off between SNR loss due to higher acceleration and SNR gain from reducing the impact/magnitude of motion. Future studies should examine how the costs and benefits of acceleration impact diffusion metrics, tractography, and reproducibility. |
| 1348 | Deep Learning Based Super-resolution of Diffusion MRI Data | |
| Zifei Liang1 and Jiangyang Zhang1 | ||
1Center for Biomedical Imaging, Dept. of Radiology, New York University School of Medicine, NEW YORK, NY, United States |
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Deep-learning/machine-learning based super-resolution techniques have shown promises in improving the resolution of MRI without additional acquisition. In this study, we examined the capability of deep-learning based super-resolution using a newly developed network at resolutions from 0.2 mm to 0.025 mm. We also investigated whether the networks were able to enhance data acquired with a different contrast. Our results demonstrated that the enhancement of deep learning based super-resolution, although better than cubic interpolation, remained limited. In order to achieve the best performance, the network needs to be trained using data acquired at the target resolution and share similar contrasts. |
| 1349 | A General Framework for Automated and Accurate b-Matrix Calculation for dMRI Pulse Sequences | |
| Lisha Yuan1, Qing Li2, Guojing Wei3, Hongjian He1, and Jianhui Zhong4 | ||
1Department of Biomedical Engineering, Center for Brain Imaging Science and Technology, Zhejiang University, Hangzhou, China, 2MR Collaborations, Siemens Healthcare Ltd., Shanghai, China, 3SHS DI MR R&D SZN LP, Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China, 4Department of Imaging Sciences, University of Rochester, Rochester, NY, United States |
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Since both imaging and diffusion gradient pulses could lead to significant diffusion-related signal attenuation, one must account for the effect of all imaging and diffusion gradient pulses to achieve an accurate estimation of diffusion metrics and tensors. Based on a generalized definition of b matrix, a general framework for an automated and accurate b-matrix calculation was proposed in this study. Its correctness was verified in SE-diffusion sequence, and the importance of accurate inclusion of all gradient pulses was shown in both SE- and SPEN-diffusion sequence. The proposed method is suitable for accurate evaluation of diffusion effects in various sequences. |
| 1350 | Automatic Phase Image Texture Analysis for Motion Detection in Diffusion MRI (APITA-MDD) with Adaptive Thresholding | |
| Xiao Liang1, Pan Su2, Steve Roys1, Rao P Gullapalli1, Jerry L Prince3, and Jiachen Zhuo1 | ||
1Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, United States, 2Siemens Medical Solutions USA Inc, Malvern, PA, United States, 3Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, United States |
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In this study, we propose a more robust PITA-MDD method with automatic brain ROI selection and adaptive thresholding for the motion threshold (termed APITA-MDD). Automatic brain ROI is initially identified by Otsu’s method and then improved by erosion and dilation. Haralick’s Homogeneity Index (HHI) of each slice is converted to a deviation score independent of image SNR and ROI size for motion detection. APITA-MDD was tested on brain dMRI data acquired with head motion and leg crossing motion and correctly detected motion slices missed by PITA-MDD due to insufficient coverage at edge slices and single thresholding. |
| 1351 | Diffusion-Weighted Imaging with Integrated Slice-Specific Dynamic-Shimming for Rectal Cancer Detection and Characterization | |
| Jianxing Qiu1, Jing Liu1, Chenwen Liu2, Jinxia Zhu2, and Thomas Benkert3 | ||
1Peking University First Hospital, Beijing, China, 2MR Collaboration, Siemens Healthcare Ltd China, Beijing, China, 3MR Application Development, Siemens Healthcare GmbH, Erlangen, Germany |
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Diffusion-weighted imaging (DWI) with integrated slice-specific dynamic-shimming (iShim) could improve image quality compared with conventional 3D-Shimming single-shot echo-planar-imaging (SS-EPI) DWI in patients with rectal cancer. iShim DWI can help differentiate rectal cancer from normal walls and predict pathologic characterizations. iShim DWI could be an effective and promising approach and a good alternative to conventional 3D-Shimming SS-EPI DWI for patients with rectal cancer. |
| 1844 | How to Benchmark DSC-MRI: the technical development of an anthropomorphic phantom for software validation | |
| Laura C. Bell1, Natenael B Semmineh1, Sudarshan Ragunathan1, and C. Chad Quarles1 | ||
1Barrow Neurological Institute, Phoenix, AZ, United States |
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Clinical adoption of DSC-MRI for brain cancer imaging is plagued by reproducibility concerns. To support and advance reproducible science for DSC-MRI, an anthropomorphic phantom is developed in order to benchmark post-processing pipelines and software platforms. In addition to this anthropomorphic phantom, the technical computation of relative cerebral blood volume (rCBV) is discussed since rCBV is not an absolute measurement in DSC-MRI. In summary, this DRO-based benchmark can then be used to characterize the accuracy of commonly employed DSC-MRI algorithms and clinical software. |
| 1845 | Reproducibility and Validation of Water Permeability in Human Brain using Magnetization Transfer based ASL at 7T | |
| Sultan Zaman Mahmud1,2, Thomas S. Denney1,2, and Adil Bashir1,2 | ||
1Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, United States, 2Auburn University MRI Research Center, Auburn University, Auburn, AL, United States |
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Blood-brain barrier (BBB) is crucial to prevent brain tissue from circulating toxins while allowing the delivery of nutrients from intravascular space to the central nervous system (CNS). Compromised BBB can result in brain dysfunction and degeneration. Development of reproducible non-invasive techniques to assess BBB permeability is of particular interest. Previously we had demonstrated a non-invasive technique to estimate BBB permeability using magnetization transfer (MT) effect on labeled arterial spins at 7T. In this work, we demonstrate the reproducibility of the technique. The feasibility was evaluated in healthy subjects at baseline and after caffeine challenge. |
| 1846 | Cross-Vendor Test-Retest Analysis of 3D pCASL Cerebral Blood Flow | |
| Kay Jann1, Xingfeng Shao1, Samantha J Ma1,2, Karl G Helmer3, Michael Magaletta3, Mitchell J Horn4, Andrew D Warren4, Vanessa A Gonzalez4, Hanzhang Lu5, Yang Li5, Zixuan Lin5, Kaisha Hazel5, George Pottanat5, and Danny JJ Wang1 | ||
1Laboratory of Functional MRI Technology (LOFT), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California (USC), Los Angeles, CA, United States, 2Siemens Medical Solutions USA, Inc., Los Angeles, CA, United States, 3Department of Radiology, Massachusetts General Hospital and Athinoula A Martinos Center for Biomedical Imaging, Harvard Medical School, Charlestown, MA, United States, 4Department of Neurology, Massachusetts General Hospital and Athinoula A Martinos Center for Biomedical Imaging, Harvard Medical School, Charlestown, MA, United States, 5The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States |
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Standardized acquisition protocols have been recommended for Arterial Spin Labeling perfusion MRI across major MRI platforms. However, there are still vendor and sequence specific differences for ASL implementations that limit the use of ASL for clinical trials. Here we evaluated the repeatability of CBF measurements across 4 different MR platforms on a traveling cohort of 10 volunteers using standardized 3D background suppressed pCASL sequences. We show that while there are differences in global CBF values, relative CBF values are reproducible in major vascular territories across the 4 MRI platforms. |
| 1847 | Velocity-Selective Inversion prepared Arterial Spin Labeling: Examination in a Commercial Perfusion Phantom | |
| Feng Xu1,2, Dan Zhu3, Hongli Fan2,3, Hanzhang Lu1,2, Dapeng Liu1,2, Wenbo Li1,2, and Qin Qin1,2 | ||
11The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, United States, 2F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States, 3Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States |
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Standardized perfusion phantom allows for controlling reproducibility of arterial spin labeling (ASL) techniques across multiple sites, field strength, and vendors. Here using a commercial perfusion phantom, velocity-selective inversion (VSI) prepared ASL was compared with PCASL with an emphasis on velocity-encoding directions. While this effect is amplified on this phantom with feeding channels having only vertical and transverse flow directions, VSI-ASL with a tilted encoding direction achieved higher labeling efficiency through more uniform labeling of the entire feeding tubes. Careful selection of velocity-encoding directions along the major feeding arteries is recommended for VSASL applications to attain optimal labeling efficiency. |
| 1848 | A separate RF Neck Coil for Arterial Spin Labeling at 7T MRI | |
| Salem Alkhateeb1, Tales Santini2, Tiago Martins2, nadim farhat2, and Tamer S. Ibrahim2 | ||
1Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States, 2University of Pittsburgh, Pittsburgh, PA, United States |
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A dedicated labeling coil for arterial spin labeling (ASL) technique can alleviate the challenges at 7T MRI, in this work we propose a separate 16-channel RF neck coil for transmit only. Finite-difference time-domain (FDTD) simulations and RF shimming have demonstrated the feasibility of this design to produce a homogeneous B1+ fields in the labeling region (left and right common carotid arteries) while minimizing SAR to within safe limits. |
| 1849 | Increased labeling efficiency with Maxmin pTx B1+ shimming for pseudo-continuous Arterial Spin Labeling at 7T | |
| Kai Wang1, Samantha J Ma2, Xingfeng Shao1, and Danny JJ Wang1 | ||
1University of Southern California, Los Angeles, CA, United States, 2Siemens Medical Solutions USA, Inc, Los Angeles, CA, United States |
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The transmit magnetic field (B1+) drop and B0 field inhomogeneity at the labeling plane make it challenging to achieve high labeling efficiency at ultrahigh field for pseudo-continuous Arterial Spin Labeling (pCASL). In this study, we designed the pCASL sequence with “Maxmin” shimming for the labeling and “MinCV” shimming for the acquisition utilizing the parallel transmission (pTx). Phantom and in-vivo experiments suggest MinCV shimming can improve the profile homogeneity within ROI and that Maxmin-shimmed labeling is a promising approach to increase the labeling efficiency for pCASL. |
| 1850 | Blood flow measurements in diabetic kidney disease: A comparison of phase contrast, arterial spin labelling and dynamic contrast enhanced MRI | |
| Bashair Alhummiany1, David Shelley1,2, Margaret Saysell1,2, Maria-Alexandra Olaru3, Bernd Kühn3, David L. Buckley1, Julie Bailey2, Michael Mansfield2, Steven Sourbron4, and Kanishka Sharma4 | ||
1Department of Biomedical Imaging Sciences, University of Leeds, Leeds, United Kingdom, 2Leeds Teaching Hospitals, NHS Trust, Leeds, United Kingdom, 3Siemens Healthcare GmbH, Erlangen, Germany, 4Department of Imaging, Infection, Immunity and Cardiovascular Disease, The University of Sheffield, Sheffield, United Kingdom |
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Kidney perfusion can be measured using DCE or ASL, but clinical confidence in the assays is undermined by the large variability in published values. In this study, an intra-subject comparison was performed of DCE and ASL against phase-contrast RBF in 25 patients with diabetic kidney disease. Results show that the three techniques agree well on average, but pairwise agreement on the single-subject level remains poor. ASL agreed better with PC than DCE, but the difference was driven by a single DCE outlier. While RBF is a useful biomarker for studies at population level, individual patient management will require further optimization. |
| 1851 | High Temporal Resolution Wideband Dynamic Contrast-Enhanced Magnetic resonance imaging : The Mice Renal Function Study | |
| Wei-Hao Huang1, Chia-Ming Shih1, Po-Wei Cheng1, and Jyh-Horng Chen1,2 | ||
1Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan, Taipei, Taiwan, 2Interdisciplinary MRI/MRS Lab, Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan, Taipei, Taiwan |
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In this study, we aim to combine dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) and Wideband technique and use this accelerated sequence to assess the renal function of mice. With temporal resolution improvement, we can get more information in the same scan time, helping to perform a more accurate analysis. The quantitative analysis based on the Tofts model was performed and compare the result to the conventional DCE. All in all, we validate the feasibility of high temporal resolution Wideband DCE. |
| 1852 | Free-breathing Renal Perfusion Imaging with Multi-Delay Arterial Spin Labeling Using Subspace-Based Fast MR | |
| Paul Han1, Thibault Marin1, Yanis Djebra1,2, Georges El Fakhri1, Jinsong Ouyang1, and Chao Ma1 | ||
1Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States, 2LTCI, Télécom Paris, Institut Polytechnique de Paris, Paris, France |
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Renal perfusion imaging with multi-delay arterial spin labeling (ASL) can provide multi-parametric information along with more robust quantification of renal blood flow. However, renal perfusion imaging with ASL is challenging especially due to respiratory motion. This work presents a subspace-based fast MR method for free-breathing multi-delay ASL imaging of the kidney. The feasibility of the proposed method is shown using in vivo data obtained from a healthy volunteer on a 3T MR scanner. |
| 1853 | Quantification of Relative Cerebral Blood Volume in Aging Collapsin Response Mediator Protein 1 Gene Knockout Mice | |
| Tzu-Ming Hung1, Sheng-Min Huang2, Yun-Chieh Tsai3, Ting-Yu Chin4, and Hsu-Hsia Peng1 | ||
1Department of Biomedical Engineering and Environmental Sciences, National Tsing Hua University, Hsinchu, Taiwan, 2Institute of biomedical engineering and nanomedicine, National Health Research Institutes, Miaoli, Taiwan, 3Graduate Institute of Life Sciences, National Defense Medical Center, Taipei, Taiwan, 4Department of Bioscience Technology, Chung Yuan Christian University, Taoyuan, Taiwan |
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Mice deficient of collapsin response mediator protein 1 (CRMP-1) gene may cause neural disorganization in hippocampus and demonstrate memory and spatial learning dysfunction. Relative cerebral blood volume (rCBV) can reflect the blood volume within the tissue and was served as an index to correlate with psychosis progression. The purpose of this study was to quantify the rCBV of hippocampus and to explore the difference of vascular distribution in wild type (WT) and aging CRMP-1 knockout (KO) mice. KO mice possessed significantly higher rCBV in the hippocampus than WT mice, indicating the increased blood volume in the hippocampus of KO mice. |
| 1854 | Robust blood brain barrier integrity measurements in clinically significant short scan time | |
| Amnah Mahroo1, Nora-Josefin Breutigam1, Jörn Huber1, and Matthias Günther1,2 | ||
1MR Physics, Fraunhofer MEVIS, Bremen, Germany, 2MR-Imaging and Spectroscopy, University of Bremen, Bremen, Germany |
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Improved blood brain barrier integrity measurements in shorter scan times |
| 1855 | An increased Normal Appearing White Matter perfusion: a possible radiological inflammatory marker in relapsing-remitting multiple sclerosis | |
| Caterina Lapucci1,2, Marco Fiorelli3, Annunziata Stefanile4, Silvana Zannino4, Maria Maddalena Filippi5, Antonio Cortese3, Carlo Piantadosi6, Marco Salvetti7, Matilde Inglese1,8, and Tatiana Koudriavtseva4 | ||
1DINOGMI, University of Genoa, Genoa, Italy, 2Department of Experimental Neurosciences, Ospedale Policlinico San Martino IRCCS, Genoa, Italy, 3Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy, Rome, Italy, 4Department of Clinical Experimental Oncology, IRCCS Regina Elena National Cancer Institute, IFO, Rome, Italy, Rome, Italy, 5Fatebenefratelli Foundation, Afar Division, Fatebenefratelli Hospital, Isola Tiberina, Rome, Italy, Rome, Italy, 6Neurology Unit, San Giovanni-Addolorata Hospital, Rome, Italy, Rome, Italy, 7Department Of Neuroscience Mental Health And Sensory Organs (NEMOS), Sapienza University, Sant’Andrea Hospital, Rome, Italy, Rome, Italy, 8Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA/, New York, NY, United States |
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Hemodynamic changes by Dynamic Susceptibility Contrast enhanced perfusion (DSC) in Multiple Sclerosis (MS) have been poorly evaluated. The aim of the study was to compare relapsing and remitting (RR) MS patients by DSC. 45 RRMS patients, 22 with (REL) and 23 without (REM) relapse in the previous 2 months were included. A hyperperfusion of the Normal Appearing White Matter (NAWM) compared to FLAIR lesions was noted. The correlations between NAWM perfusion, disease duration and 1-year before Annualized Relapse Rate in REM patients seemed to suggest that an increased NAWM perfusion may be a radiological marker of higher inflammatory activity. |
| 1856 | Image Quality Optimization: DCE imaging of the Liver at 3T using a Continuously Acquired Radial Golden-angle Compressed Sensing Acquisition | |
| Hui Liu1, Gaofeng Shi1, Qinglei Shi2, Weishuai Wang3, Jiangyang Pan1, and Yang Li1 | ||
1Fourth Hospital of Hebei Medical University, shijiazhuang, China, 2MR Scientific Marketing, Siemens Healthcare, beijing, China, 3CS, Services,, Siemens Healthcare, jinan, China |
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The sequence that continuously acquired Golden-angle RAdial Sparse Parallel acquisition employing compressed sensing reconstruction (“GRASP”) can acquire high spatial and high temporal resolution as well as motion robustness to DCE MRI in liver imaging. However, there are still some artifacts in abdominal imaging, especially in the early arterial phase. In this study, we proposed an optimization scheme which can significantly improve the image quality both in plain and all enhanced phases, which may have important value in the study of abdominal disease using GRASP based DCE in future. |
| 1857 | Disentangling the heterogeneity of MCI condition by unsupervised clustering of brain measurements on ASL and T1w MR imaging | |
| Paolo Bosco1, Laura Biagi1, Giovanni Cioni2, Michela Matteoli3, Alessandro Sale3, Nicoletta Berardi3, Michela Tosetti1, and the Train the Brain Consortium4 | ||
1FiRMLAB, IRCCS Stella Maris Foundation, Pisa, Italy, 2IRCCS Stella Maris Foundation, Pisa, Italy, 3Institute of Neuroscience of the CNR, Pisa, Italy, 4the Train the Brain Consortium, Pisa, Italy |
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One of the main challenges in identifying people at risk of dementia is their clinical heterogeneity. One hypothesis is that the clinical symptoms may be the result of different biological processes. We applied a data-drive clustering approach on structural and perfusion brain-MR imaging on a cohort of 141 MCI subjects in order to elucidate homogeneous structural and perfusion profiles and we observed the correspondent clinical features. Unsupervised clustering identified 6 different clusters on both ASL and gray matter volume data. Perfusion and atrophy showed to be variable in the different clusters and showed dissimilar patterns at subcortical and cortical levels. |
| 1858 | A Convolutional Neural Network for Accelerating the Computation of the Extended Tofts Model in DCE-MRI | |
| Ke Fang1, Zejun Wang2,3, Zhaoqing Li2,3, Bao Wang4, Guangxu Han2,3, Zhaowei Cheng1, Zhihong Chen1, Chuanjin Lan5, Yi Zhang6, Peng Zhao7, Xinyu Jin1, Yingchao Liu8, and Ruiliang Bai2,3 | ||
1College of Information Science & Electronic Engineering, Zhejiang University, Hangzhou, China, 2Department of Physical Medicine and Rehabilitation of The Affiliated Sir Run Run Shaw Hospital AND Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China, 3Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China, 4Department of Radiology, Qilu Hospital of Shandong University, Jinan, China, 5School of Medicine, Shandong University, Jinan, China, 6Shandong Medical Imaging Research Institute, Shandong University, Jinan, China, 7Department of Neurosurgery, Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China, 8Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China |
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We proposed a customized conventional neural network (CNN) to fasten the computation time of non-linear pharmacokinetic models in DCE-MRI. The results demonstrated that the CNN could shorten the computation time of extended Tofts model of whole-brain data to less than a minute without sacrificing the agreements with conventional non-linear least square (NLLS) fitting. This CNN could serve as an alternative to conventional NLLS fitting for fast assessment of pharmacokinetic parameters in clinical practice. |
| 1859 | Changes of brain perfusion under anesthesia in humans – an explorative Arterial Spin Labeling study | |
| Thomas Lindner1,2, Hajrullah Ahmeti3, Dana Voß3, Monika Huhndorf2, Friederike Austein1,2, Michael Helle4, Olav Jansen2, Michael Synowitz3, and Stephan Ulmer2,5 | ||
1Department of Diagnostic and Interventional Neuroradiology, University Hospital Hamburg-Eppendorf, Hamburg, Germany, 2Department of Radiology and Neuroradiology, University Hospital Schleswig-Holstein, Kiel, Germany, 3Neurosurgery, University Hospital Schleswig-Holstein, Kiel, Germany, 4Tomographic Imaging Department, Philips Research Laboratories, Hamburg, Germany, 5Radiology, Kantonsspital Winterthur, Winterthur, Switzerland |
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Arterial Spin Labeling allows to intraoperatively monitor changes in perfusion induced by anesthesia. |
| 1860 | Brain response to acupuncture treatment in dysmenorrhea: An arterial spin labeling study | |
| Hui-Chieh Yang1, Cheng-Hao Tu2, and Shin-Lei Peng1 | ||
1Department of Biomedical Imaging and Radiological Science, China Medical University, Taichung, Taiwan, 2Graduate Institute of Acupuncture Science, China Medical University, Taichung, Taiwan |
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Studies on the brain responses to the pain-relieving treatments are relative limited, especially in dysmenorrhea. In this study, we investigated the brain response to acupuncture treatment in dysmenorrhea by using the arterial spin labeling technique. Results showed that after acupuncture treatment, significant decreases in cerebral blood flow were found in the pain-related regions, such as dorsal anterior cingulate cortex in the acupuncture group while orbitofrontal cortex, caudate, and insula in the sham acupuncture group. These findings suggest that acupuncture improves the descending pain modulation system by decreasing the neuronal activity in these brain regions. |
| 1861
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Perfusion mapping with sinusoidal CO2 respiratory challenge | |
| Chau Vu1, Jian Shen1, Matthew Borzage2, Soyoung Choi3, and John Wood4 | ||
1Biomedical Engineering, University of Southern California, Los Angeles, CA, United States, 2Fetal and Neonatal Institute, Children's Hospital Los Angeles, Los Angeles, CA, United States, 3Neuroscience Graduate Program, University of Southern California, Los Angeles, CA, United States, 4Pediatrics and Radiology, Children's Hospital Los Angeles, Los Angeles, CA, United States |
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Dynamic susceptibility contrast MRI is a popular perfusion technique that requires the use of intravenous exogenous contrast. To avoid gadolinium injection, this study proposed a perfusion MRI method based on a CO2 respiratory challenge, which delivers a sinusoidally-modulated CO2 stimulus. We evaluated this technique at two different stimulus amplitudes and reported cerebral blood flow (CBF), cerebral blood volume (CBV) and transit time (TT) within the acceptable range of the previous literature. |
| 1862 | Evidence for a sustained cerebrovascular response following motor practice | |
| Eleonora Patitucci1, Michael Germuska1, James Kolasinski1, Valentina Tomassini1,2,3, and Richard G Wise1,2 | ||
1CUBRIC, Cardiff University, Cardiff, United Kingdom, 2Institute for Advanced Biomedical Technologies (ITAB), Department of Neurosciences, Imaging and Clinical Sciences, University of Chieti-Pescara, Chieti, Italy, 3MS Centre, Neurology Unit, SS. Annunziata University Hospital, Chieti, Italy |
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Functional MRI can detect modifications in the brain’s resting state with learning-related behavioural improvements. However, the impact of learning on local cerebral blood flow after task execution remains unclear. Here we investigate changes in CBF after the execution of a motor task and demonstrate a sustained increase in resting CBF that is localised in regions relevant for the learning of the task. Our results show that learning induces sustained changes of local cerebral blood flow (over a timescale of minutes). |
| 1863 | Effect of subject-specific T1 values for arterial spin labelling on cerebral blood flow in mild stroke patients | |
| Michael S Stringer1,2, Cameron Manning1,2, Una Clancy1,2, Alasdair Morgan1,2, Zahra Shirzadi3,4, Francesca M Chappell1,2, Dany Jaime Garcia1,2, Angela CC Jochems1,2, Maria Valdes-Hernandez1,2, Stewart Wiseman1,2, Eleni Sakka1,2, Gordon W Blair1,2, Rosalind Brown1,2, Bradley MacIntosh3,4, Ian Marshall1,2, Fergus Doubal1,2, and Joanna M Wardlaw1,2 | ||
1Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom, 2UK DRI at the University of Edinburgh, Edinburgh, United Kingdom, 3Hurvitz Brain Sciences Research Program, Sunnybrook Health Sciences Centre, Toronto, ON, Canada, 4Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada |
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Accurate cerebral blood flow (CBF) quantification using arterial spin labelling (ASL) relies on physiological and MR parameters. Longitudinal relaxation time (T1) of blood, which depends on haematocrit, can be a factor in some patient groups. We determined subject-specific T1 using the DESPOT-1 HIFI method in a mild stroke cohort, calculating CBF using nominal and subject-specific values. CBF calculated with subject-specific T1 values was lower in grey and higher in white matter, though there was not a proportional bias. CBF was lower in patients with higher disease burden. Subject-specific T1 values can reduce variance, potentially improving CBF quantification in clinical ASL. |
| 2023 | Super-resolution and CNN denoising to improve the accuracy of small brainstem structure characterization with in vivo diffusion MRI | |
| Benjamin Ades-Aron1, Hong-Hsi Lee1, Heidi Schambra2, Dmitry S. Novikov1, Els Fieremans1, and Timothy Shepherd1 | ||
1Radiology, NYU School of Medicine, New York, NY, United States, 2Neurology, NYU Langone, New York, NY, United States |
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Diffusion MRI should be sensitive to early pathology or functional re-organization changes for small internal brainstem structures associated with ischemia, multiple sclerosis or neurodegeneration. Application of diffusion MRI to brainstem studies is challenged by limited spatial resolution, image distortion from skull base artifacts and bias introduced if diffusion contrast is also used for structure segmentation. We describe and evaluate a novel combination of Fast Gray Matter Acquisition T1 Inversion Recovery (FGATIR) denoising with deep learning, multi-modal nonlinear image co-registration and super-resolution techniques to improve the accuracy of small internal brainstem structure segmentation on advanced diffusion MRI data. |
| 2024 | Probabilistic structural atlas and connectome of brainstem nuclei involved in arousal and sleep by 7 Tesla MRI in living humans | |
| Maria Guadalupe Garcia Gomar1, Kavita Singh1, and Marta Bianciardi1 | ||
1Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States, Charlestown, MA, United States |
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Brainstem nuclei such as the medullary reticular formation, raphe nuclei, pontine nuclei, locus coeruleus and subcoeruleus, among others, play a crucial role in arousal and sleep. Despite their involvement in critical functions, their study in living humans is challenging due to limited resolution and contrast of conventional MRI. First, we precisely delineated nine arousal/sleep brainstem nuclei in 7 Tesla MRI of healthy humans and generated their validated in-vivo stereotaxic probabilistic atlas. Second, we evaluated their structural connectivity using 7 Tesla High-Angular-Resolution-Diffusion-Imaging and probabilistic tractography. This atlas and connectome might help evaluating disorders of consciousness, sleep disorders and neurological disorders. |
| 2025 | Investigating the Relationship Between Morphology and Microstructure in the Hippocampus | |
| Bradley Karat1, Jordan DeKraker1, Uzair Hussain2, and Ali Khan1,2 | ||
1Department of Neuroscience, Schulich School of Medicine & Dentistry, Western University, London, ON, Canada, 2Centre for Functional and Metabolic Mapping, Robarts Research Institute, Western University, London, ON, Canada |
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Aberrations of hippocampal subfields and microstructure are well studied, however, current in-vivo measures of microstructure are non-specific towards intra-hippocampal pathways and neurites within subfields. This is partly due to its complex and folded structure. Although highly folded, the hippocampus maintains an intrinsic coordinate system with well defined axes along the anterior-posterior, proximal-distal, and inner-outer dimensions. Importantly, hippocampal microstructure tends to align with these axes. Specific macrostructural measures such as gradient vector fields can be derived from these axes. Leveraging these measures, we were able to find systematic correlations between macrostructure and local microstructure in the hippocampus. |
| 2026 | Probing human cortical microstructure using diffusion MRI: Insights from N=17,646 individuals of the UK Biobank. | |
| Ivan Maximov1,2, Dennis van der Meer2, Ann-Marie de Lange2, Tobias Kaufmann2, and Lars T. Westlye2 | ||
1Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen, Norway, 2NORMENT, University of Oslo, Oslo, Norway |
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While diffusion MRI (dMRI) has been established as a powerful tool for studying human brain white matter, its potential for characterising structural grey matter properties waits for to be fully realised. dMRI is capable of providing unique complementary information about cortical microstructure, function and connectivity. Here, we describe the spatial distribution and individual differences in cortical grey matter microstructure across 17,646 UK Biobank (UKB) participants using three diffusion MRI approaches, namely, diffusion tensor imaging, kurtosis tensor imaging and spherical mean technique, and demonstrate its predictive value for brain age prediction using machine learning. |
| 2027 | Using Sub-Millimeter Isotropic DTI to Observe the Cortical Depth Dependence of Diffusion Anisotropy and Diffusivity in-vivo | |
| Iain P Bruce1, Yixin Ma1, and Allen W Song1 | ||
1Brain Imaging and Analysis Center, Duke University, Durham, NC, United States |
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The cerebral cortex is comprised of short column structures that span across the cortical layers between white matter and the pial surface. Subtle abnormalities in this microstructure, which may not be visible on anatomical scans, can have a large effect on brain function and development. In an effort to delineate such abnormalities, this study presents a technique to accurately and effectively observe the cortical depth dependence of diffusion anisotropy and diffusivity in-vivo using sub-millimeter isotropic resolution diffusion tensor imaging. |
| 2028 | Surface based analysis of cortical diffusion metrics: associations with cortical myeloarchitecture and underlying white matter anisotropy | |
| Tonima Sumya Ali1 and Fernando Calamante1,2 | ||
1School of Biomedical Engineering, The University of Sydney, Sydney, Australia, 2Sydney Imaging, The University of Sydney, Sydney, Australia |
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We employ structural and diffusion MRI metrics to evaluate their effectiveness for cortical segregation based on myelination, neurite density and microstructure in cortex. Three cortical measures (T1w/T2w, FA and total apparent fibre density, AFDtotal, demonstrated significant inter-correlations. Two track-weighted parameters (FOD and FA, measured in white matter adjacent to cortex), also showed significant correlations to cortical FA and AFDtotal. The spatial cortical patterns corresponding to these parameters suggest they provide complementary information on cortical features, and may help improve our understanding of cortical organisation in vivo and eventually lead to a further multi-parametric model for cortical parcellation. |
| 2029 | Generalized anisotropy profiles distinguish cortical and subcortical structures in ex vivo diffusion MRI | |
| Robert Jones1, Qiyuan Tian1, Chiara Maffei1, Jean Augustinack1, Aapo Nummenmaa1, Susie Huang1, and Anastasia Yendiki1 | ||
1Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States |
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We propose an approach to extracting a generalized anisotropy profile from the ensemble average propagator, which can be obtained either from diffusion spectrum imaging (DSI) data or from a generalized DSI analysis of diffusion MRI data acquired on q-shells. We validate this approach on data from ex vivo human tissue, acquired at 9.4T with 0.25 mm spatial resolution. We show that the proposed anisotropy profile can be used to distinguish between various white- and gray-matter structures, revealing fundamental differences in their microstructure. |
| 2030 | Comparison of high-resolution DTI in ex vivo newborn and adult marmoset brain | |
| Emmanuelle Weber1, Erpeng Dai1, Christoph Leuze1, Nikola T. Markov2, Nicholas Tran1, Mariko Bennett1, Samuel Baker1, Kerriann Casey1, Kalanit Grill-Spector1, Keren Haroush1, and Jennifer A. McNab1 | ||
1Stanford, Stanford, CA, United States, 2Buck Institute, Novato, CA, United States |
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High-resolution (0.15 mm isotropic) diffusion MRI of newborn and an adult marmoset brains were acquired. For the adult marmoset brain the diffusion MRI data of anterior and posterior parts of the brain were separately acquired and subsequently co-registered. Across the whole brain, fractional anisotropy (FA) was lower and mean diffusivity (MD) was higher (Fig. 4) in the newborn compared to the adult. The biggest differences were observed in white matter. Cingulate cortex region A25 showed the smallest difference, which aligns with previous studies showing its early stage development |
| 2031 | Is calibration necessary to relate NODDI, NODDIDTI, WMTI to axonal volume fraction? - A joint ex vivo MRI and histology study. | |
| Sebastian Papazoglou1, Mohammad Ashtarayeh1, Martina F. Callaghan2, Mark D. Does3,4,5,6, and Siawoosh Mohammadi1,7 | ||
1Department of Systems Neurosciences, University Medical Center Hamburg-Eppendorf, Hamburg, Germany, 2Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom, 3Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States, 4Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States, 5Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States, 6Department of Electrical Engineering, Vanderbilt University, Nashville, TN, United States, 7Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany |
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It is unknown whether the accuracy of DWI-model based estimates of the axonal water fraction could be enhanced by additional calibrations. In this study we compared three DWI-models (WMTI, NODDI, NODDIDTI) using histology data as gold standard in ex vivo mouse models with a broad dynamic range of axonal metrics. We found that all DWI-models improved with additional calibration. Models with fixed diffusivities benefited efficiently from an additional scaling, while the WMTI model was stronger affected by an additional offset. Furthermore, without any additional calibration, the axonal compartment biomarker from NODDIDTI could explain the data better than WMTI or NODDI. |
| 2032 | b-Value Dependency of Diffusion Parameters Derived from the DTI and DKI Models in Postmortem Human Brain Hemispheres | |
| Junye Yao1, Zihan Zhou1, Benjamin C. Tendler2, Karla L. Miller2, Lei Zhang3, Keqing Zhu3, Aimin Bao3, Hongjian He1, and Jianhui Zhong1,4 | ||
1Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrumental, Zhejiang University, Hangzhou, China, 2Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, London, United Kingdom, 3National Human Brain Bank for Health and Disease, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, China, 4Department of Imaging Sciences, University of Rochester, Rochester, NY, United States |
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Diffusion weighted images of formalin-fixed human brain hemispheres were used to study b-value dependence of diffusion parameters with the diffusion tensor and diffusion kurtosis model. Consistent decreases of FA with increasing b-values were observed in all hemispheres. Meanwhile, the mean kurtosis was found to increase with the discrepancy of FA between high and low b-value datasets. These results indicate that the b-value dependence of FA could be explained by non-gaussian diffusion effects consistent with tissue microstructure. |
| 2033 | Analysis of high-resolution 3T diffusion MRI data obtained with minimal CUSP acquisition scheme from a Non-Human Primate | |
| Alex Colin Valcourt Caron1, Amir Shmuel2, Ilana R. Leppert2, and Maxime Descoteaux1 | ||
1Université de Sherbrooke, Sherbrooke, QC, Canada, 2Montreal Neurological Institute, McGill University, Montreal, QC, Canada |
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The validation of advanced diffusion MRI methods requires acquisition at high-resolution and high SNR, which is difficult to obtain in humans. The use of anesthetized Non-Human Primates (NHPs) is key to unlocking valid microstructural maps. However, data acquisition and analysis tools must be adapted and configured for successful application to NHPs imaging. Here we propose a processing pipeline allowing for the analysis of diffusion data using DTI, CSD, and DIAMOND reconstruction, tailored for the analysis of data from the macaque brain. We present results obtained by applying the pipeline to a dataset acquired with a minimal CUSP 90 directions scheme. |
| 2034 | Scanning post mortem fixed whole human brain for advanced higher order diffusion modelling using a 300 mT/m whole-body MRI scanner | |
| Luke Joel Edwards1, Evgeniya Kirilina1,2, Carsten Jäger1,3, Kirsten Garus4, Markus Cremer4, Katrin Amunts4,5, and Nikolaus Weiskopf1,6 | ||
1Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 2Center for Cognitive Neuroscience Berlin, Freie Universität Berlin, Berlin, Germany, 3Paul Flechsig Institute of Brain Research, Leipzig University, Leipzig, Germany, 4Institute of Neuroscience and Medicine, Research Centre Jülich, Jülich, Germany, 5C. and O. Vogt Institute for Brain Research, Heinrich Heine University Düsseldorf, Düsseldorf, Germany, 6Felix Bloch Institute for Solid State Physics, Leipzig University, Leipzig, Germany |
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Higher order diffusion modelling (diffusional kurtosis and multi-tissue CSD) of a whole post mortem human brain with excellent tissue quality was enabled by ultra-high b values from a whole-body 3T scanner with ultra-strong gradients. This was complemented by a novel gradient nonlinearity correction scheme to interpolate signals onto diffusion shells before estimation of fibre distributions. The brain is part of the BigBrain initiative, and will undergo an extensive atlasing procedure. This dataset will thus extend the studies possible on the future BigBrain atlas, allowing investigation into diffusion microstructure imaging and tractography. |
| 2035 | Adapted Microscopy Estimation of Axon Diameters for Diffusion MRI Comparison | |
| Michael Paquette1, Cornelius Eichner1, Guillermo Gallardo1, and Alfred Anwander1 | ||
1Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany |
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The quantification of axon diameter from electron microscopy (EM) images requires a choice of heuristics to approximate the dimensions. This choice impacts the resulting size distributions and should be adapted to the task. In diffusion MRI, complex shapes are encoded based on their directional mean squared displacement. We compute diffusion-specific ground truth diameters using Monte-Carlo simulations and evaluate typical choices of EM image analysis heuristics against them. Further, we propose a new and simple heuristic based on the mean square displacement inside an ellipse to compute better axon diameter quantifications from electron microscopy. |
| 2036 | Selective microstructure-size filters for non-invasive quantitative MRI | |
| Milena Capiglioni1,2,3, Analía Zwick1, Pablo Jimenez1, and Gonzalo Álvarez1,2 | ||
1Laboratorio de Espectroscopía e Imágenes por RMN, Departamento de Física Médica, Centro Atómico Bariloche - CNEA - CONICET, Bariloche, Argentina, 2Instituto Balseiro, CNEA, Universidad Nacional de Cuyo, Bariloche, Argentina, 3Support Center for Advanced Neuroimaging (SCAN), Institute for Diagnostic and Interventional Neuroradiology, University Hospital of Bern, University of Bern, Bern, Switzerland |
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Extracting quantitative microstructure information of living-tissue by non-invasive imaging is an outstanding challenge for understanding disease mechanisms. We introduce a method to make selectively images of microstructure-sizes by probing molecule diffusion with MRI. It relies on designing dynamical control of nuclear spins to sense magnetization “decay-shifts” rather than the commonly used spin-echo decay-rates. The feasibility and performance of the method are illustrated with proof-of-principle experiments and simulations on typical size-distributions of white-matter in the mouse brain. These results position spin-echo decay-shifts as a promising MRI tool to perform non-invasive histology without assuming a microstructure distribution model. |
| 2037 | Validation of MRI-based axon radius index estimation using large-scale light microscopy and deep learning | |
| Mohammad Ashtarayeh1, Laurin Mordhorst1, Maria Morozova2,3, Tobias Streubel1,2, Jan Malte Oeschger1, Joao Periquito4, Andreas Pohlmann4, Henriette Rusch3, Carsten Jäger2, Thoralf Niendorf4, Nikolaus Weiskopf2,5, Markus Morawski2,3, and Siawoosh Mohammadi1,2 | ||
1Department of Systems Neurosciences, University Medical Center Hamburg-Eppendorf, Hamburg, Germany, 2Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 3Paul Flechsig Institute of Brain Research, University of Leipzig, Leipzig, Germany, 4Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany, 5Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany |
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We used a new method for validation of MRI-based axon radius index (ARI) mapping using large-scale light microscopy (lsLM) that provides a good representation of the fraction of large axons - the main contributors to the MRI-based ARI. The proposed method captures 100-1000 times more axons than current standard small field of view microscopy. We showed that the one-to-one correspondence between MRI-based ARI and lsLM-based effective axon radius is superior to the current standard method. |
| 2038 | Nonparametric D(ω)-distributions for model-free analysis of b(ω)-encoded multidimensional diffusion MRI on ex vivo rat brain | |
| Omar Narvaez1, Maxime Yon2, Alejandra Sierra1, and Daniel Topgaard3 | ||
1A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland, 2CEMHTI, French National Centre for Scientific Research, Paris, France, 3Department of Chemistry, Lund University, Lund, Sweden |
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Nonparametric distributions of cell sizes or diffusion tensors have recently been applied to analyze clinically relevant data acquired with advanced diffusion encoding schemes building on oscillating gradients, targeting the frequency-dependence and cell size, or more general q-vector trajectories focusing on the tensorial aspects. We introduce nonparametric D(ω)-distributions as a joint analysis framework taking both frequency-dependence and tensorial properties into account, and demonstrate the approach with ex vivo rat brain data acquired with gradient waveforms exploring the relevant dimensions of the tensor-valued encoding spectrum b(ω). |
| 2039 | Biophysical modeling of ex vivo diffusion MRI for the longitudinal characterization of axonal degeneration in the optic nerve | |
| Ricardo Coronado-Leija1, Santiago Coelho1, Omar Narvaez2, Jorge Larriva-Sahd3, Alonso Ramirez-Manzanares4, Luis Concha3, Dmitry S. Novikov1, and Els Fieremans1 | ||
1Radiology, New York University School of Medicine, New York, NY, United States, 2University of Eastern Finland, Kuopio, Finland, 3Instituto de Neurobiologia, Universidad Nacional Autonoma de Mexico, Queretaro, Mexico, 4Centro de Investigacion en Matematicas, Guanajuato, Mexico |
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In this work, we evaluated the parameters of the Standard Model (SM), augmented with a free water compartment, on ex vivo diffusion MRI, to detect longitudinal changes caused by axonal degeneration. Parameters of SM were estimated from the rotational invariants of the diffusion signal using a supervised machine learning approach. Axonal degeneration was induced by nerve injury using a rat retinal ischemia model. Comparisons with 2D histology derived metrics revealed that SM parameters are sensitive to changes caused by axonal degeneration, particularly axon loss. SM parameters also reveal presence of microglia, and increased orientation dispersion. |
| 2040 | Microstructural Diffusion MRI in Mouse Models of Severe and Repetitive Mild Traumatic Brain Injury | |
| Naila Rahman1,2, Kathy Xu2, Nico Arezza1,2, Kevin Borsos1,2, Matthew Budde3, Arthur Brown2,4, and Corey Baron1,2 | ||
1Medical Biophysics, Western University, London, ON, Canada, 2Robarts Research Institute, London, ON, Canada, 3Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, United States, 4Anatomy and Cell Biology, Western University, London, ON, Canada |
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Microstructural diffusion MRI (dMRI) improves the specificity required to detect microstructure changes related to pathophysiology. Oscillating gradient spin-echo (OGSE) dMRI is sensitive to structural disorder and microscopic anisotropy (µA) dMRI is sensitive to water diffusion anisotropy independent of neuron fiber orientation. In this work, OGSE and µA protocols were implemented to enable in vivo longitudinal scanning at 9.4T. Preliminary data in a rodent model of traumatic brain injury (TBI) revealed changes in mean diffusivity dependence on OGSE frequency post-TBI and changes in spherical tensor kurtosis (sensitive to cell size heterogeneity), compared to healthy mice. |
| 2041
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Susceptibility-induced fiber orientation dependency of the DWI signal in white matter measured in ex vivo rat brain at 7 T | |
| Sidsel Winther1,2, Mariam Andersson1,2, Henrik Lundell2, and Tim Dyrby1,2 | ||
1DTU Compute, Technical University of Denmark, Kongens Lyngby, Denmark, 2Danish Research Center for Magnetic Resonance, Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark |
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Magnetic susceptibility of myelin induces morphology- and orientation-dependent perturbations of the B_0-field. At the microstructural scale of brain white matter, the main contribution to these perturbations comes from myelin. Here, we show that a consequence of this is a fiber-orientation-dependent bias of the DWI-signal across white matter regions in an ex vivo rat brain. This implies that biophysical modeling must regard susceptibility at the microstructural scale in order not to become biased as well. Higher field strength will increase the bias and vice versa. Hence, especially pre-clinical scans are affected. |
| 2042 | In vivo validation of a data driven algorithm for multicomponent T2 mapping on a mice model of demyelination | |
| Noam Omer1, Ella Wilczynski1, Neta Stern1, Tamar Blumenfeld-Katzir1, Meirav Galun2, and Noam Ben-Eliezer1,3,4,5,6 | ||
1Department of Biomedical Engineering, Tel-Aviv University, Tel-Aviv, Israel, 2Department of Computer Science and Applied Mathematics, Weitzman institute of science, Rehovot, Israel, 3Department of Orthopedics, Shamir Medical Center, Zerifin, Israel, 4Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel, 5Sagol School of Neuroscience, Tel-Aviv University, Tel-Aviv, Israel, 6Center for Advanced Imaging Innovation and Research (CAI2R), New-York University Langone Medical Center, New York, NY, United States |
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Multicomponent T2 analysis (mcT2) can provide a clinically-useful myelin biomarker in vivo. Its clinical applicability, however, is hindered by lack of gold standard technique that can overcome the ambiguity of fitting several T2 components to a single experimental signal. In this study we aimed to validate the utility of a novel data-driven mcT2 mapping algorithm for quantifying myelin content. To that end, we applied the mcT2 algorithm to 14 mice divided into two groups of mice: cuprizone-induced demyelination model, and controls. Results show excellent agreement between the mcT2 based myelin biomarker and ground truth quantification of myelin from immunohistochemical staining. |
| 2043
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Cognitive training-derived microstructural and functional neuroplasticity and the neural mechanisms underlying the far-transfer effect | |
| Daisuke Sawamura1,2, Ryusuke Suzuki3, Shinya Sakai1, Keita Ogawa4, Xinnan Li2, Hiroyuki Hamaguchi2, and Khin Khin Tha5 | ||
1Department of Rehabilitation Science, Hokkaido University, Sapporo, Japan, 2Department of Biomarker Imaging Science, Hokkaido University, Sapporo, Japan, 3Department of Medical Physics, Hokkaido University Hospital, Sapporo, Japan, 4Department of Rehabilitation, Hokkaido University Hospital, Sapporo, Japan, 5Global Center for Biomedical Science and Engineering, Hokkaido University Faculty of Medicine, Sapporo, Japan |
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Little is known about how microstructural and functional neuroplasticity occurs upon cognitive training and the relationship between cognitive training-derived brain changes and cognitive performance. This prospective study aimed to elucidate cognitive training-derived neuroplasticity and the mechanism underlying transfer effects using diffusion spectrum imaging (DSI) and resting-state functional MRI (rsfMRI). The results suggest that the right inferior parietal lobule and its neural connections and the right cerebellar vermis may modulate the far-transfer effect. |
| 2044 | Quantifying tissue microstructural changes associated with short-term learning using model-based diffusion MRI | |
| Michele Guerreri1, Thomas Villemonteix2,3, Whitney Stee3, Evelyne Balteau4, Philippe Peigneux3,4, and Hui Zhang1 | ||
1Computer Science & Centre for Medical Image Computing, University College London, London, United Kingdom, 2Laboratoire de Psychopathologie et Neuropsychologie, Saint Denis, Paris 8 Vincennes - St Denis University, Paris, France, 3Neuropsychology and Functional Neuroimaging Research Group (UR2NF) at the Centre for Research in Cognition and Neurosciences (CRCN), Université Libre de Bruxelles, Brussels, Belgium, 4Cyclotron Research Centre, University of Liège, Liège, Belgium |
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We use model-based diffusion MRI to assess microstructural changes associated with short-term plasticity. Neuroplasticity changes are the foundation of experience. These mechanisms include microstructural rearrangements which can manifest even after short learning episodes. DTI has proven effective in highlighting such changes. However, the connection with the underlying microstructural processes remains speculative. Biophysical modelling can help interpreting such changes. We use NODDI and CHARMED models to examine MD changes obtained in a spatial navigation task. NODDI’s FWF and CHARMED’s hMD share similar cortical patterns of decrease as MD. FWF exhibited higher sensitivity than MD and hMD to capture microstructural changes. |
| 2045 | White matter microstructure associated with functional connectivity changes following short-term learning of a visuomotor sequence | |
| Stefanie A. Tremblay1,2, Anna-Thekla Jäger3, Julia Huck1, Chiara Giacosa1, Stephanie Beram1, Uta Schneider3, Sophia Grahl3, Arno Villringer3,4,5,6, Christine Lucas Tardif7,8, Pierre-Louis Bazin3,9, Christopher J Steele3,10, and Claudine J. Gauthier1,2 | ||
1Physics, Concordia University, Montreal, QC, Canada, 2Montreal Heart Institute, Montreal, QC, Canada, 3Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 4Clinic for Cognitive Neurology, Leipzig, Germany, 5Leipzig University Medical Centre, IFB Adiposity Diseases, Leipzig, Germany, 6Collaborative Research Centre 1052-A5, University of Leipzig, Leipzig, Germany, 7Biomedical Engineering, McGill University, Montreal, QC, Canada, 8Montreal Neurological Institute, Montreal, QC, Canada, 9Faculty of Social and Behavioral Sciences, University of Amsterdam, Amsterdam, Netherlands, 10Psychology, Concordia University, Montreal, QC, Canada |
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To characterize the temporal dynamics of plasticity, we conducted a longitudinal MRI study at ultra-high field (7T) during the learning process of a sequential visuomotor task, in a learning and control group. WM microstructure was altered in the tracts underlying the primary motor and sensorimotor cortices, and in tracts adjacent to the right supplementary motor area (SMA), where changes in functional connectivity were also found in this cohort. Our study provides evidence for short-term white matter plasticity in the sensorimotor network, where the SMA would play a key role in linking the spatial and motor aspects of motor sequence learning. |
| 2046 | Tissue Microstructural Changes following Four-Week Neurocognitive Training: Observations of Double Diffusion Encoding MRI | |
| Xinnan Li1, Daisuke Sawamura2, Hiroyuki Hamaguchi1, Yuta Urushibata3, Thorsten Feiweier4, Keita Ogawa5, and Khin Khin Tha1,6 | ||
1Department of Biomarker Imaging Science, Graduate School of Biomedical Science and Engineering, Hokkaido University, Sapporo, Japan, 2Department of Functioning and Disability, Faculty of Health Sciences, Hokkaido University, Sapporo, Japan, 3Siemens Healthcare K.K., Tokyo, Japan, 4Siemens Healthcare GmbH, Erlangen, Germany, 5Department of Rehabilitation, Hokkaido University Hospital, Sapporo, Japan, 6Global Center for Biomedical Science and Engineering, Faculty of Medicine, Hokkaido University, Sapporo, Japan |
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A four-week neurocognitive training of spatial attention and working memory was conducted in 21 volunteers. A change in tissue microstructure was tested by using double diffusion encoding MRI, which revealed a decrease in μFA in the left middle frontal gyrus. This decrease showed a significant negative correlation with the changes in the response time as assessed by the orienting attention network test. |
| 2047 | Microstructural alterations in the white matter of children with dyslexia assessed by multi-fascicle diffusion compartment imaging | |
| Nicolas Delinte1, Claire Gosse2,3, Laurence Dricot3, Quentin Dessain1, Mathieu Simon1, Benoit Macq1, Marie Van Reybroeck2,3, and Gaetan Rensonnet1 | ||
1ICTEAM, UCLouvain, Louvain-la-Neuve, Belgium, 2IPSY, UCLouvain, Louvain-la-Neuve, Belgium, 3IoNS, UCLouvain, Brussels, Belgium |
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Dyslexia is a deviant development of both reading and spelling abilities affecting 5-12 % of children, yet the microstructural changes it induces in the white matter (WM) remain incompletely understood. This study analyzed multi-shell diffusion MRI on a population of 17 dyslexic children and 18 controls. Advanced models (Diamond & Microstructure Fingerprinting), able to separately characterize intersecting fascicles within a voxel, obtained stronger correlations with children's reading and spelling performances than traditional DTI and showed increased sensitivity. The novel indices, obtained from these models, suggested refined interpretations of the microstructural characteristics of dyslexia in WM pathways. |
| 2048 | Robust estimation of the fetal brain architecture from in-utero diffusion-weighted imaging | |
| Davood Karimi1, Onur Afacan1, Clemente Velasco-Annis1, Camilo Jaimes1, Caitlin Rollins1, Simon Warfield1, and Ali Gholipour1 | ||
1Boston Children's Hospital, Harvard Medical School, Boston, MA, United States |
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Diffusion weighted magnetic resonance imaging (DW-MRI) of fetal brain is challenged by fetal and maternal motion, low signal-to-noise ratio and short scan times. Hence, there is a need for methods that can accurately estimate the parameters of interest from small numbers of noisy measurements. We propose a deep learning method for accurate and robust estimation of color fractional anisotropy as a measure of brain architecture from fetal DW-MRI scans. We also propose methods for simulating realistic training data. Evaluations on an independent cohort of fetal DW-MRI scans show that the proposed method is significantly more accurate than standard methods. |
| 2049 | The value of quantitative diffusion tensor MRI in diagnosis of hypoxic ischemic brain injury (HIBD) in premature infant | |
| Xueyuan Wang1, Bohao Zhang2, Xianglong Liu3, Kaiyu Shang4, Jinxia Guo4, Xin Zhao1, and Xiaoan Zhang1 | ||
1Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China, Zhengzhou, China, 2College of Chemistry, Zhengzhou University, Zhengzhou, China, Zhengzhou, China, 3Zhengzhou Central Hospital Affiliated to Zhengzhou University, Zhengzhou, China, Zhengzhou, China, 4GE Healthcare, MR Research China, Beijing, China, Beijing, China |
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Diffusion tensor imaging (DTI) is currently the only non-invasive technology available to evaluate the damage to the cerebral white matter (WM) fibers in neonates, which can reflect the occurrence of damage through the decrease of FA values. This study aims to validate the value of diffusion tensor imaging (DTI) to diagnose and predict hypoxic-ischemic brain injury (HIBD) of preterm infants to assist clinical diagnosis and treatment. |
| 2050
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Characterizing axonal and myelin microstructure development across early childhood using NODDI and qihMT | |
| Jess E Reynolds1,2, Emma Tarasoff3, R Marc Lebel1,4, Bryce L Geeraert1, and Catherine Lebel1 | ||
1Department of Radiology, University of Calgary, Calgary, AB, Canada, 2Telethon Kids Institute, The University of Western Australia, Perth, Australia, 3Department of Neuroscience, University of Calgary, Calgary, AB, Canada, 4GE Healthcare, Calgary, AB, Canada |
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There is a need to better understand white matter development across early childhood, as it is a time of rapid brain development that supports ongoing cognitive and behavioral maturation. Here, we aimed to apply NODDI and qihMT techniques longitudinally to provide a more specific understanding of early brain development. Consistent with diffusion MRI research, these advanced diffusion and non-diffusion methods indicated earlier development of central tracts compared to more peripheral regions. NODDI and qiHMT metrics demonstrate that white matter development during early childhood is dominated by increasing axon density, alongside ongoing myelination and slightly decreasing axon coherence. |
| 2051 | Investigating cortical microstructure in preterm-born adolescents using three-tissue compositional analysis | |
| Thijs Dhollander1, Claire Kelly1,2, Ian Harding3,4, Wasim Khan3, Richard Beare1, Jeanie Cheong2,5,6, Lex Doyle2,5,6,7, Marc Seal1,7, Deanne Thompson1,2,7, and Peter Anderson2,8 | ||
1Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia, 2Victorian Infant Brain Studies (VIBeS), Murdoch Children's Research Institute, Melbourne, Australia, 3Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia, 4Monash Biomedical Imaging, Monash University, Melbourne, Australia, 5Newborn Research, The Royal Women's Hospital, Melbourne, Australia, 6Department of Obstetrics and Gynaecology, The University of Melbourne, Melbourne, Australia, 7Department of Paediatrics, The University of Melbourne, Melbourne, Australia, 8Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Australia |
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While many studies have used diffusion MRI to investigate white matter microstructure, fewer studies have investigated cortical grey matter microstructure. We investigated cortical microstructural tissue and fluid composition using diffusion tissue signal fractions from Single-Shell 3-Tissue Constrained Spherical Deconvolution, in a cohort of preterm-born children at 13 years of age (n=130). Compared with term-born controls (n=45), we identified several cortical regions exhibiting a relative shift from a grey matter-like composition towards a more fluid-like composition, potentially reflecting reduced cell density and increased free-water content. This illustrates the utility of 3-tissue compositional analysis for studying cortical microstructure in neurodevelopment. |
| 2052 | More than just axons: A positive relationship between an intracellular isotropic diffusion signal & pubertal development in white matter regions | |
| Benjamin T Newman1,2, James T Patrie3, and T Jason Druzgal1 | ||
1Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, VA, United States, 2Brain Institute, University of Virginia, Charlottesville, VA, United States, 3Department of Public Health Sciences, University of Virginia, Charlottesville, VA, United States |
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Understanding how the brain develops during adolescence is important for evaluating neuronal developments that affect mental health throughout the lifespan. This study uses 3-tissue constrained spherical deconvolution (3T-CSD) to examine the relationship between brain diffusion microstructure in deep white matter ROIs and pubertal development in a cross-sectional group of 4752 adolescents. An anisotropic diffusion signal fraction was found to have a negative correlation, while an intracellular isotropic diffusion signal fraction had a positive correlation with pubertal development across the majority of axonal ROIs. These results provide evidence for complex microstructural changes in brain development within the white matter skeleton. |
| 2053 | Harmonization of multi-site diffusion MRI data of the Adolescent Brain Cognitive Development (ABCD) Study | |
| Suheyla Cetin-Karayumak1, Fan Zhang1, Tashrif Billah2, Sylvain Bouix1, Steve Pieper3, Lauren J. O'Donnell1, and Yogesh Rathi1 | ||
1Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States, 2Brigham and Women's Hospital, Boston, MA, United States, 3Isomics, Boston, MA, United States |
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This study presents our harmonization efforts on the multi-site diffusion MRI data of the ~12,000 adolescents from the Adolescent Brain Cognitive Development (ABCD) study, collected from 22 sites using Siemens, GE and Philips scanners. On the minimally preprocessed diffusion MRI data provided by the ABCD study - release 3, we first applied brain masking using our deep learning tool which showed 99% Dice overlap performance compared to the manually corrected masks. Next, we harmonized the dMRI data from 22 sites (with 45 scanner settings) using our previously-validated software. The harmonized diffusion MRI data will be shared through the NIMH data archive. |
| 2054 | Characterizing Temporal Pole Microstructure with Diffusion Kurtosis Imaging in Temporal Lobe Epilepsy | |
| Loxlan Wesley Kasa1,2, Terry Peters1,2,3,4, Seyed M Mirsattari3,4,5, Ali R Khan1,2,3, and Roy AM Haast1 | ||
1Imaging Research Laboratories, Robarts Research Institute, London, ON, Canada, 2School of Biomedical Engineering, Western University, London, ON, Canada, 3Department of Medical Biophysics, Western University, London, ON, Canada, 4Department of Medical Imaging, Western University, London, ON, Canada, 5Department of CNS, Western University, London, ON, Canada |
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The role of the temporal pole (TP) in nonlesional temporal lobe epilepsy (‘MRI-’) has been underappreciated. Better understanding of the possible white matter (WM) microstructural changes within the TP in MRI- is important for informing resective surgery. The purpose of this study was to evaluate the use of diffusion kurtosis imaging (DKI), to detect abnormalities at specific regions along WM fibre bundles proximal to the TP in MRI- and lesional TLE (‘MRI+’). DKI was able to detect possible microstructural changes near TP in both MRI+ and MRI- subjects not clearly visible using diffusion tensor imaging metrics. |
| 2055 | Assessment of Perivascular Glymphatic System Activity in Middle-aged HIV Infected Patients on Combination Antiretroviral Therapies | |
| Benedictor Alexander Nguchu1, Jing Zhao 2,3, Yanming Wang1, Jean de Dieu Uwisengeyimana1, Xiaoxiao Wang1, Bensheng Qiu1, and Hongjun Li2,3 | ||
1Hefei National Lab for Physical Sciences at the Microscale and the Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, China, 2Department of Radiology, Beijing Youan Hospital, Capital Medical University, Beijing, China, 3School of Biological Science and Medical Engineering, Beihang University, Beijing, China |
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The brain activity underlying cognitive processing can be affected by HIV. We examine the ALPS index, a measure reflecting glymphatic system activity, along the perivascular space and its relationship with cognitive performance in middle-aged HIV infected patients successfully adhering to antiretroviral therapy. We found that the ALPS index was increased significantly in middle-aged HIV-infected patients receiving cART and was correlated with attention and working memory. The duration on cART was also associated with some cognitive measures. These findings suggest that ALPS index might provide an impetus for understanding cognitively relevant diffusivity changes following HIV or long-term use of cART. |
| 2056 | Altered Functional Connection and Neuroinflammation in Fibromyalgia Using Independent Component Analysis and Diffusion Kurtosis MRI | |
| JIA-WEI Liang1, Tang-Jun Li2, Yao-Wen Liang3, Ting-Chun Lin3, Yi-Chen Lin3, Jiunn-Horng Kang2,4, You-Yin Chen3,5, and Yu-Chun Lo5 | ||
1Department of Biomedical Optoelectronic, Taipei Medical University, Taipei, Taiwan, 2College of Medicine, Taipei Medical University, Taipei, Taiwan, 3Department of Biomedical Engineering, National Yang Ming University, Taipei, Taiwan, 4Department of Physical Medicine & Rehabilitation, Taipei Medical University, Taipei, Taiwan, 5Ph.D. Program for Neural Regenerative Medicine, Taipei Medical University, Taipei, Taiwan |
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Recently, neuroinflammation was proposed as an important role in fibromyalgia. However, the correlation between neuroinflammation and functional connection in fibromyalgia patients remained unclear. Fibromyalgia patients and healthy control participants were recruited to investigate the mechanism of fibromyalgia. Independent component analysis, diffusion kurtosis MRI and cortical thickness estimation were applied in this study. The finding implied that neuroinflammation and structural change of brain were associated with the abnormal functional connection in fibromyalgia. |
| 2057 | Clinical correlations of DTI and volumetric metrics in people with multiple sclerosis | |
| Abdulaziz Alshehri1,2, Oun Al-iedani1,2, Jameen Arm1,2, Neda Gholizadeh1, Thibo Billiet3, Rodney Lea2, Jeannette Lechner-Scott1,2,4, and Saadallah Ramadan1,2 | ||
1University of Newcastle, Newcastle, Australia, 2Hunter Medical Research Institute, Newcastle, Australia, 3Icometrix, Leuven, Australia, 4John Hunter Hospital, Newcastle, Australia |
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This study is to evaluate DTI parameters in RRMS patients with age and sex-matched HCs, and to correlate these DTI metrics values in total-brain white matter (TBWM) and white matter lesion (WML) in comparison to white matter-related volumetric measures with clinical symptoms showing the differentiation and significant P-values. DTI parameters showed a stronger correlation with clinical parameters than white matter-related volumetric measurements in RRMS. Importantly, more DTI parameters (16 metrics) with stronger clinical correlations were obtained than volume measurements (5 metrics). |
| 2058 | Microstructural Gray Matter Abnormalities in Progressive Supranuclear Palsy and Corticobasal Syndrome: Evaluation by Free-water Imaging | |
| Koji Kamagata1, Christina Andica1, Kaito Takabayashi1, Yuya Saito1, Wataru Uchida1,2, Shohei Fujita1, Toshiaki Akashi1, Akihiko Wada1, Kouhei Kamiya3, Masaaki Hori3, and Shigeki Aoki1 | ||
1Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan, 2Department of Radiological Sciences, Tokyo Metropolitan University, Tokyo, Japan, 3Department of Radiology, Toho University Omori Medical Center, Tokyo, Japan |
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Corticobasal syndrome (CBS) and progressive supranuclear palsy (PSP) are neurodegenerative disorders characterized by the deposition of the abnormal 4 microtubule-binding domain (4R) tau protein in specific brain regions. Voxel-based morphometry (VBM) has been widely used in CBS and PSD; however, the detection of pathological changes of these diseases is challenging in the early stages, including with VBM. In this study, we used free-water imaging (FWI) to evaluate gray matter (GM) microstructural changes in CBS and PSP. We determined that FWI could detect GM abnormalities, which likely reflected tau-related pathology in CBS and PSP patients more sensitively than VBM. |
| 2059 | Can Diffusion Kurtosis Imaging and 3D-Arterial Spin Labeling perfusion imaging improve the diagnostic accuracy of Binswanger's Disease? | |
| Xiaoyi He1,2, Weiqiang Dou3, Hansen Schie1, and Junying Wang1,2 | ||
1Department of Medical Imaging, Shandong Provincial Qianfishan Hospital, The First Hospital Affiliated with Shandong First Medical University, Jinan, China, 2Shandong First Medical University, Taian, China, 3GE Healthcare, MR Research China, Beijing, China |
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This study aimed to investigate whether the combined 3D-arterial spin labeling (3D-ASL) and diffusion kurtosis imaging (DKI) can distinguish Binswanger’s disease (BD) patients from healthy subjects. 35 BD patients and 33 age/gender-matched controls were scanned in DKI and ASL at 3T. Compared with healthy subjects, significant alterations were found in almost all DKI & ASL relevant parameters on the major lesions and partial non-lesion regions of BD. With these findings, we thus proved that the combined DKI and 3D-ASL can be effectively tools exploring pathophysiological mechanisms and performing robust diagnostic accuracy for BD patients. |
| 2060 | Evaluation of Multi-shot DTI Metrics at Non-Compressed Levels for the Diagnosis and Prognosis of Degenerative Cervical Myelopathy (DCM) | |
| Sisi Li1, Ke Wang2, Xiao Han3, Jinchao Wang3, Wen Jiang3, Xiaodong Ma4, Bing Wu5, Yandong Liu3, Wei Liang3, and Hua Guo1 | ||
1Center for Biomedical Imaging Research, Beijing, China, 2Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, United States, 3Beijing Jishuitan Hospital, Beijing, China, 4University of Minnesota, Minnesota, Minnesota, MN, United States, 5GE Healthcare, MR Research China, Beijing, China |
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Degenerative cervical myelopathy (DCM) is a chronic disease of spinal cord. The sensitivity of conventional structural T1W and T2W MRI to the diagnosis of DCM is low. Diffusion tensor imaging (DTI) can provide quantitative assessments for pre- and post-surgery spinal cord functions. However, the prognostic value of DTI metrics at the level-of-most-compression (LMC) remains controversial. Additionally, it is difficult to differentiate the clinical utility of various tracts at LMC due to severe compressions and limited resolution. This retrospective cohort follow-up study aimed to investigate the correlation of DTI metrics with clinical assessment in different tracts at non-compressed C2 level. |
| 2061 | Differentiation of spinal epidural hematoma and infection in vertebral decompression patients using Diffusion-Relaxation Matrix (DRM) | |
| Daichi Murayama1, Takayuki sakai1, Masami Yoneyama2, and Shigehiro Ochi3 | ||
1Radiology, Eastern Chiba Medical Center, Chiba, Japan, 2Philips Japan, Tokyo, Japan, 3Eastern Chiba Medical Center, Chiba, Japan |
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Postoperative complications such as vertebral decompression can lead to hematoma formation and infection. The differentiation of hematoma from infection as a postoperative follow-up is important in assessing future treatment options and the need for surgery. The aim of this study was to differentiate between spinal epidural hematoma, spinal epidural abscess and pyogenic spondylitis based on the ADC and T2 values obtained using DRM. The T2 and diffusion weighted T2 (ΔT2) values were significantly higher in abscesses than in hematomas, and even higher in pyogenic spondylitis.DRM allows to differentiate hematoma from infection. |
| 2062 | Decreased sciatic nerve fractional anisotropy in diabetes and prediabetes associated with lower and upper limb function impairment | |
| Johann ME Jende1, Zoltan Kender1, Christoph Mooshage1, Sabine Heiland1, Peter Nawroth1, Martin Bendszus1, Stefan Kopf1, and Felix T Kurz1 | ||
1Heidelberg University Hospital, Heidelberg, Germany |
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Nerve damage in distal polyneuropathy first becomes clinically apparent in in the legs and later in hands and arms. Previous studies could show, however, that peripheral nerve lesions in the leg predominate in the thigh and that upper limb nerve function can be impaired in early stages of the disease. We show that a decrease in sciatic nerve fractional anisotropy is associated with impaired nerve function in both upper and lower limbs for patients with diabetes and patients with prediabetes. Our findings therefore suggest that structural nerve damage in diabetic polyneuropathy already occurs at early, subclinical stages of the disease. |
| 2437 | Quantification of multiple diffusion metrics from asymmetric balanced SSFP frequency profiles using neural networks | |
| Florian Birk1, Felix Glang1, Christoph Birkl2, Klaus Scheffler1,3, and Rahel Heule1,3 | ||
1High Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, 2Department of Neuroradiology, Medical University of Innsbruck, Innsbruck, Austria, 3Department of Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany |
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Asymmetries in the balanced SSFP frequency profile are known to reflect information about intravoxel tissue microenvironment with strong sensitivity to white matter fiber tract orientation. Phase-cycled bSSFP has demonstrated potential for multi-parametric quantification of relaxation times, static and transmit field inhomogeneity, or conductivity, but has not yet been investigated for diffusion quantification. Therefore, a neural network approach is suggested, which learns a model for voxelwise quantification of diffusion metrics from bSSFP profiles. Not only the feasibility for robust predictions of mean diffusivity (MD) and fractional anisotropy (FA) is shown, but also potential to estimate the principal diffusion eigenvector. |
| 2438 | Rotation-Equivariant Deep Learning for Diffusion MRI | |
| Philip Müller1, Vladimir Golkov1, Valentina Tomassini2, and Daniel Cremers1 | ||
1Computer Vision Group, Technical University of Munich, Munich, Germany, 2D’Annunzio University, Chieti–Pescara, Italy |
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Convolutional networks are successful, but have recently been outperformed by new neural networks that are equivariant under rotations and translations. These new networks do not struggle with learning each possible orientation of each image feature separately. So far, they have been proposed for 2D and 3D data. Here we generalize them to 6D diffusion MRI data, ensuring joint equivariance under 3D roto-translations in image space and the matching rotations in q-space, as dictated by the image formation. We validate our method on multiple-sclerosis lesion segmentation. Our proposed neural networks yield better results and require less training data. |
| 2439 | Improved image quality with Deep learning based denoising of diffusion MRI data | |
| Radhika Madhavan1, Jaemin Shin2, Nastaren Abad1, Luca Marinelli1, J Kevin DeMarco3, Robert Y Shih3, Vincent B Ho3, Suchandrima Banerjee4, and Thomas K Foo1 | ||
1GE Global Research, Niskayuna, NY, United States, 2GE Healthcare, New York, NY, United States, 3Walter Reed National Military Medical Center and Uniformed Services University of the Health Sciences, Bethesda, MD, United States, 4GE Healthcare, Menlo Park, CA, United States |
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Structure-preserved denoising of MRI images is a critical step in medical image analysis. This is particularly critical in diffusion MRI where higher spatial and angular resolutions required to map tissue microstructure in low SNR (especially at higher b-values) situations, if longer acquisition times are not used. Denoising using deep convolutional neural networks (DCNN) can reduce noise without requiring extensive averaging, enabling shorter scan times and high image quality, especially in the resulting tensor-derived maps. Preliminary results using DCNN based denoising on multi-shell diffusion data demonstrates improved image quality and reduced noise, without compromising on structural integrity and tensor derived metrics. |
| 2440 | Deep learning based denoising for high b-value high resolution diffusion imaging | |
| Seema S Bhat1, Pavan Poojar2, Hanumantharaju M C3, and Sairam Geethanath1,2 | ||
1Medical Imaging Research center, Dayananda sagar college of engineering, Bangalore, India, 2Columbia University in the City of New York, Newyork, NY, United States, 3Department of Electronic and Communications, BMS Institute of Technology and Management, Bangalore, India |
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Deep learning based denoising can improve signal-to-noise ratio in high b-value diffusion imaging. Denoising CNN (DnCNN) model is trained with clean and simulated noisy patches of b=2000 s/mm2 DWI images from Openneuro database. We applied DnCNN to simulated noisy DWI and prospective DWI at b=2000 s/mm2.Unsharp masking used during testing to emphasize medium contrast details. Peak signal-to-noise ratio(>32dB) for simulated noisy DWI and image entropy(>7.17) for prospective DWI obtained after denoising. This denoising can be leveraged to shorten acquisition time by reducing the number of signal averages or increase resolution in through plane by acquiring with smaller slice thickness. |
| 2441 | Microstructural White Matter Segmentation in Mild Traumatic Brain Injury Patients using DTI and a Deep 2D-UNet Ensemble | |
| Brian McCrindle1,2, Nicholas Simard1,2, Ethan Samson2,3, Ethan Danielli 2,3, Thomas E. Doyle1,3,4, and Michael D. Noseworthy1,2,3 | ||
1Electrical and Computer Engineering, McMaster University, Hamilton, ON, Canada, 2Imaging Research Center, St. Joseph's Healthcare, Hamilton, ON, Canada, 3School of Biomedical Engineering, McMaster University, Hamilton, ON, Canada, 4Vector Institute, Toronto, ON, Canada |
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Patients who experience a mild traumatic brain injury often suffer from microstructural white matter damage that even radiologists are unable to detect. By employing diffusion tensor imaging and a deep 2D-UNet ensemble network, we developed an image processing pipeline capable of detecting and segmenting damaged white matter regions. We show that ensemble networks are more reliable compared to any single model over the prediction threshold range under test-time-augmentation. |
| 2442 | Deep learning-based DWI Denoising method that suppressed the "instability" problem | |
| Hayato Nozaki1,2, Yasuhiko Tachibana3, Yujiro Otsuka4, Wataru Uchida1,2, Yuya Saito1, Koji Kamagata1, and Shigeki Aoki1 | ||
1Department of Radiology, Graduate School of Medicine, Juntendo University, Tokyo, Japan, 2Graduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo, Japan, 3Department of Molecular Imaging and Theranostics National Institute of Radiological Sciences National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan, 4Miliman, Tokyo, Japan |
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Deep learning-based noise reduction technique for DWI contains a risk of outputting values that are greatly deviating from what it should be because of the instability problem of deep learning. The neural network model was designed in this study to suppress this risk which can fix the generated value for each pixel within the range of values of neighboring pixels in the original image. The results of the volunteer study suggested that the proposed method has potential to provide effective denoising beside suppressing the instability risk. |
| 2443 | Accelerating Brain Diffusion Tensor Imaging using Neural Networks: A Comparison of three Neural Networks | |
| Yuhao Yan1,2 and Zheng Chang1,2 | ||
1Medical Physics Graduate Program, Duke University, Durham, NC, United States, 2Department of Radiation Oncology, Duke University, Durham, NC, United States |
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This work focused on accelerating DTI using deep learning methods. Three neural networks including U-net, PD-net and Cascade-net were investigated on reconstructing DTI images, ADC maps and FA maps from Cartesian under-sampled k-space data. The results indicated that Cascade-net out-performed the other two networks, obtaining comparable image quality as compared with the reference reconstructed from full k-space data. In summary, neural networks can be used to accelerate DTI while maintaining image quality. |
| 2444 | Accelerating Diffusion Tensor Imaging of the Rat Brain using Deep Learning | |
| Ali Bilgin1,2,3,4, Loi Do1, Phillip A Martin2, Ethan Lockhart4, Adam S Bernstein1, Chidi Ugonna1, Laurel Dieckhaus1, Courtney Comrie1, Elizabeth B Hutchinson1, Nan-Kuei Chen1, Gene E Alexander5,6, Carol A Barnes5,7,8, and Theodore P Trouard1,3,5 | ||
1Biomedical Engineering, University of Arizona, Tucson, AZ, United States, 2Electrical and Computer Engineering, University of Arizona, Tucson, AZ, United States, 3Medical Imaging, University of Arizona, Tucson, AZ, United States, 4Program in Applied Mathematics, University of Arizona, Tucson, AZ, United States, 5Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United States, 6Departments of Psychology and Psychiatry, University of Arizona, Tucson, AZ, United States, 7Division of Neural System, Memory & Aging, University of Arizona, Tucson, AZ, United States, 8Departments of Psychology, Neurology and Neuroscience, University of Arizona, Tucson, AZ, United States |
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The aim of this work is to accelerate analysis of diffusion weighted MRI (dMRI) of the rat brain using deep learning. The proposed approach allows prediction of unacquired diffusion-weighted images (DWIs) from a small set of acquired DWIs. By combining the acquired and predicted DWIs, accurate and reliable diffusion tensor metrics can be obtained with up to ten-fold reduction in scan time. |
| 2445 | Automatic Detection of Nyquist Ghosts in Whole-Body Diffusion Weighted MRI Using Deep Learning | |
| Alistair Lamb1, Anna Barnes2, Stuart A Taylor2, and Hui Zhang3 | ||
1Department of Medical Phyics and Biomedical Engineering, University College London, London, United Kingdom, 2Centre for Medical Imaging, University College London, London, United Kingdom, 3Centre for Medical Image Computing, University College London, London, United Kingdom |
||
Despite its potential as an imaging biomarker in assessing tumor response to therapy, use of apparent diffusion coefficient (ADC) as a quantitative endpoint is not routine in clinical practice. One factor that limits the usefulness of ADC is the presence of artifacts in the constituent diffusion-weighted imaging (DWI) data. In this study, we propose a supervised deep-learning approach to detect the presence of Nyquist ghosts in axial DWI slices of the abdomen, achieving a test accuracy of 81.5%. The detection and removal of these artifacts could help improve the reproducibility of quantitative ADC measurements. |
| 2446 | SRDTI: Deep learning-based super-resolution for diffusion tensor MRI | |
| Qiyuan Tian1,2, Ziyu Li3, Qiuyun Fan1,2, Chanon Ngamsombat1, Yuxin Hu4, Congyu Liao1,2, Fuyixue Wang1,2, Kawin Setsompop1,2, Jonathan R Polimeni1,2, Berkin Bilgic1,2, and Susie Y Huang1,2 | ||
1Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States, 2Harvard Medical School, Boston, MA, United States, 3Department of Biomedical Engineering, Tsinghua University, Beijing, China, 4Department of Electrical Engineering, Stanford University, Stanford, CA, United States |
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High-resolution diffusion tensor imaging (DTI) is beneficial for probing tissue microstructure in fine neuroanatomical structures, but long scan times and limited signal-to-noise ratio pose significant barriers to acquiring DTI at sub-millimeter resolution. To address this challenge, we propose a deep learning-based super-resolution method entitled “SRDTI” to synthesize high-resolution diffusion-weighted images (DWIs) from low-resolution DWIs. SRDTI employs a deep convolutional neural network (CNN), residual learning and multi-contrast imaging, and generates high-quality results with rich textural details and microstructural information, which are more similar to high-resolution ground truth than those from trilinear and cubic spline interpolation. |
| 2447 | Inferring Diffusion Tensors on Unregistered Cardiac DWI Using a Residual CNN and Implicitly Modelled Data Prior | |
| Jonathan Weine1, Robbert J. H. van Gorkum1, Christian T. Stoeck1, Valery Vishnevskiy1, Thomas Joyce1, and Sebastian Kozerke1 | ||
1Institute for Biomedical Engineering, University and ETH Zurich, Zürich, Switzerland |
||
Cardiac DTI provides invaluable information about the state of myocardial microstructure. Motion and systematic signal variations of the imaging process influence the tensor inference. Image registration prior to tensor fitting with an LSQ estimator is the common data processing approach. The feasibility of training a neural network with simulated data modelling tensors and slice misalignment due to free breathing for inference of diffusion tensors from free-breathing in vivo data is investigated. Evaluation on simulated test data demonstrates feasibility of the training process. Application to in vivo data shows promising results of the CNN especially at myocardial borders. |
| 2448 | Learning the relationship between human brain tissue microstructure and diffusion MRI data | |
| Emmanuelle Weber1, Christoph Leuze1, Daniel A. N. Barbosa1, Gustavo Chau Loo Kung1, Kalanit Grill-Spector1, and Jennifer A. McNab1 | ||
1Stanford, Stanford, CA, United States |
||
We demonstrate the feasibility of machine learning direct prediction of tissue microstructure from raw diffusion MRI data. We test the approach by attempting to predict the main fiber orientation as this metric is well-understood and easily extracted using a diffusion tensor model. We present results on both simulated data and a matched dMRI-3D histology dataset. |
| 2449 | Patch-CNN-DTI: Data-efficient high-fidelity tensor recovery from 6 direction diffusion weighted imaging. | |
| Tobias Goodwin-Allcock1, Ting Gong1, Robert Gray2, Parashkev Nachev2, and Hui Zhang1 | ||
1Centre for Medical Image Computing (CMIC), UCL, London, United Kingdom, 2High-Dimensional Neurology, University College London Queen Square Institute of Neurology, London, United Kingdom |
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We present Patch-CNN-DTI, a deep-learning method to estimate diffusion tensors (DT) accurately from only 6 diffusion-weighted images. Early voxel-wise deep-learning methods can only estimate scalar measures of DT. Later work shows DT can be estimated using image-wise methods based on convolutional neural networks (CNN), but they require large training cohort. Patch-CNN-DTI can estimate DT with only one training subject, by pooling information from local neighbourhood of a voxel similar to the CNN but at a much smaller scale to minimise training data requirements. Results show it outperforms conventional model fitting with twice the number of diffusion directions. |
| 2450 | Rapid Multi-slice STEAM Diffusion Imaging with a Prepared Gradient Echo Echoplanar Sequence | |
| David C Alsop1,2, Manuel Taso1,2, and Arnaud Guidon3 | ||
1Radiology, Beth Israel Deaconess Medical Center, Boston, MA, United States, 2Radiology, Harvard Medical School, Boston, MA, United States, 3Global MR applications and workflow, GE Healthcare, Boston, MA, United States |
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STEAM diffusion offers longer diffusion times, reduced gradient demands and other advantages for diffusion imaging but has suffered from long acquisition times. We propose a non-selective preparation of a conventional gradient echo echoplanar sequence that enables the rapid acquisition of many slices. Initial application to the brain readily enabled up to 32 slice acquisition within a single TR. |
| 2451 | Multi-band in Diffusion MRI: Can we go too fast? | |
| Arun Venkataraman1, Benjamin Risk2, Deqian Qiu3,4, Jianhui Zhong1,5, and Zhengwu Zhang6 | ||
1Physics and Astronomy, University of Rochester, Rochester, NY, United States, 2Biostatistics and Bioinformatics, Emory University, Atlanta, GA, United States, 3Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, United States, 4Biomedical Engineering, Emory University, Atlanta, GA, United States, 5Imaging Sciences, University of Rochester Medical Center, Rochester, NY, United States, 6Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY, United States |
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In this study, we sought to better understand the effect of multiband and phase acceleration on diffusion image reconstruction. As part of an on-going study on SMS in dMRI, 10 test-retest scans from 5 young, healthy subjects were scanned. We found that g-factor, reflecting noise amplification, increased with higher acceleration factors, the g-factor was also higher in frontal regions compared to occipital regions. We also found that the DTI fitting performed worse where we saw increased g-factor. Finally, we found that streamlines were stable as a function of acceleration in the occipital areas, but not frontal areas. |
| 2452 | A unified framework for estimating diffusion kurtosis tensors with multiple prior information | |
| Li Guo1,2,3, Lyu Jian2,3, Yingjie Mei4, Mingyong Gao1, Yanqiu Feng2,3, and Xinyuan Zhang2,3,5 | ||
1Department of MRI, The First People’s Hospital of Foshan (Affiliated Foshan Hospital of Sun Yat-sen University), Foshan, China, 2School of Biomedical Engineering, Southern Medical University, Guangzhou, China, 3Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China, 4Philips Healthcare, Guangzhou, China, 5Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Guangzhou, China |
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Accurate tensor estimation for DKI is usually challenged by noise. The noncentral Chi distribution noise would introduce bias in the estimated DKI tensors. Although several noise-corrected models are statistically unbiased, the DKI tensors generated by these estimators have large variances. In addition, severe noise easily causes the estimated kurtosis values outside a physically acceptable range. The goal of this work is to propose a unified framework that integrates multiple prior information including nonlocal structural self-similarity (NSS), local spatial smoothness (LSS), physical relevance (PR) of DKI model, and noise characteristic of magnitude diffusion images for improved DKI tensor estimation. |
| 2453 | Influence of electrocardiogram signal triggering on filter exchange imaging | |
| Julian Rauch1,2, Dominik Ludwig1,2, Frederik B. Laun3, and Tristan A. Kuder1 | ||
1Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany, 2Faculty of Physics and Astronomy, Heidelberg University, Heidelberg, Germany, 3Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany |
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Apparent exchange rate (AXR) mapping can be used to non-invasively investigate water exchange between the intra- and extracellular compartment, which might yield insight into cell membrane permeability. To obtain the AXR properly with the filter exchange imaging (FEXI) approach, signal stability is crucial. We show that electrocardiogram (ECG) triggering can lead to a slight improvement of the signal stability for AXR measurements in the human brain. However, pulsation-induced fluctuations are not the main source of signal variations. Thus, it remains questionable if investing additional measurement time in triggering is justified. |
| 2454 | Improved parameter estimation for non-Gaussian IVIM using an unbiased vector non-local means | |
| Lyu Jian1,2, Xinyuan Zhang1,2,3, Yingjie Mei4, and Li Guo1,2,5 | ||
1School of Biomedical Engineering, Southern Medical University, Guangzhou, China, 2Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China, 3Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Guangzhou, China, 4Philips Healthcare, Guangzhou, China, 5Department of MRI, The First People’s Hospital of Foshan (Affiliated Foshan Hospital of Sun Yat-sen University), Foshan, China |
||
Non-Gaussian intravoxel incoherent motion (NG-IVIM) has been proposed to simultaneously quantify the perfusion and non-Gaussian diffusion properties in tissues. However, accurate parameter estimation for NG-IVIM is usually challenged by noise. The noncentral χ-distribution noise would introduce bias in the estimated NG-IVIM parameters. In addition, severe noise easily causes the estimated parameter values have large variance. To improve the accuracy and precision of parameter estimation for NG-IVIM, we propose to use an unbiased vector non-local means (UVNLM) filter to denoise and correct the noise bias before NG-IVIM model fitting. |
| 2455 | Evaluation of quantitative MRI parameters reproducibility across a major scanner upgrade: spinal cord diffusion weighted (DW) imaging | |
| Ratthaporn Boonsuth1, Marco Battiston1, Francesco Grussu1,2, Marios Yiannakas1, Torben Schneider3, Rebecca Samson1, Ferran Prados1,4,5, and Claudia A. M. Gandini Wheeler-Kingshott1,6,7 | ||
1NMR research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, London, United Kingdom, 2Radiomics Group, Vall d’Hebron Institute of Oncology, Vall d’Hebron Barcelona Hospital Campus, Barcelona, Spain, 3Philips Healthcare, Guildford, Surrey, United Kingdom, 4Centre for Medical Image Computing, Medical Physics and Biomedical Engineering, University College London, London, United Kingdom, 5E-Heath Centre, Universitat Oberta de Catalunya, Barcelona, Spain, 6Department of Brain & Behavioural Sciences, University of Pavia, Pavia, Italy, 7Department of Brain Connectivity Centre Research Department, IRCCS Mondino Foundation, Pavia, Italy |
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Major MRI scanner upgrades can potentially introduce systematic changes in quantitative MRI metrics and affect reliability and reproducibility of quantitative parameters. Advanced diffusion weighted (DW) imaging methods are a powerful diagnostic and research tool in the brain and in spinal cord, but it is unclear to what extent DW-derived metrics can be affected by upgrades. Here we assess the effect of scanner upgrades on state-of-the-art spinal cord DW techniques. We found that diffusion matrices such as FA, MD and MK remain stable following a major upgrade when measured in the whole spinal cord, white matter, and grey matter areas. |
| 2456 | High-resolution microstructural imaging in the human hippocampus with b-tensor encoding and zoomed imaging | |
| Jiyoon Yoo1, Leevi Kerkelä1, Patrick W. Hales1, Kiran K. Seunarine1, Iulius Dragonu2, Enrico Kaden1, and Christopher A. Clark1 | ||
1UCL Great Ormond Street Institute of Child Health, London, United Kingdom, 2Siemens Healthcare Ltd, Frimley, United Kingdom |
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In this work, our protocol leverages the most recent advances in the b-tensor diffusion encoding, and also uses a zoomed imaging technique, to specifically scan the hippocampus. Our sequence is able to acquire high-resolution images which enable direct delineation of hippocampal structures and allows estimation of advanced diffusion metrics, as well as parameters that can be measured from a standard multi-shell diffusion data set. Therefore, our acquisition can be used as an all-in-one sequence for microstructural imaging of the hippocampus. We also defined a subsampled acquisition protocol that is feasible for a clinical setting. |
| 2457 | Benefits of arbitrary gradient waveform design for diffusion encoding | |
| Kevin Moulin1,2,3, Mike Loecher1,2, Matthew J Middione1,2, and Daniel B Ennis1,2,3 | ||
1Department of Radiology, Stanford University, Stanford, CA, United States, 2Department of Radiology, Veterans Administration Health Care System, Palo Alto, CA, United States, 3Cardiovascular Institute, Stanford University, Stanford, CA, United States |
||
Traditional diffusion encoding waveforms are usually composed of two symmetric trapezoidal gradients (TRAP). Shape-free arbitrary (ARB) gradient waveforms offer a higher b-value than ARBs. They can be designed analytically and symmetric or numerically and asymmetric. The objectives of this work were to analyze the performances of ARB and TRAP for asymmetric numerically designs and for symmetric analytically designed diffusion encoding gradient waveforms. |
| 2458 | Gradient waveforms for comprehensive sampling of the frequency and "shape" dimensions in b(ω)-encoded diffusion MRI | |
| Hong Jiang1 and Daniel Topgaard1 | ||
1Physical Chemistry, Lund University, Lund, Sweden |
||
Diffusion encoding with either oscillating gradients or as a function of the "shape" of the b-tensor have both recently found powerful applications for characterization of tissue microstructure in clinical MRI. We here propose a simple scheme based on the "double rotation" technique in solid-state NMR spectroscopy to generate a family of gradient waveforms enabling comprehensive sampling of the multidimensional space defined by the tensor-valued encoding spectrum with special emphasis on the frequency and shape dimensions. The approach is demonstrated by microimaging experiments on phantoms with well-defined anisotropy and restriction properties, thereby paving the way for future clinical implementations. |
| 2459 | Tissue microstructure by ellipsoidal tensor encoding with independently varying spectral anisotropy and tuning | |
| Samo Lasic1,2 and Henrik Lundell1 | ||
1Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Copenhagen, Denmark, 2Random Walk Imaging, Lund, Sweden |
||
Ellipsoidal tensor encoding (ETE) with independent control of spectral anisotropy (SA) and tuning provides two distinct encoding frequency windows in a single experiment and yields distinctly different signal signatures for compartments with different anisotropic time-dependent diffusion. ETE can be orientation invariant, depending on SA and restriction geometry. Signal orientation variation minima depends on size relative to tuning but not on orientation dispersion. This popery could be useful for quick size estimation and geometry detection. Such encoding strategy could potentially provide new contrasts sensitive to specific pathological variations. |
| 2460 | A Novel Fast Quantitative Parameter Distribution Estimator Applied to Diffusion Tensor Distribution Imaging | |
| Anders Garpebring1 | ||
1Radiation Sciences, div. Radiation Physics, Umeå University, Umeå, Sweden |
||
Non-parametric diffusion tensor distribution estimation is very computationally expensive and can require several hours of processing for a single 3D volume. In this work a new formulation of the estimation problem is developed as well as a new more efficient algorithm. The results show that the computational times can be reduced to minutes or even seconds rather than hours. Thus, making these types of analysis suitable also in a clinical setting. |
| 2461 | Quantifying the Repeatability of Microstructural Measures Derived from Free Gradient Waveforms | |
| Kristin Koller1, Chantal MW Tax1,2, Dmitri Sastin1,3,4, and Derek K Jones1,5 | ||
1Cardiff University Brain Research Imaging Centre, Cardiff, United Kingdom, 2Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands, 3Department of Neurosurgery, University Hospital of Wales, Cardiff, United Kingdom, 4BRAIN Biomedical Research Unit, Health & Care Research Wales, Cardiff, United Kingdom, 5Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, Australia |
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Diffusional variance decomposition (DIVIDE) is a promising state-of-the-art approach to measure microscopic microstructure using ‘free’ gradient waveforms (including spherical and linear tensor encoding). Here, in a cohort of 6 participants scanned 5 times each with the DIVIDE protocol, we quantify the microscopic FA (μFA) and isotropic and anisotropic diffusional variance (MKi and MKa) across scans, thus demonstrating high test-retest repeatability. |
| 2462 | Adequate mixing time for double diffusion encoding in normal brain structures and brain tumors | |
| Kentaro Akazawa1, Koji Sakai1, Tomoaki Kitaguchi1, Tomonori Toyotsuji1, Thorsten Feiweier 2, Hiroshi Imai3, and Kei Yamada1 | ||
1Radiology, Kyoto Prefectural University of Medicine, Kyoto, Japan, 2Siemens Healthcare GmbH, Erlangen, Germany, 3Siemens Healthcare K.K., Shinagawa, Japan |
||
The mixing time for double diffusion encoding (DDE) should be set low to reduce the relaxation effects but also high enough for estimating microscopic fractional anisotropy. We tested the adequacy of the mixing time of 30 msec by comparing acquisitions with parallel and anti-parallel directions as well as with orthogonal and collinear directions. Relatively short mixing time for our cohort was adequate to evaluate the microscopic fractional anisotropy not only in the normal brain area of the white matter and the central gray matter, but also in pathologically abnormal areas such as brain tumors. |
| 2463 | Intra-compartmental kurtosis biases tensor-valued multidimensional diffusion | |
| Rafael Neto Henriques1, Sune Nørhøj Jespersen2,3, and Noam Shemesh1 | ||
1Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal, 2Center of Functionally Integrative Neuroscience (CFIN) and MINDLab, Clinical Institute, Aarhus University, Aarhus, Denmark, 3Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark |
||
Multidimensional diffusion encoding (MDE) has been gaining attention for its potential to describe tissue microstructure with enhanced specificity by resolving kurtosis sources, albeit with significant assumptions (no time dependence, no intra-compartmental kurtosis). Correlation Tensor Imaging (CTI) has been introduced as a novel methodology capable of resolving kurtosis sources without relying on a-priori assumptions. Here, we harnessed CTI to validate the accuracy of tensor-valued MDE metrics and assess the importance of intra-compartmental kurtosis (Kintra) in tissues. Our results reveal that Kintra is non-negligible and skews the estimates of tensor-valued MDE approaches, even in the absence of detectable diffusion time dependence. |
| 2464 | Towards more robust and reproducible Diffusion Kurtosis Imaging | |
| Rafael N Henriques1, Sune N. Jespersen2,3, Derek K. Jones4,5, and Jelle Veraart6 | ||
1Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal, 2Department of Clinical Medicine, Aarhus University, Aarhus, Denmark, 3Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark, 4School of Psychology, Cardiff University, Cardiff, United Kingdom, 5Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, Australia, 6Center for Biomedical Imaging, NYU Grossman School of Medicine, New York, NY, United States |
||
The general utility of Diffusion Kurtosis Imaging (DKI) is challenged by its poor robustness to imaging artifacts and thermal noise that often lead to implausible kurtosis values. A robust scalar kurtosis index can be estimated from powder-averaged diffusion-weighted data. We introduce a novel DKI estimator that uses this scalar kurtosis index as a proxy for the mean kurtosis to regularize the fit. The regularized DKI estimator improves the robustness and reproducibility of the kurtosis metrics and results in parameter maps with enhanced quality and contrast; thereby promoting the wider use of DKI in clinical research and potentially diagnostics. |
| 2465 | The diffusion time dependence of MAP-MRI parameters in the human brain | |
| Alexandru V Avram1,2, Qiyuan Tian3, Qiuyun Fan3, Susie Y Huang3,4, and Peter J Basser1 | ||
1Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, United States, 2Center for Neuroscience and Regenerative Medicine, The Henry Jackson Foundation, Bethesda, MD, United States, 3Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States, 4Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States |
||
We acquire mean apparent propagator (MAP) MRI data in the human brain using different diffusion times. We characterize the diffusion-time dependence of propagator metrics in vivo and compute the statistical distance between co-registered propagators measured with short and long diffusion times. We derive time-scaling parameters that can assess anomalous diffusion in disordered, fractal-like tissue environments. Preliminary results suggest that the diffusion-time dependence of in vivo MRI signals is strongly modulated by restrictions and hindrances that occur over a range of length scales and could provide new contrasts to quantify structural and architectural differences in healthy and diseased tissues. |
| 2466 | Investigating the relationship between diffusion MRI signal cumulants and hepatocyte microstructure at fixed diffusion time | |
| Francesco Grussu1, Kinga Bernatowicz1, Ignasi Barba2, and Raquel Perez-Lopez1,3 | ||
1Radiomics Group, Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain, 2NMR Lab, Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain, 3Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain |
||
To date, limited attention has been paid to diffusion-weighted (DW) MRI signal modelling of the liver, where new imaging methods are needed to tackle diseases such as cancer. We report on Monte Carlo (MC) simulations run in synthetic hepatic cells to inform the developing of new model-based methods for liver application. We specifically investigate the question: “can cell size and diffusivity be estimated from signal cumulants at fixed diffusion time and realistic SNR?”, and find that the task is feasible for clinical diffusion times and b=0 SNR as low as 20, provided that both apparent diffusivity and kurtosis are considered. |
| 2467 | Application of DKI and IVIM in staging of hepatic fibrosis | |
| YANLI JIANG1, Jie Zou1, FengXian Fan1, Yuping Bai1, Jing Zhang1, and Shaoyu Wang2 | ||
1Department of Magnetic Resonance, LanZhou University Second Hospital, LanZhou, China, 2MR Scientific Marketing, Siemens Healthineers, Shanghai, China |
||
Intravoxel Incoherent Motion (IVIM) is a MRI method that enables simultaneous assessment of diffusion and perfusion. Diffusion Kurtosis imaging (DKI) is based on a mathematical approach that uses a polynomial model with a dimensionless factor called the kurtosis (K). This study evaluated the relationship between IVIM-DKI diffusion models and clinical-pathologic to assess their diagnostic accuracy for staging of hepatic fibrosis. We found that a high level of hepatic fibrosis usually have a higher MK values. A significant negative correlation was observed between FibroScan and MD. In conclusion, compared with IVIM, DKI might be more useful in staging of hepatic fibrosis. |
| 2468 | Single-shot measurement of sub-millisecond, time-dependent diffusion using optimized, unequal pulse spacings in a static field gradient | |
| Teddy Xuke Cai1,2, Nathan Hu Williamson1,3, Velencia Witherspoon1, Rea Ravin1,4, and Peter Basser1 | ||
1Section on Quantitative Imaging and Tissue Sciences, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD, United States, 2Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom, 3National Institute of General Medical Sciences, Bethesda, MD, United States, 4Celoptics, Inc., Rockville, MD, United States |
||
Time-dependent diffusion contains rich information about the tissue microstructure. Conventional methods to measure the time-varying diffusivity probe a single timescale per acquisition, limiting time resolution. Furthermore, access to sub-millisecond timescales is limited by the pulsed gradient hardware. An alternative method is presented here. We extend the static field gradient, Carr-Purcell-Meiboom-Gill cycle by incrementing the $$$\pi$$$-pulse spacings to isolate the on-resonance signal. The resulting spin echo train probes a range of short timescales (50 – 500 microseconds) in one shot and enables a 1-minute time-dependent diffusivity measurement. Proof-of-principle simulations and experimental results on pure liquids and yeast are presented. |
| 2469 | Automated Surface-Based Segmentation of Deep Grey Matter Brain Regions Based Solely on Diffusion Tensor Images | |
| Graham Little1 and Christian Beaulieu1 | ||
1Biomedical Engineering, University of Alberta, Edmonton, AB, Canada |
||
A surface-based deep grey matter segmentation algorithm is proposed that works directly on diffusion images and maps of the brain acquired at a 1.5 mm isotropic resolution. The method was applied to twenty participants spanning a large age range (6-90 years) resulting in accurate segmentations of the thalamus, caudate, putamen and globus pallidus. Fractional anisotropy and mean diffusivity showed unique non-linear trajectories across the lifespan. The proposed method avoids the need of problematic coregistration to other scans (anatomical T1) and will accelerate the analysis of microstructural changes of deep grey matter regions with age (or disease) in large populations. |
| 2470 | Investigating time dependent diffusion, microscopic anisotropy and T2 effects in the mouse heart | |
| Henrik Lundell1, Samo Lasič1,2, Filip Szczepankiewicz3,4,5, Beata Wereszczyńska6, Matthew Budde7, Erica Dall'Armellina6, Nadira Yuldasheva6, Jürgen E. Schneider6, and Irvin Teh6 | ||
1Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark, 2Random Walk Imaging, Lund, Sweden, 3Clinical Sciences, Lund University, Lund, Sweden, 4Harvard Medical School, Boston, MA, United States, 5Brigham and Women's Hospital, Boston, MA, United States, 6Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom, 7Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, United States |
||
Non-invasive characterization of cardiac microstructure by diffusion MRI has provided insights into the healthy and diseased heart. Multidimensional diffusion encoding (MDE) aims for measurements with independent contrasts for specific effects. We suggest a battery of MDE measurements that probe diffusivity and microscopic anisotropy at different diffusion and echo times. We show a clear effect of time-dependent diffusion but a smaller effect from transversal relaxation. |
| 2471 | Data-driven separation of MRI signal components for tissue characterization | |
| Sofie Rahbek1, Kristoffer H. Madsen2,3, Henrik Lundell2, Faisal Mahmood4,5, and Lars G. Hanson1,2 | ||
1Department of Health Technology, Technical University of Denmark, Kgs. Lyngby, Denmark, 2Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark, 3Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kgs. Lyngby, Denmark, 4Laboratory of Radiation Physics, Odense University Hospital, Odense, Denmark, 5Department of Clinical Research, University of Southern Denmark, Odense, Denmark |
||
We propose a novel data-driven method for extraction of tissue-related signal components from high-dimensional MRI data. In this method, the standard non-negative matrix factorization (NMF) has been extended with signal monotonicity constraints suitable for several MR signal types, and is termed the monotonous slope NMF (msNMF). Its applications are here demonstrated using both diffusion-weighted and relaxometry data. The msNMF successfully distinguish areas with different cell densities and levels of white matter intra-myelinic edema, respectively, and is potentially useful for diagnosis and therapy evaluation. |
| 2472 | Multi-tissue log-domain intensity and inhomogeneity normalisation for quantitative apparent fibre density | |
| Thijs Dhollander1,2, Rami Tabbara2, Jonas Rosnarho-Tornstrand3,4, J-Donald Tournier3,4, David Raffelt2, and Alan Connelly2 | ||
1Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia, 2Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia, 3Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, 4Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom |
||
Multi-tissue constrained spherical deconvolution of diffusion MRI data yields white matter fibre orientation distributions, from which a quantitative metric of apparent fibre density can be obtained. Unlike most other diffusion MRI models, this fibre density metric is directly proportional to the diffusion-weighted signal magnitude, and thus intensity normalisation and bias field correction are needed to compare it between subjects in a study. Here we propose an intensity and inhomogeneity correction algorithm for multi-tissue constrained spherical deconvolution results, estimating a bias field and global normalisation in the log-domain. It outperforms a previously proposed approach that did not operate in the log-domain. |
| 2473 | dMRIPrep: a robust preprocessing pipeline for diffusion MRI | |
| Michael J Joseph1, Derek Pisner2, Adam Richie-Halford3, Garikoitz Lerma-Usabiaga4, Salim Mansour1, James D Kent5, Anisha Keshavan3, Matthew Cieslak6, Erin W Dickie1, Sebastian Tourbier7, Aristotle N Voineskos1, Theodore D Satterthwaite6, Russell A Poldrack8, Jelle Veraart9, Ariel Rokem10, and Oscar Esteban7 | ||
1The Centre for Addiction and Mental Health, Toronto, ON, Canada, 2Department of Psychology, University of Texas at Austin, Austin, TX, United States, 3eScience Institute, The University of Washington, Seattle, WA, United States, 4Basque Center on Cognition, Brain and Language, Donostia - San Sebastian, Spain, 5Neuroscience Program, University of Iowa, Iowa City, IA, United States, 6Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States, 7Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland, 8Department of Psychology, Stanford University, Stanford, CA, United States, 9NYU Grossman School of Medicine, New York City, NY, United States, 10Department of Psychology, The University of Washington, Seattle, WA, United States |
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We present dMRIPrep, a preprocessing pipeline for diffusion MRI (dMRI) inspired by the approach and wide uptake of fMRIPrep. dMRIPrep reliably and consistently performs on diverse data acquired by different studies. dMRIPrep equips researchers with a reliable and transparent tool developed with the best available engineering practices and neuroimaging standards, maintained as part of NiPreps, a community software framework that ensures long-lasting support and public-interest steering. |
| 2474 | Sensitivity to WM injury in SLE assessed by diffusion MRI: influence of field strength, acquisition approach and post-processing strategy | |
| Evgenios N. Kornaropoulos1,2, Stefan Winzeck2,3, Theodor Rumetshofer1, Anna Wikstrom1, Linda Knutsson4,5, Marta Correia6, Pia Sundgren1,7,8, and Markus Nilsson1 | ||
1Diagnostic Radiology, Lund University, Lund, Sweden, 2Division of Anaesthesia, University of Cambridge, Cambridge, United Kingdom, 3Department of Computing, Imperial College London, London, United Kingdom, 4Department of Medical Radiation Physics, Lund University, Lund, Sweden, 5Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, United States, 6MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom, 7Lund University BioImaging Center, Lund University, Lund, Sweden, 8Department of Medical Imaging and Physiology, Skane University Hospital, Lund, Sweden |
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There are many ways to acquire and process diffusion MRI data. However, it is not known which yields the largest effect sizes in group studies. We evaluated the impact of different acquisitions (3T versus 7T and DTI versus DKI) and post-processing strategies (motion correction, Gibbs-ringing and denoising) on effect size estimates of white matter (WM) injury in patients with Systemic Lupus Erythematosus (SLE). Results showed that fractional anisotropy (FA) from a 3T DTI acquisition yielded the largest effect sizes. |
| 2475 | Reducing Noise in Complex-Valued Multi-Channel Diffusion-Weighted Data via Optimal Shrinkage of Singular Values | |
| Khoi Minh Huynh1,2, Wei-Tang Chang2, and Pew-Thian Yap1,2 | ||
1Biomedical Engineering, UNC Chapel Hill, Chapel Hill, NC, United States, 2Department of Radiology and Biomedical Research Imaging Center (BRIC), UNC Chapel Hill, Chapel Hill, NC, United States |
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We evaluated the effectiveness of optimal-shrinkage singular value decomposition (OS-SVD) in denoising multi-channel complex-valued diffusion MRI data prior to image reconstruction and show that it outperforms other state-of-the-art denoising methods. |
| 2476 | Model Based Denoising of Diffusion MRI Reduces Bias in Tensor Derived Parameters and Connectivity Measures | |
| Nastaren Abad1, Luca Marinelli1, Radhika Madhavan1, and Tom K.F Foo1 | ||
1General Electric Global Research, Niskayuna, NY, United States |
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Higher spatial and angular resolution is essential in diffusion MRI to resolve fiber and structural ambiguities. However, quantitative measures are confounded by low SNR, particularly at high b-values, compensation of which leads to longer acquisition times. In this study, the fundamental question asked is: Can denoising aid the stability of the measurement in the presence of increasing noise? Model based denoising was used to explore accelerated sampling by evaluating bias developed in qualitative and quantitative end points. Experimental results highlight superior performance, compared to ground truth, in noise and bias reduction in metrics along with structure preservation. |
| 2713 | The Open Source Initiative for Perfusion Imaging (OSIPI): ASL Pipeline inventory | |
| Sudipto Dolui1, Hongli Fan2, Paula L. Croal3,4, Charlotte Buchanan4, Lydiane Hirschler5, Udunna Anazodo6, David L. Thomas7, Henk J.M.M. Mutsaerts8, and Jan Petr9 | ||
1Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States, 2The Johns Hopkins School of Medicine, Baltimore, BC, United States, 3Radiological Sciences, Division of Clinical Neuroscience, School of Medicine, University of Nottingham, Nottingham, United Kingdom, 4Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, United Kingdom, 5Leiden University Medical Center, Leiden, Netherlands, 6Western University, London, ON, Canada, 7UCL Queen Square Institute of Neurology, University College London, London, United Kingdom, 8Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, location VU, Amsterdam, Netherlands, 9Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany |
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As a part of the Open Source Initiative for Perfusion Imaging (OSIPI), we have created an inventory of software for automated processing of Arterial Spin Labeling (ASL) perfusion MRI data. We contacted the ASL community through different channels, inviting software developers to list their pipelines by completing a questionnaire covering different aspects and features of a desired pipeline. We received inputs from 18 developers and have summarized the main characteristics of their pipelines based on the information they provided. We expect that this inventory will facilitate ASL-related research, reduce duplicate development, and enable translation of ASL to clinical practice. |
| 2714 | The Open Source Initiative for Perfusion Imaging (OSIPI) ASL MRI Challenge | |
| Udunna Anazodo1,2, Joana Pinto3, Flora A. Kennedy McConnell4,5,6, Maria-Eleni Dounavi7, Cassandra Gould van Praag8, Henk Mutsaerts9, Aaron Oliver Taylor10, André Paschoal11, Jan Petr12, Diego Pineda-Ordóñez13, Joseph G. Woods14, Moss Y. Zhao15, and Paula L. Croal4,5 | ||
1Department of Medical Biophysics, University of Western Ontario, London, ON, Canada, 2Imaging Division, Lawson Health Research Institute, London, ON, Canada, 3Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom, 4Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom, 5Radiological Sciences, Division of Clinical Neuroscience, School of Medicine, University of Nottingham, Nottingham, United Kingdom, 6Nottingham Biomedical Research Centre, Queens Medical Centre, Nottingham, United Kingdom, 7Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom, 8Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom, 9Amsterdam University Medical Center, Amsterdam, Netherlands, 10Gold Standard Phantoms Limited, London, United Kingdom, 11Department of Radiology, LIM44 - HCFMUSP, Sao Paulo, Brazil, 12Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany, 13Department of Radiology, Clinica Del Country, Bogotá, Colombia, 14Department of Radiology, University of California San Diego, San Diego, CA, United States, 15Department of Radiology, Stanford University, Stanford, CA, United States |
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The OSIPI ASL MRI Challenge is a community-led initiative aiming to establish the range of approaches used for ASL image analysis and cerebral blood flow (CBF) quantification. Challenge data will consist of population-based and synthetic pseudo-continuous ASL images, with participants analysing the data and submitting resulting CBF maps and mean tissue CBF, along with documentation. Entries will be scored on accuracy, reproducibility and documentation quality. Through documenting the analysis choices made within the community, we will begin to better understand sources of variability, ultimately identifying an optimum pipeline, and moving towards the much-needed consensus of ASL image processing standards. |
| 2715 | Optimization of post-labeling delays in multi-delay 3D pCASL by modeling arterial transit time distribution | |
| Zhiyuan Zhang1,2, Timothy Macaulay3, and Lirong Yan1 | ||
1USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States, 2Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, United States, 3Division of Biokinesiology and Physical Therapy, Ostrow School of Dentistry, University of Southern California, Los Angeles, CA, United States |
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The design of post-labeling delays (PLDs) directly affects the accuracy of CBF and ATT quantifications using multi-delay ASL. In this study, we optimized PLDs in 3D pCASL based upon different ATT distributions including normal distribution directly derived from in vivo ASL data and uniform distribution. Evenly spaced PLDs were also applied for comparison. Our results showed that optimal PLDs based on ATT normal distribution had the best performance in CBF and ATT quantifications with the smallest errors. |
| 2716 | Investigation of angiographic shine-through in time-encoded pCASL | |
| Lena Vaclavu1, Dilek Betül Arslan2, Lydiane Hirschler1, Carles Falcon3,4, Esin Ozturk-Isik2, Juan Domingo Gispert3,4, Paula Montesinos5, Kim van de Ven6, and Matthias JP van Osch1 | ||
1Department of Radiology, C.J. Gorter Center for High Field MRI, Leiden University Medical Center, Leiden, Netherlands, 2Biomedical Engineering Institute, Boğaziçi University, Istanbul, Turkey, 3BarcelonaBeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain, 4CIBER-BBN, Madrid, Spain, 5Philips Healthcare Iberia, Madrid, Spain, 6Philips Healthcare, Best, Netherlands |
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Physiologic fluctuations can lead to the appearance of artefactual angiographic signal in the perfusion image of time-encoded pCASL previously dubbed “shine-through effect”. The aim of this study was to investigate the potential mechanisms inducing this artefact by characterizing the noise in time-encoded pCASL signal from individual Hadamard columns and rows as well as without labeling. We observed higher temporal standard deviation in the arteries compared to gray matter, and found that the shine-through effect was present even without labeling, suggesting that it is caused by the selective background suppression pulse applied close to acquisition time and the associated fresh inflow. |
| 2717 | Verifying the effect of DANTE preparation pulse for separating spin-compartments in arterial spin labeling using T2-measurement | |
| Shota Ishida1, Hirohiko Kimura2, Naoyuki Takei3, Yasuhiro Fujiwara4, Tsuyoshi Matsuda5, Yuki Matta1, Masayuki Kanamoto1, Nobuyuki Kosaka2, and Eiji Kidoya1 | ||
1Radiological center, University of Fukui Hospital, Eiheiji, Japan, 2Department of Radiology, Faculty of Medical Sciences, University of Fukui, Eiheiji, Japan, 3Global MR Applications and Workflow, GE Healthcare Japan, Hino, Japan, 4Department of Medical Image Sciences, Faculty of Life Sciences, Kumamoto University, Chuo-ku, Japan, 5Division of Ultra-high Field MRI, Institute for Biomedical Science, Iwate Medical University, Shiwa-gun, Japan |
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To verify the characteristics of DANTE for vascular suppression, T2 values of the ASL signal under the application of DANTE were determined. While T2 values without DANTE decreased as the PLD increased, T2 values with DANTE (T2_DANTE) did not change among the PLDs. Moreover, T2_DANTE were equivalent to those of the reference. The positive correlation between T2 values and the ATT without DANTE was not observed when DANTE was used. T2_DANTE were neither dependent on the ATT nor PLD. Therefore, DANTE separates the spin compartments in ASL by selective elimination of intra-vascular signals from total ASL signals. |
| 2718 | Systematic investigation of the sensitivity of optimised pCASL protocols to macrovascular contamination | |
| Logan Xin Zhang1 and Michael A Chappell1,2,3 | ||
1Institute of Biomedical Engineering, University of Oxford, Oxford, United Kingdom, 2Radiological Sciences, Division of Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, United Kingdom, 3Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, United Kingdom |
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Optimised pCASL protocols may still be sensitive to macrovascular contamination (MVC), leading to high CBF estimation error. In this study, we conducted a systematic investigation of CBF sensitivity to MVC from a comprehensive set of optimal pCASL protocols. The general kinetic model was only robust for CBF estimation when tissue ATT was less than 1.5s. An extended kinetic model could reduce CBF sensitivity to up to 2.3s. The results of CBF sensitivity maps could be used for examining a protocol for possible MVC effects before scanning, or data interpretation afterwards. |
| 2719 | Perfusion Quantification using Velocity Selective Inversion pulses in a combined ASL-MRF Framework | |
| Anish Lahiri1, Jeffrey Fessler1, and Luis Hernandez-Garcia2 | ||
1Electrical and Computer Engineering, University of Michigan, Ann Arbor, MI, United States, 2FMRI Laboratory and Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States |
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This work proposes a quantitative perfusion imaging using Velocity Selective Inversion pulses combined with an MR Fingerprinting ASL framework that allows for the alleviation of several nuisance parameters in the model, and provides hemodynamic estimates over an extensive region of the brain in a single scan. Preliminary in-vivo experiments indicate that the obtained hemodynamic estimates in gray and white matter agree with values typically found in literature. |
| 2720
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A general framework for eddy current minimization in Velocity Selective Arterial Spin Labeling | |
| Joseph G. Woods1, Eric C. Wong1, David D. Shin2, and Divya Bolar1 | ||
1Department of Radiology, University of California San Diego, San Diego, CA, United States, 2GE Healthcare, Menlo Park, CA, United States |
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A novel framework that minimizes eddy current mismatch between tag and control acquisitions in velocity-selective (VS) arterial spin labeling is introduced. The framework is based on minimizing the 0th-order gradient moment in the presence of eddy currents and is applicable to any VS module design, without suffering a time penalty in module duration. Simulation and empirical data are presented and demonstrate reductions in eddy current artifacts in both phantom and in vivo data. |
| 2721 | Reduction of motion effects in myocardial arterial spin labeling | |
| Verónica Aramendía-Vidaurreta1,2, Pedro M. Gordaliza3,4, Marta Vidorreta5, Rebeca Echeverría-Chasco1,2, Gorka Bastarrika1,2, Arrate Muñoz-Barrutia3,4, and María A. Fernández-Seara1,2 | ||
1Radiology, Clínica Universidad de Navarra, Pamplona, Spain, 2IdiSNA, Instituto de Investigación Sanitaria de Navarra, Pamplona, Spain, 3Universidad Carlos III de Madrid, Madrid, Spain, 4Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain, 5Siemens Healthineers, Madrid, Spain |
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This work investigated the impact of three different breathing strategies, named breathhold (BH), synchronized-breathing (SB) and free-breathing (FB), together with motion detection and correction algorithms in myocardial arterial spin labeling (ASL) images. Results indicate the superiority of FB combined with pairwise registration, which showed higher accuracy (in synthetic images) and higher intrasession reproducibility together with lower variability across subjects (in in vivo images). BH and SB after motion detection provided similar results, but their practical application is more complicated as it demands the subject's collaboration to follow the respiratory pattern in SB or perform the apneas in BH. |
| 2722 | Clinically applicable automatic quantitative renal perfusion measurement using ASL-MRI and machine learning | |
| Isabell Katrin Bones1, Clemens Bos1, Chrit Moonen1, Jeroen Hendrikse2, and Marijn van Stralen1 | ||
1Center for Image Sciences, University Medical Center Utrecht, Utrecht, Netherlands, 2Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands |
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ASL-MRI quantification involves kidney segmentation and cortex-medulla differentiation to obtain cortical renal blood flow, requiring time consuming manual interaction hampering clinical adoption. We applied machine learning to automat renal ASL-MRI quantification. A cascade of three U-nets was constructed to replace manual segmentation steps. Automatic segmentation yielded a dice score of 0.78, which was similar to the inter-observer variability of 0.77. Moreover, good agreement for cortical RBF was found between automatic and manual segmentations on group and individual level; 211±31 and 208±31mL/min/100g, respectively. Our proposed method automates quantification without compromising performance. This makes renal ASL-MRI more attractive for clinical application. |
| 2723 | Arterial Spin Labeling Denoising with Convolutional Neural Network and Convolutional Long-Short-Term-Memory (ConvLSTM) | |
| Qinyang Shou1, Chaitanya Gupte2, Danny JJ Wang1, and Hosung Kim2 | ||
1Laboratory of Functional MRI Technology (LOFT), Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, United States, 2Neuroimaging with Deep Learning Lab (NIDLL), Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, United States |
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The purpose of this study was to develop a deep learning algorithm for 3D spatial-temporal denoising of ASL perfusion image series. 162 datasets from the Pediatric Template of Brain Perfusion database were used for model training and testing. The results showed that the proposed method can achieve higher Peak Signal-to-Noise Ratio (PSNR) and higher Structural Similarity Index (SSIM) than averaging of the time series and using traditional Principal Component Analysis (PCA) denoising. This result was robust when reducing the input measurements to one quarter of the total measurements, which shows the potential to reduce the scan time for ASL imaging. |
| 2724 | Gradient adjustments for improved pcASL exploiting a B1+ shimmed labeling train | |
| Christian R. Meixner1, Sebastian Schmitter2,3, Jürgen Herrler4, Arnd Dörfler4, Michael Uder1, and Armin M. Nagel1,3 | ||
1Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany, 2Physikalisch-Technische Bundesanstalt (PTB), Braunschweig und Berlin, Germany, 3Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany, 4Institute of Neuro-Radiology, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany |
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Pseudo-continuous arterial spin labeling (pcASL) at 7T suffers from insufficient B1+-amplitudes and specific absorption rate (SAR) constraints. Even with B1+ phase-only or phase/amplitude shimming for the labeling the resulting inversion is suboptimal. In this work, we performed Bloch simulations to examine the impact of thicker pcASL labeling slices by adjusting the slice-selective gradient of a B1+-shimmed labeling train exploiting Variable-Rate Selective Excitation. The findings were evaluated experimentally in 5 healthy volunteers. Using lower slice-selective gradients and subsequently longer exposure of the spins to the pcASL labeling train, the perfusion images improved according to gray matter temporal signal-to-noise ratio by 35%. |
| 2725 | Whole-brain Perfusion Mapping at 7T by SAR-efficient Non-segmented 3D EPI-pCASL | |
| Seon-Ha Hwang1, SoHyun Han2, Seong-Gi Kim2, Jaeseok Park3,4, and Sung-Hong Park1 | ||
1Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea, Republic of, 2Center for Neuroscience Imaging Research, Institute of Basic Science, Suwon, Korea, Republic of, 3Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Korea, Republic of, 4Department of Intelligent Precision Healthcare Convergence, Suwon, Korea, Republic of |
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Due to high specific absorption rate (SAR), it has not been easy to apply pseudo-continuous arterial spin labeling (pCASL) at 7T human MRI, especially with 3D readouts. In this study, non-segmented 3D-EPI-pCASL is proposed for whole-brain perfusion mapping. SAR was reduced by multiple low-flip-angle water-excitation rectangular RF pulses for 3D EPI. The proposed 3D-EPI-pCASL produced consistent perfusion maps at both 3T and 7T compared to 2D-EPI-pCASL which was available only at 3T because of SAR. The high temporal resolution of the proposed non-segmented 3D-EPI-pCASL enabled us to get a whole-brain 3D pCASL fMRI map at 7T for the first time. |
| 2726 | PCASL labeling efficiency measurement with B0 off-resonance compensation at 7T | |
| Gael Saib1, Alan Koretsky1, and S Lalith Talagala2 | ||
1NINDS/LFMI, National Institutes of Health, Bethesda, MD, United States, 2NINDS/NMRF, National Institutes of Health, Bethesda, MD, United States |
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At 7T, it is known that B1+ and B0 inhomogeneities reduce the PCASL labeling efficiency. Further, the short T2 of blood also reduces the maximum blood labeling efficiency that can be achieved in practice. In this work, we employed a PCASL-prepared FLASH sequence to measure vessel-specific labeling efficiency of PCASL with B0 off-resonance correction. At 7T, experimental data indicates a maximal labeling efficiency of ~0.6. This study also shows that optimization of PCASL labeling efficiency is possible by tailoring the average gradient according to the blood velocity range and B1 at the feeding arteries. |
| 2727 | Retrospective Motion Correction of multi-shot 3D GRASE Arterial Spin Labelling using ESPIRiT reconstruction | |
| Jack Highton1, Enrico De Vita2, and David Thomas3,4,5 | ||
1UCL Queen Square Institute of Neurology, University College London, London, United Kingdom, 2School of Biomedical Engineering and Imaging Sciences, Kings College London, London, United Kingdom, 3Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom, 4Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, University College London, London, United Kingdom, 5Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom |
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A retrospective motion correction method is presented, for multi-shot 3D GRASE ASL. ESPIRiT is used to calculate coil sensitivity fields, using raw ASL k-space data. These are used to reconstruct complete images from the interleaved fractions of k-space sampled during each shot using SENSE. Therefore, typical image registration can be used to correct inter-shot motion. The method was tested using a simulation of 3D GRASE ASL and an equivalent experiment, where the subject was trained to nod or keep still. The motion correction reduced artefacts, and increased the correlation between cerebral blood flow measurements acquired with and without motion. |
| 2728 | Optimization and Evaluation of Super-Resolution SMS ASL with Slice-Dithered Enhanced Resolution (SLIDER) technique | |
| Qinyang Shou1, Xingfeng Shao1, and Danny JJ Wang1 | ||
1Laboratory of Functional MRI Technology (LOFT), Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, United States |
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The goal of this study is to optimize and evaluate super-resolution simultaneous multislice (SMS) Arterial Spin Labeling (ASL) using the Slice Dithered Enhanced Resolution (SLIDER). Different numbers (2/3/4) of shifted slices for SLIDER SMS ASL were evaluated for spatial and temporal SNR. The results showed that the SNR efficiency of SLIDER SMS ASL increased with a greater number of shifted slices which may be attributed to reduced g-factor for SMS imaging of thicker slices as well as the presence of physiological noise. |
| 2729 | Saturated Look-Locker FAIR (SALL-FAIR) Sequence with FPOCK Model for Simultaneous Acquisition of CBF, aBAT, tBAT, and T1 Map | |
| Zihan Ning1, Shuo Chen1, Zhensen Chen1, Huiyu Qiao1, Hualu Han1, Rui Shen1, Dandan Yang1, and Xihai Zhao1 | ||
1Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine Tsinghua University, Beijing, China |
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A SAturated Look-Locker Flow-sensitive Alternating Inversion Recovery (SALL-FAIR) sequence combined with the Four-Phase One-Compartment Kety (FPOCK) kinetic model was proposed for simultaneous acquisition of CBF, aBAT, tBAT and T1 map with a single scan. The T1 maps of SALL-FAIR were verified by standard IR-SE on phantom, and higher accuracy of perfusion quantification from SALL-FAIR with FPOCK model was proved by comparing with the Buxton’s and the single-TI model in vivo. |
| 2730 | BATS: the Boston ASL Template and Simulator – development and initial evaluation | |
| Manuel Taso1, Fanny Munsch1, and David C Alsop1 | ||
1Division of MRI research, Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States |
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Neuroscientific and clinical research has seen tremendous advances over the past 25 years. While hardware, pulse-sequences and reconstruction developments have been an immense driver for this, image processing tools have also been crucial.While anatomical templates such as the MNI152 have become widely used and are a hallmark of neuroimaging analyses, functional contrast-specific templates for group studies are much scarcer but of great interest. We therefore report here the initial development of BATS – the Boston ASL Template and Simulator, highlighting its development and initial use. |
| 2731 | ASLDRO: Digital reference object software for Arterial Spin Labelling | |
| Aaron Oliver-Taylor1, Thomas Hampshire1, Nadia A S Smith2, Michael Stritt3, Jan Petr4, Johannes Gregori3, Matthias Günther3,5, Henk J Mutsaerts6, and Xavier Golay1,7 | ||
1Gold Standard Phantoms Limited, London, United Kingdom, 2National Physical Laboratory, Teddington, United Kingdom, 3mediri GmbH, Heidelberg, Germany, 4Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany, 5Fraunhofer MEVIS, Bremen, Germany, 6Amsterdam University Medical Center, Amsterdam, Netherlands, 7Institute of Neurology, University College London, London, United Kingdom |
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ASLDRO is digital reference object software for Arterial Spin Labelling. Here we present the development and demonstration of the DRO software, and its use in a sensitivity and uncertainty analysis of the single-subtraction equation for ASL perfusion quantification.The DRO software was written in python, and can generate synthetic ASL control, label and M0 data in ASL BIDS format. Pulsed and continuous labelling are supported, and patient motion and instrument noise are accurately simulated. It can be used both for testing and validation of image processing software, and for investigating ASL quantification models. |
| 2732 | Reproducibility and repeatability of quantitative pCASL measurements in a 3D-printed perfusion phantom | |
| Yiming Wang1, Limin Zhou1, Durga Udayakumar1,2, and Ananth J. Madhuranthakam1,2 | ||
1Radiology, UT Southwestern Medical Center, Dallas, TX, United States, 2Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, United States |
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Arterial spin labelling (ASL) is a non-invasive and non-contrast perfusion imaging technique that can serve as an imaging biomarker to assess tissue blood flow characteristics. A perfusion phantom is valuable to evaluate newly developed ASL sequences, test consistency and to compare sequence reproducibility across various scanners. In this study, we performed a longitudinal assessment of the reproducibility and repeatability of perfusion measurement using 2D pCASL sequence with 20 PLDs over 5 weeks duration with a previously developed 3D printed perfusion phantom. Intra-class correlation coefficient (ICC) of measured perfusion and T1 are 0.96 and 0.94 respectively, indicating good reproducibility and repeatability. |
| 2733 | A quantitative multiparametric 18F-FPIA PET/MRI study for the characterization of primary brain gliomas | |
| Marianna Inglese1, Shah Islam1, Matthew Grech-Sollars1,2, Giulio Anichini3, James Davies4, Azeem Saleem4,5, Matthew Williams6,7, Kevin S O'Neill3, Adam D Waldman8, and Eric O Aboagye1 | ||
1Surgery and Cancer, Imperial College London, London, United Kingdom, 2Imaging, Imperial College London Healthcare NHS Trust, London, United Kingdom, 3Imperial College London Healthcare NHS Trust, London, United Kingdom, 4Invicro Imperial College London, London, United Kingdom, 5Hull York Medical School, Faculty of Health Sciences, University of Hull, Hull, United Kingdom, 6Computational Oncology Group, Department of Surgery and Cancer, Imperial College London, London, United Kingdom, 7Institute for Global Health Innovation, Imperial College London, London, United Kingdom, 8Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom |
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18F-FPIA PET/MRI integrates two imaging modalities that can provide valuable insight into the characterization and classification of brain tumours. 10 patients with primary brain gliomas were recruited to this study. Static and dynamic 18F-FPIA PET, together with perfusion/diffusion MRI data were post-processed for the extraction of 3D parametric maps for each subject. Correlations among parameters were evaluated with Spearman test. Tumour grade prediction was assessed with a machine learning model. A strong correlation was found between uptake and influx rate constant of FPIA and MRI perfusion parameters. The PET/MRI methodology provided 100% accuracy in differentiating low from high grade tumours. |
| 2734 | Identification of IDH1 mutation status in glioblastoma using multi-delay 3D arterial spin labeling perfusion MRI: a pilot study | |
| Huilou Liang1,2, Lianwang Li3, Yuchao Liang3, Siqi Cai4, Jing An5, Yan Zhuo1,2,6, Lijuan Zhang4, Danny JJ Wang7, and Rong Xue1,2,8 | ||
1State Key Laboratory of Brain and Cognitive Science, Beijing MRI Center for Brain Research, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China, 2University of Chinese Academy of Sciences, Beijing, China, 3Department of Neurosurgery, Beijing Tiantan Hospital of Capital Medical University, Beijing, China, 4Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China, 5Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen, China, 6CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Beijing, China, 7Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States, 8Beijing Institute for Brain Disorders, Beijing, China |
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Arterial spin labeling (ASL) perfusion MRI with single post-labeling delay (PLD) has been used to noninvasively predict the IDH1 mutation status in glioblastoma patients. However, single-delay ASL can make inaccurate estimations of cerebral blood flows (CBF) due to the variability of arterial transit times (ATT) among individuals. In this study, we applied multi-delay 3D ASL technique with multiple hemodynamic parameters including quantitative ATT, ATT-corrected CBF and arterial cerebral blood volume (aCBV) in glioblastoma. Our results show that aCBV-based relative perfusion parameters may provide a better identification of IDH1 mutation status and is worthy of further verification in future studies. |
| 2735 | Intrasession reliability of arterial spin labeled MRI measured perfusion in GBM at 3T | |
| Limin Zhou1, Yiming Wang1, Marco Da Cunha Pinho1,2, Edward Pan3,4,5, Yin Xi1,6, Joseph A Maldjian1,2, and Ananth J Madhuranthakam1,2 | ||
1Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, United States, 2Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX, United States, 3Department of Neurology and Neurotherapeutics, University of Texas Southwestern Medical Center, DALLAS, TX, United States, 4Department of Neurological Surgery, University of Texas Southwestern Medical Center, DALLAS, TX, United States, 5Harold C. Simmons Cancer Center, University of Texas Southwestern Medical Center, DALLAS, TX, United States, 6Department of Population and Data Sciences, University of Texas Southwestern Medical Center, Dallas, TX, United States |
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A 3D TSE using Cartesian acquisition with spiral profile reordering (CASPR) in combination with pseudo-continuous arterial spin labeling (pCASL) was developed to improve the robustness of ASL measured perfusion to increased B0 inhomogeneities in GBM patients. Previous results showed high intrasession reliability of this method in GBM patients. In this study, we compared the 3D TSE-CASPR measured perfusion with clinically available 3D GraSE at 3T. With 24 GBM imaging sessions, the results showed that 3D pCASL with TSE-CASPR is more robust to B0 inhomogeneities and has higher intrasession reliability than the clinical sequence, 3D pCASL with GraSE at 3T. |
| 2736 | The feasibility of 3D pcASL MRI with Multiple post-labeling delay times in evaluating subtypes of parotid gland tumors | |
| Lu Chen1, Guo-Yi Su1, Weiqiang Dou2, Yong Shen3, Fei-Yun Wu1, and Xiao-Quan Xu1 | ||
1Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China, 2GE Healthcare, MR Research China, Beijing, P.R. China, Beijing, China, 3GE Healthcare, MR Enhanced Application China, Beijing, P.R. China, Beijing, China |
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In this study, we aimed to investigate 3D pcASL with multiple PLDs in evaluating subtypes of parotid gland tumors. By quantitatively measuring tumor blood flow (TBF) and comparing the values within and between subgroups, we found 3D pcASL with multiple PLDs can differentiate parotid gland tumors and reflect changes of TBF. With these findings, 3D pcASL MRI, especially with short PLD was suggested to evaluate patients with parotid gland tumors in routine clinical practice. |
| 2737 | Robust Implementation of a 3D Pulsed ASL Sequence for Assessment of Liver Perfusion | |
| Jörn Huber1, Daniel Hoinkiss1, and Matthias Günther1,2 | ||
1Fraunhofer MEVIS, Bremen, Germany, 2University of Bremen, Bremen, Germany |
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Liver perfusion can give valuable functional information about diseases like carcinoma and cirrhosis. Arterial Spin Labeling allows non-invasive assessment of liver perfusion without exogenous contrast agents being especially helpful in patients with renal failure. ASL in abdominal organs like liver faces increased challenges due to low perfusion rates, breathing motion and strong off-resonance as well as B1-inhomogeneity. In this work, a robust implementation of a pulsed ASL (PASL) sequence with FAIR labeling and 3D GRASE readout is provided, addressing these difficulties. |
| 2738 | Depicting the developmental trajectories of brain cerebral blood flow using 3D ASL in children aged 28 days to 15 years. | |
| Peiyao Chen1, Chao Jin1, Xianjun Li1, Miaomiao Wang1, Congcong Liu1, Xiaoyu Wang1, Fan Wu1, Yuli Zhang1, Cong Tian1, Mengxuan Li1, Xiaocheng Wei2, and Jian Yang1 | ||
1First Affiliated Hospital of Xi 'an Jiaotong University, Xi'an, Shaanxi, China, 2MR Research China, GE Healthcare, Beijing, China |
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Adequate cerebral blood flow (CBF) is essential for development of brain structure and function. However, little is known about the developmental trajectory of CBF across the broad age range in childhood. This study aims to investigate the spatiotemporal evolution of CBF in cerebral cortex and basal ganglia in healthy term children aged from 28 days to 15 years. Our results indicated that the estimated age with highest CBF was earliest in the occipital lobe, followed by temporal and parietal lobe, at last in the frontal lobe. The perfusion of basal ganglia showed a U-shaped curve, which slowly increased with age. |
| 2739 | Brain perfusion in dementia with Parkinson's disease and Alzheimer’s disease: an arterial spin labeling MRI study | |
| Hongri Chen1, Weiqiang Dou2, and Wei yin Liu2 | ||
1Dalian Medical University, Northern Jiangsu People’s Hospital, Yangzhou, China, Yangzhou, China, 2GE Healthcare, MR Research China, Beijing, P.R. China, Beijing, China |
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The present study was to explore regional perfusion changes in patients with Parkinson's disease dementia (PDD) and Alzheimer’s disease (AD) using 3D arterial spin labeling MRI and further assess the corresponding difference between PDD and AD patients. The results revealed that the perfusion pattern in PDD group was distinct from that in AD group despite of overlapped perfusion regions. The resultant normalized cerebral blood flow (CBF) can distinguish PDD from AD. Therefore, normalized CBF provided sensitive imaging-based markers that contribute to the diagnosis and differential diagnosis of the two dementia. |
| 2740
|
Relationship between global grey matter perfusion, damage and disability in multiple sclerosis | |
| Daniele Mascali1, Antonio Maria Chiarelli1, Ilona Lipp2,3, Anna Digiovanni4, Valentina Tomassini1,3,4, and Richard Geoffrey Wise1,3 | ||
1Institute for Advanced Biomedical Technologies,Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio University" of Chieti-Pescara, Chieti, Italy, 2Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 3Cardiff University Brain Research Imaging Centre (CUBRIC) School of Psychology, Cardiff University, Cardiff, United Kingdom, 4MS Centre, Neurology Unit, SS. Annunziata University Hospital, Chieti, Italy |
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We investigated the relationship between grey matter perfusion and clinical and conventional MRI measures in patients with relapsing multiple sclerosis (MS) to test the hypothesis that an impaired energy supply is associated with the development of brain damage and clinical disability. Using multi-inversion time pulsed ASL we demonstrated that MS patients have significantly lower cerebral grey matter perfusion when compared to healthy controls. In the patients, lower perfusion correlates with greater tendency to develop irreversible tissue damage and with worse clinical scores, suggesting that altered energy supply may directly contribute to damage and disability in MS. |
| 2741 | ASL perfusion and disability in primary progressive MS: an observational cohort study | |
| Clara Delacour1, Ahmed-Ali El Ahmadi1, Gilles Brun1, Nadine Girard1,2, Christoph Heesen3,4, Arzu Ceylan Has3,4, and Jan-Patrick Stellmann2,3,4,5 | ||
1Neuroradiology, APHM La Timone, Marseille, France, 2Aix-Marseille Univ, CNRS, CRMBM, UMR 7339, Marseille, France, 3Institute of Neuroimmunology and MS (INIMS), University Medical Centre Hamburg-Eppendorf, Hamburg-Eppendorf, Germany, 4Neurology, University medical centre Hamburg-Eppendorf, Hamburg-Eppendorf, Germany, 5APHM La Timone, CEMEREM, Marseille, France |
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Disability progression in Multiple Sclerosis (MS) is driven by inflammation and neurodegeneration. Arterial spin labelling (ASL) is a non-invasive MRI method for the assessment of brain perfusion without the need for gadolinium. Here, we explored ASL perfusion as a biomarker for diseases progression and disability in a cohort of 77 patients with primary progressive MS (PPMS). While brain perfusion seemed rather stable during the follow-up of up to 5 years, we observed an association between higher regional perfusion rates and cognitive performance and hand functioning. Altered perfusion in PPMS seems thus not closely related to the major pathomechanism neurodegeneration. |
| 2742 | Reliability of Arterial Spin Labeling derived Cerebral Blood Flow measurements in Periventricular White Matter | |
| Sudipto Dolui1, Audrey P. Fan2,3, Moss Y. Zhao3, Greg Zaharchuk3, and John A. Detre1,4 | ||
1Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States, 2Departments of Biomedical Engineering and Neurology, University of California, Davis, CA, United States, 3Department of Radiology, Stanford University, Palo Alto, CA, United States, 4Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States |
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Periventricular white matter (PVWM) is exclusively perfused by small vessels, and hence PVWM Cerebral Blood Flow (CBF) can provide a biomarker of cerebral small vessel functional integrity. Although PVWM is weakly perfused, we demonstrate that PVWM-CBF derived from state-of-the-art Arterial Spin Labeling (ASL) acquired twice ~15minutes apart in a cohort of 16 subjects showed high reproducibility that was comparable to other larger regions of interest. Further there was high correlation between PVWM-CBF derived from ASL and concurrently acquired [15O]-water Positron Emission Tomography data. These findings suggest that PVWM CBF can be reliably measured with advanced ASL methods. |
| 2743 | Reduced Cerebral Blood Flow in Patients with Pulmonary Arterial Hypertension | |
| Bhaswati Roy1, Susana Vacas1, Kathy McCloy2, Rajan Saggar2, and Rajesh Kumar1,3,4,5 | ||
1Anesthesiology, University of California Los Angeles, Los Angeles, CA, United States, 2Medicine, University of California Los Angeles, Los Angeles, CA, United States, 3Bioengineering, University of California Los Angeles, Los Angeles, CA, United States, 4Radiological Sciences, University of California Los Angeles, Los Angeles, CA, United States, 5Brain Research Institute, University of California Los Angeles, Los Angeles, CA, United States |
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Pulmonary arterial hypertension (PAH) patients show cognitive and mood impairments, and brain tissue injury in those areas. However, the underlying cause of tissue damage in PAH patients remain unclear. Altered cerebral blood flow (CBF) may contribute to develop brain tissue injury and cognitive and mood deficits. We evaluated CBF in PAH patients over controls, and found changes in the prefrontal cortices, insula, cingulate, frontal cortex, corona radiate, temporal, occipital, and parietal gyrus. Significant correlations also emerged between CBF and functional deficits in PAH, including mood and cognition symptoms, implying altered hemodynamic contributing to brain changes and functional deficits. |
| 2744 | Moving Towards Robust Quantification of Cerebrovascular Reactivity (CVR) using Pseudocontinuous Arterial Spin Labelling (pCASL) | |
| Colette C. Milbourn1, Thomas W. Okell2, and Nicholas P. Blockley1 | ||
1The School of Life Sciences, University of Nottingham, Nottingham, United Kingdom, 2Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom |
||
New clinical tools are needed for the diagnosis and prognosis of cerebrovascular diseases. Pseudocontinuous Arterial Spin Labelling (pCASL) is recommended for quantifying tissue cerebral blood flow due to its superior signal-to-noise. Stressors to the brain like high carbon dioxide (hypercapnia), used to map Cerebrovascular Reactivity (CVR), are known to reduce the labelling efficiency of pCASL and therefore underestimate CVR. In this study a systematic difference in CVR was observed across measurements made with three different sets of pCASL parameters. Ultimately this work will help to determine pCASL parameters that minimise systematic error and produce robust quantitative estimates of CVR. |
| 2745 | Arterial Spin Labeling Can Identify Cerebrovascular Reactivity Deficit in Patients with Vasculopathy: A Pilot Study Using Simultaneous PET/MRI | |
| Moss Y Zhao1, Audrey P Fan2, David Chen3,4, Jia Guo5, Yosuke Ishii6, David Shin7, Mohammad Mehdi Khalighi1, Dawn Holley1, Kim Halbert1, Andrea Otte1, Brittney Williams1, Jun-Hyung Park1, Bin Shen1, Gary Steinberg8, and Greg Zaharchuk1 | ||
1Radiology, Stanford University, Stanford, CA, United States, 2Biomedical Engineering and Neurology, University of California Davis, Davis, CA, United States, 3Medical Imaging, Taipei Medical University – Shuan-Ho Hospital, New Taipei City, Taiwan, 4Department of Radiology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan, 5Bioengineering, University of California Riverside, Riverside, CA, United States, 6Neurosurgery, Tokyo Medical and Dental University, Tokyo, Japan, 7GE Healthcare, Melo Park, CA, United States, 8Neurosurgery, Stanford University, Stanford, CA, United States |
||
Cerebrovascular reactivity (CVR) reflects the capacity of the brain to respond to external stress. Impaired CVR leads to a higher risk of stroke. The standard CVR measuring tool relied on PET imaging but is inaccessible to most patients. Here we investigate the CVR of Moyamoya patients using arterial spin labeling (ASL), a non-invasive and quantitative MRI technique. Results showed that significant lower CVR was found in flow territories with severe stenosis or occlusion, making ASL a potential diagnostic tool to predict the risk of stroke for patients with vasculopathy. |
| 2746 | A digital brain perfusion phantom for validation of ASL data post-processing software | |
| Chenyang Zhao1, Ze Wang2, and Danny Wang1 | ||
1Laboratory of Functional MRI Technology (LOFT), Mark & Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, United States, 2Department of Diagnostic Radiology and Nuclear Medicine, School of Medicine, University of Maryland, Baltimore, MD, United States |
||
A digital brain perfusion phantom was designed using a representative 5-delay 3D pCASL protocol and applied to validate the quantification accuracy of 4 ASL post-processing software packages, including ASLtbx, ASL_MRICloud, BASIL, and Cereflow. The 4 tested software can produce generally correct quantification results under normal SNR conditions, however their accuracy may be affected by the limitation occurred in low perfusion regions and low SNR condition. The digital phantom provides a reliable reference with high flexibility to validate ASL post-processing software. |
| 2747 | Association of Arterial Spin Labeling Global Metrics and Attentional Processes | |
| Shichun Chen1, Yakun Zhang1, Zongpai Zhang1, Wenna Duan1, George Weinschenk1, Brandon E. Gibb2, Wenming Luh3, and Weiying Dai1 | ||
1Department of Computer Science, State University of New York at Binghamton, Binghamton, NY, United States, 2Department of Psychology, State University of New York at Binghamton, Binghamton, NY, United States, 3National Institute on Aging, National Institutes of Health, Baltimore, MD, United States |
||
We investigated the relationship between brain global activity or global topology of brain networks and attentional processes. The former measures were evaluated by dynamic arterial spin labeling (ASL) perfusion fMRI. The latter measures were assessed by P3 amplitude and latency in event-related potentials (ERPs). The P3 properties were significantly correlated with numbers of correct response. We found positive associations between global perfusion and P3 amplitude and between characteristic path length and P3 latency, and negative associations between global perfusion, global efficiency, mean functional connectivity and P3 latency, indicating close correlation of brain global behavior and attention. |
| 2748 | Mapping water exchange rate change after caffeine uptake using 3D diffusion prepared arterial spin labeled perfusion MRI | |
| Qihao Zhang1, Jana Ivanidze2, Thanh Nguyen2, Pascal Spincemaille2, and Yi Wang1 | ||
1Cornell University, New York, NY, United States, 2Weill Cornell Medical College, New York, NY, United States |
||
We propose to exam the water exchange rate (kw) change after caffeine uptake based on an optimized diffusion prepared arterial spin labeling (ASL) sequence and reconstruction method in a previous work1. 5 subjects went through two scans to test the reproducibility of the reconstruction pipeline. Another 5 subjects are scanned before and half an hour after caffeine uptake. Cerebral blood flow (CBF) and are reconstructed from the ASL images. A 26% decrease in CBF and 13% decrease of kw is observed. |
| 2749 | High spatio-temporal resolution 3D ASL renal perfusion with variable-density FSE and deep-learning reconstruction | |
| Manuel Taso1, Uri Wollner2, Arnaud Guidon3, Rafi Barda2, Christopher J Hardy4, Sangtae Ahn4, and David C Alsop1 | ||
1Division of MRI research, Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States, 2GE Research, Herzliya, Israel, 3Global MR Applications and Workflow, GE Healthcare, Boston, MA, United States, 4GE Research, Niskayuna, NY, United States |
||
Arterial spin labeling (ASL) has proven to be a powerful research and clinical technique for functional imaging of tissues. The combination of undersampled acquisitions and compressed sensing reconstruction shows promise for increased speed, resolution, and robustness but conventional CS reconstructions are slow and may not be satisfactory, especially for low SNR data. This work explores the feasibility and performance of Deep-Learning based reconstruction of similarly sampled data to realize the full potential of these ASL acquisitions using DCI-net, an unenrolled iterative CS network. We show DCI-net performance at high acceleration rates and potential for fast volumetric ASL perfusion imaging. |
| 2750 | Reproducibility of multiparametric MRI in transplanted kidneys | |
| Rebeca Echeverria-Chasco1,2, Marta Vidorreta3, Veronica Aramendia-Vidaurreta2,4, David Cano 1, Gorka Bastarrika2,4, Nuria Garcia-Fernandez2,5, Paloma L. Martin Moreno2,5, and Maria A. Fernandez-Seara2,4 | ||
1Radiology, Clínica Universidad de Navarra, Pamplona, NE, Spain, 2IdiSNA, Instituto de Investigación Sanitaria de Navarra, Pamplona, Spain, 3Siemens Healthineers, Madrid, Spain, 4Radiology, Clínica Universidad de Navarra, Pamplona, Spain, 5Nephrology, Clínica Universidad de Navarra, Pamplona, Spain |
||
The goals of this work were to test a multiparametric MRI protocol to measure perfusion, diffusion and T1 and to assess inter-session reproducibility in a group of transplanted patients with stable renal function. 18 patients were imaged in 2 exams employing pseudo-continuous arterial spin labeling technique, intravoxel incoherent motion technique and T1 mapping sequence. Reproducibility was assessed using Bland-Altman analysis, within-subject coefficient of variation (CVws) and intra-class correlation coefficient (ICC). Results of the 3 techniques were promising showing a CVws <20% in most of the cases (especially for T1 and D (<6%)) and high ICC coefficients for PCASL and T1. |
| 2751 | Measurement of Pulmonary Perfusion under Expiratory and Inspiratory Breathing Conditions using PCASL-bSSFP Imaging at 1.5 Tesla | |
| Petros Martirosian1, Rolf Pohmann2, Martin Schwartz1,3, Thomas Kuestner4, Manuel Kolb4, Ahmed Othman4, Cecilia Zhang4, Klaus Scheffler2,5, Konstantin Nikolaou4, Fritz Schick1, and Ferdinand Seith4 | ||
1Section on Experimental Radiology, University of Tübingen, Tübingen, Germany, 2Max Planck Institute for Biological Cybernetics, Tübingen, Germany, 3Institute of Signal Processing and System Theory, University of Stuttgart, Stuttgart, Germany, 4Department of Diagnostic and Interventional Radiology, University of Tübingen, Tübingen, Germany, 5Department of Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany |
||
Pseudo-continuous-arterial-spin-labeling (PCASL) has been successfully applied in the lung providing high quality perfusion images. The pulmonary blood flow and the respiratory system interact closely: the intrathoracic pressure has impact on the venous return. Therefore, in this work, we evaluate the effects of intrathoracic pressure on lung perfusion by using PCASL imaging in end-expiratory and end-inspiratory breath-hold. PCASL imaging is able to detect changes of parenchymal lung perfusion caused by alterations of the intrathoracic pressure. Perfusion signal measured under end-inspiratory condition were noticeably reduced as compared to end-expiratory breath-hold. This correlated significantly with measured blood flow volume through the pulmonary trunk. |
| 2752 | Prostate Perfusion Mapping using Fourier-Transform based Velocity-Selective Pulse Trains: Choice of Cutoff Velocity and Comparison with Brain | |
| Dapeng Liu1,2, Dan Zhu3, Wenbo Li1,2, and Qin Qin1,2 | ||
1Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, United States, 2F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States, 3Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, United States |
||
Prostate perfusion mapping using velocity-selective arterial spin labeling (VSASL) is desired for higher SNR and insensitivity to arterial transit delay. The choice of cutoff velocity (Vc) determines its sensitivity to perfusion-weighted signal (PWS). The utility of Fourier-transform based velocity-selective (FT-VS) pulse trains have been demonstrated in cerebral blood flow and cerebral blood volume mapping. In this study, FT-VS prepared blood flow and blood volume mapping sequences were performed in parallel in both brain and prostate to investigate their Vc dependence to PWS. The results suggest that lower Vc is demanded for prostate VSASL. |
| 3401
|
Realistic simulations of diffusion MR spectroscopy: The effect of glial cell swelling on non-Gaussian and anomalous diffusion | |
| André Döring1, Maryam Afzali1, Elena Kleban1, Roland Kreis2, and Derek K Jones1 | ||
1Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom, 2Departments of Radiology and Biomedical Research, University of Bern, Bern, Switzerland |
||
An existing Monte-Carlo simulation was refined to allow realistic modeling of 150x150x150μm³ tissue samples. The approach was validated on a reference sample, where ground truth is known. The non-Gaussian and anomalous diffusion behavior in diffusion MR spectroscopy experiments was modeled in realistic tissue samples composed of 30 glial cells addressing a hypothesized cell swelling evoked by glial activation. The simulated results agree well with in vivo literature values and may help to improve the linkage between diffusion and histology. |
| 3402 | Characterizing time-dependent diffusion in the extra-axonal space of white matter for axon loss and demyelination | |
| Ricardo Coronado-Leija1, Hong-Hsi Lee1, Els Fieremans1, and Dmitry S. Novikov1 | ||
1Radiology, New York University School of Medicine, New York, NY, United States |
||
In this work, we use Monte Carlo simulations to show how time-dependent diffusion, D(t), in the extra-axonal space provides information about the packing geometry of the axons. In particular we relate the correlation-length obtained from simulations to the correlation-length computed from the power spectrum of the axon packings. We also show through Monte Carlo simulations, in geometries of cylinders and realistic substrates, that D(t) can provide information that differentiates between axon loss and demyelination. |
| 3403 | A minimal geometrical model for Monte Carlo simulations of time dependent diffusion in axons | |
| Henrik Lundell1 and Samo Lasič1,2 | ||
1Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark, 2Random Walk Imaging, Lund, Sweden |
||
Understanding the link between axonal geometry and diffusion is of large relevance for diffusion weighted MRI (DW-MRI) of white matter. Identifying the minimal geometrical features needed to describe time dependent diffusion allows for faster simulations adequate for the experimentally feasible level of abstraction. We propose an augmented 1D random walk model that within relevant limits mimics the time dependent diffusion in a 3D model of an axon with varying radius. |
| 3404 | Quantifying Cell Size and Membrane Permeability with Microstructure Fingerprinting | |
| Khoi Minh Huynh1,2, Ye Wu2, and Pew-Thian Yap1,2 | ||
1Biomedical Engineering, UNC Chapel Hill, Chapel Hill, NC, United States, 2Department of Radiology and Biomedical Research Imaging Center (BRIC), UNC Chapel Hill, Chapel Hill, NC, United States |
||
In diffusion MRI, biophysical models offer a non-invasive means of probing the tissue micro-architecture of the human brain. However, most models rely on closed-form formulas derived with simplifying assumptions such as short gradi- ent pulse, Gaussian phase distribution, and the absence of compartmental ex- change. We present a fast microstructure fingerprinting framework for accurate estimation of axon/soma radii and membrane permeability without relying on these assumptions. |
| 3405 | DIFFnet: Diffusion parameter mapping network generalized for input diffusion gradient directions and b-values | |
| Juhyung Park1, Woojin Jung1, Eun-jung Choi1, Se-Hong Oh2, Dongmyung Shin1, Hongjun An1, and Jongho Lee1 | ||
1Seoul National University, Seoul, Korea, Republic of, 2Hankuk University of Foreign Studies, Gyeonggi-do, Korea, Republic of |
||
A deep neural network, referred to as DIFFnet, was developed to reconstruct the diffusion parameters from data with reasonable b-value and gradient scheme (gradient direction and the number of gradients). For the generalization, Qmatrix was proposed via the projection and quantization of q-space. DIFFnet was trained by simulated datasets with various b-values and gradient schemes. Two DIFFnets, one for DTI and the other for NODDI were developed. DIFFnet successfully reconstructs the diffusion parameter maps of two in-vivo datasets with different b-values and gradient schemes. |
| 3406 | Providing realistic ground truth and AI-ready data for fiber tractography: The 99 simulated brains dataset | |
| Peter Neher1 and Klaus Maier-Hein1,2,3 | ||
1Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany, 2Medical Faculty, University of Heidelberg, Heidelberg, Germany, 3Pattern Analysis and Learning Group, Heidelberg University Hospital, Heidelberg, Germany |
||
We present our new dataset of 99 simulated brains, suitable for fiber tractography training, validation and beyond. With the proposed approach it was possible to create a large dataset of 792 simulated MR images based on 99 subjects. A large variety of acquisition settings and artifacts could be realized. This dataset is the first large collective of diversely simulated brain-like MRI datasets. We believe that this unique dataset is an important contribution to the ongoing efforts of the tractography community to enable proper validation with a real ground truth and to further enable the training of new machine-learning based approaches. |
| 3407 | A novel in silico phantom for microstructure, tractography and quantitative connectivity estimation | |
| Gabriel Girard1,2,3, Jonathan Rafael-Patino3, Raphael Truffet4, Marco Pizzolato3,5, Emmanuel Caruyer4, and Jean-Philippe Thiran1,2,3 | ||
1University Hospital Center (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland, 2CIBM Center for BioMedical Imaging, Lausanne, Switzerland, 3Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland, 4Univ Rennes, Inria, CNRS, Inserm, IRISA UMR 6074, Empenn ERL U-1228, Rennes, France, 5Technical University of Denmark, Kongens Lyngby, Denmark |
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In this work, we propose a novel phantom obtained from Monte-Carlo simulations of spins dynamics to improve testing and validation of DW-MRI quantitative structural connectivity. The DiSCo (Diffusion-Simulated Connectivity) phantom is composed of 16 regions of interest placed on a sphere of 1 millimeter in diameter, interconnected by 12,196 axon-like tubular fibers ranging from 1.4um to 4.2um in diameter. Its associated connectivity matrix is weighted by their cross-sectional areas. This in silico phantom, with both microscopic and macroscopic complexity, aims at improving the development and the validation of white matter connectivity estimation methods. |
| 3408 | Impact of within-voxel heterogeneity in fibre geometry on spherical deconvolution | |
| Ross Callaghan1, Daniel C Alexander1, Marco Palombo1, and Hui Zhang1 | ||
1Department of Computer Science and Centre for Medical Image Computing, University College London, London, United Kingdom |
||
Axons in white matter have been shown to have varying geometries within a bundle, but what does this mean for spherical deconvolution, which assumes a single diffusion MRI (dMRI) fibre response function (FRF) for all axons within a voxel? We demonstrate, using advanced dMRI simulations, that variable fibre geometry leads to a variable FRF across axons and that a different choice of FRF can lead to large differences in the recovered fibre orientation distribution function (fODF). This finding suggests that assuming a single FRF can lead to misestimation of the fODF, causing further downstream errors in techniques such as tractography. |
| 3409 | A closer look at diffusion and fiber ODFs in a ground truth crossing fiber phantom | |
| Steven H. Baete1,2, Patryk Filipiak1,2, Lee Basler3, Anthony Zuccolotto3, Ying-Chia Lin1,2, Dimitris G. Placantonakis4, Timothy Shepherd1,2, Walter Schneider3, and Fernando E. Boada1,2 | ||
1Center for Advanced Imaging Innovation and Research (CAI2R), NYU School of Medicine, New York, NY, United States, 2Center for Biomedical Imaging, Dept. of Radiology, NYU School of Medicine, New York, NY, United States, 3Psychology Software Tools, Inc., Pittsburgh, PA, United States, 4Department of Neurosurgery, Perlmutter Cancer Center, Neuroscience Institute, Kimmel Center for Stem Cell Biology, NYU School of Medicine, New York, NY, United States |
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High quality diffusion acquisitions are routinely used to study brain connectivity. In each voxel complex intra-voxel fiber crossings may be captured in Orientation Distribution Functions (ODFs). Direct comparison of ODFs calculated with different methods challenging due to a lack of ground truth. Here, we compare different q-space sampling schemes and ODF-reconstructions on a clinical 3T scanner for a known ground truth of crossing Taxons (textile water filled tubes). This comparison illustrates difficulties separating fibers crossing at less than 45° and estimating relative fiber bundle densities using conventional fiber peak identification. Use of more advanced methods is thus recommended. |
| 3410 | Assessment of the effects of cellular properties in tissue on ADC measurements by an experimental study | |
| Xiaodong Li1, Yafei Bai1, Yupeng Liao1, and Sherman Xuegang Xin1 | ||
1South China University of Technology, Guangzhou, China |
||
The apparent diffusion coefficient (ADC) provided by diffusion-weighted magnetic resonance imaging (DW-MRI) has been used clinically for nearly three decades. Some hypotheses have been proposed to explain the change in ADC, including the change in membrane permeability, intracellular volume fraction (IVF), tortuosity of extracellular spaces, and intracellular diffusivity. However, no experimental study has been conducted to quantitatively assess the effects of these parameters on the ADC measurements. Experimental study is helpful to understand the biophysical mechanisms underlying the change in the ADC. Here, we designed a series of multi-parameter phantoms to conduct a quantitative experimental study. |
| 3411 | Normalization of Temperature Effects for Improved Quantitative Prostate Apparent Diffusion Coefficient (ADC) Imaging Across Multiple Sites | |
| Ken-Pin Hwang1, R. Jason Stafford2, Joshua Yung2, and Aradhana M. Venkatesan3 | ||
1The University of Texas M.D. Anderson Cancer Center, Houston, TX, United States, 2Department of Imaging Physics, The University of Texas M.D. Anderson Cancer Center, Houston, TX, United States, 3Department of Abdominal Radiology, The University of Texas M.D. Anderson Cancer Center, Houston, TX, United States |
||
Performing a standardized measurement of ADC requires maintaining a phantom temperature of 0oC. To expand quality assurance of ADC measurement on a network of scanners at room temperatures, a model for temperature dependence was applied as a correction factor. A diffusion phantom was scanned on 1.5T and 3T scanners at four locations using sequence parameters from a prostate protocol. With temperature of the phantom measured at each acquisition, ADC measurements on identically configured scanners exhibited reduced variance when normalized to modeled values. The use of the temperature model is potentially useful in developing a QA program for ADC measurements. |
| 3412 | Measurement of intraventricular temperature in the whole brain using second order motion compensation DTI | |
| Shuhei Shibukawa1, Tetsu Niwa2, Tosiaki Miyati3, Misaki Saito4, Tetsuo Ogino5, Daisuke Yoshimaru6, and Kagayaki Kuroda7 | ||
1Tokai university hospital, Kanagawa, Japan, 2Tokai University School of Medicine, Isehara, Japan, 3Kanazawa University, Kanazawa, Japan, 4Tokai university hospital, Isehara, Japan, 5Philips Japan, Tokyo, Japan, 6RIKEN Center for Brain Science, saitama, Japan, 7Course of Electrical and Electronic Engineering, Graduate School of Engineering, Tokai University, Isehara, Japan |
||
The intraventricular cerebrospinal fluid (CSF) temperature calculated from the diffusion coefficient is affected by the CSF pulsation. Therefore, we investigated the second-order motion compensation DTI (2nd-MC DTI) in consideration of fractional anisotropy (FA) for the CSF to the determination of the intraventricular temperature to improve that accuracy. The measurement of the intraventricular temperature with 2nd-MC DTI showed the least SD and can be more accurately estimated than conventional DTI. |
| 3413 | Temperature and Concentration Dependence of PVP Phantom Diffusion | |
| Ghoncheh Amouzandeh1, Dariya I Malyarenko1, Yuxi Pang1, Brian D Ross1, and Thomas L Chenevert1 | ||
1Radiology, University of Michigan, Ann arbor, MI, United States |
||
This study investigates temperature and concentration dependence of apparent diffusion coefficient (ADC) for aqueous solutions of polyvinylpyrrolidone (PVP). Our objective is to report accurate diffusion values for PVP in the scanner room temperature range. We performed ADC measurements of PVP (0-50% concentration) with K40 polymer moiety at multiple room temperatures while simultaneously measuring internal phantom temperature using an MRI-compatible optical thermometer. To reduce measurement bias, we also performed “gradient calibration” of each physical gradient channel using water ADC at 0oC. Our results are consistent with Arrhenius model for water ADC dependence on temperature and PVP concentration. |
| 3414 | Detection of alterations in water transport across the cell membrane by filter-exchange spectroscopy | |
| Athanasia Kaika1, Geoffrey J. Topping1, Mathias Schillmaier1, and Franz Schilling1 | ||
1Department of Nuclear Medicine, Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Munich, Germany |
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Filter-Exchange Spectroscopy (FEXSY) is performed using a double-diffusion magnetic resonance pulse sequence, which encodes information dependent on transmembrane water exchange. Permeabilized baker’s yeast cells were examined with a FEXSY sequence and trypan blue staining. Upon permeabilization with isopropanol, TritonX-100 and sonication, the AXR value of yeast cells increased and trypan blue staining verified the membrane permeabilization. In presence of low isopropanol concentration, a progressive increase of the AXR value was observed, which stopped after isopropanol removal. No differences were detected in the trypan blue staining over time, in presence and in absence of isopropanol. |
| 3415 | Cumulant expansions for measuring restricted diffusion and water exchange | |
| Arthur Chakwizira1, Filip Szczepankiewicz2, Linda Knutsson1,3, Pia Sundgren2,4,5,6, and Markus Nilsson2 | ||
1Department of Medical Radiation Physics, Lund University, Lund, Sweden, 2Department of Diagnostic Radiology, Lund University, Lund, Sweden, 3Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States, 4Lund University Bioimaging Center, Lund University, Lund, Sweden, 5Department for Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden, 6Department of Radiology, University of Michigan, Ann Arbor, MI, United States |
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Cell sizes and membrane permeability can be inferred by probing time–dependent diffusion due to restricted diffusion and water exchange. However, restriction and exchange have opposing effects on the diffusion weighted signal when varying the diffusion time, making it a challenge to disentangle the two phenomena. We explore the applicability of a unified theoretical framework that includes size and exchange in living cells by applying it to healthy and diseased human brain in vivo as well as a yeast phantom. Results highlight the potential of the framework for differentiating between healthy and abnormal tissue. |
| 3416 | Filtered water diffusion pore imaging on a 14.1T spectrometer using strong gradients and capillary phantoms in the presence of extraporal fluid | |
| Dominik Ludwig1,2, Frederik B. Laun3, Karel D. Klika4, Mark E. Ladd1,2,5, Peter Bachert1,2, and Tristan A. Kuder1 | ||
1Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany, 2Faculty of Physics and Astronomy, Heidelberg University, Heidelberg, Germany, 3Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany, 4Molecular Structure Analysis, German Cancer Research Center (DKFZ), Heidelberg, Germany, 5Faculty of Medicine, Heidelberg University, Heidelberg, Germany |
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Diffusion pore imaging (DPI) can be used to retrieve the pore space function of arbitrary closed pores. In this study, we show that DPI of glass capillaries is possible even under difficult experimental conditions. By separating the long gradient into a CPMG-like gradient echo train, matching the magnetic susceptibility and adding an additional filter diffusion weighting, it was possible to acquire diffraction patterns of glass capillaries that were placed orthogonally to the main magnetic field. Furthermore, the feasibility of doing DPI in the presence extraporal water using our filtered approach was demonstrated. |
| 3417 | Lamellar liquid crystal phantom for validating MRI methods to distinguish oblate and prolate diffusion tensors on whole-body scanners | |
| Hong Jiang1, João Pedro de Almeida Martins1, Dan Lundberg2, Chantal M. W. Tax3, and Daniel Topgaard1 | ||
1Physical Chemistry, Lund University, Lund, Sweden, 2CR Competence AB, Lund, Sweden, 3Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom |
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Conventional diffusion MRI can yield planar tensors in tissues such as epidermoid cysts, comprising tightly packed planar cells, and brain tissue "sheet" structures with populations of axonal fibers crossing at nearly right angles. The two cases may be resolved by multidimensional diffusion encoding as previously demonstrated with various liquid crystal phantoms on preclinical equipment. For method validation also on whole-body scanners, we here develop a lamellar liquid crystal phantom giving microscopically planar diffusion tensors and having sufficiently long T2 for use with single-shot EPI signal read-out. |
| 3418 | Microstructure size-distribution estimations with smooth and sharp non-uniform oscillating gradient spin-echo modulations | |
| Melisa Lucía Giménez1,2, Pablo Jiménez1,2, Leandro Andrés Pedraza Pérez1,2, Diana Betancourth2, Analía Zwick2,3,4, and Gonzalo Agustín Álvarez1,2,3,4 | ||
1Departamento de Física Médica, Instituto Balseiro, Universidad Nacional de Cuyo, CNEA, San Carlos de Bariloche, Argentina, 2Centro Atómico Bariloche, CNEA, San Carlos de Bariloche, Argentina, 3Consejo Nacional de Investigaciones Científicas y Técnicas de Argentina (CONICET), San Carlos de Bariloche, Argentina, 4Instituto de Nanociencia y Nanotecnología, CNEA,CONICET, San Carlos de Bariloche, Argentina |
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Morphological changes related to neurological diseases occur at micrometer scales. Obtaining such information non-invasively opens new paradigms for clinical diagnosis. We use the Non-uniform Oscillating Gradient Spin-Echo sequence to estimate microstructure size-distributions with high sensitivity based on probing a signal “decay-shift” rather than a signal decay-rate. The “decay-shift” arises with sharp gradient modulations. As fast ramps are prohibitive in clinical diagnosis, we evaluate the method using sharp and smooth gradient modulations. We show using simulations and proof-of-principle experiments with phantoms that mimic axon-bundles, that optimal estimation of the underlying microstructure-size distribution is obtained either using sharp or smooth modulations. |
| 3419 | Estimating the pore size in a biomimetic phantom using free gradient waveforms | |
| Maryam Afzali1, Tomasz Pieciak2,3, Lars Mueller1, Andre Doring1, Dan Ma4, Marco Pizzolato5,6, and Derek K Jones1 | ||
1Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom, 2AGH University of Science and Technology, Kraków, Poland, 3LPI, ETSI Telecomunicación, Universidad de Valladolid,, Valladolid, Spain, 4Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States, 5Department of Applied Mathematics and Computer Science, Technical University of Denmark,, Kongens Lyngby, Denmark, 6Signal Processing Lab (LTS5), École polytechnique fédérale de Lausanne (EPFL), Lausanne, Swaziland |
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Diffusion magnetic resonance imaging is a non-invasive tool to probe the microstructural features of a sample. One of these properties is the restriction size that can be measured by changing the diffusion time or alternatively changing the frequency content of the gradient waveform. B-tensor encoding was proposed recently to disentangle microstructural features of the tissue. Here we use the combination of linear, planar, and spherical tensor encoding to estimate the pore size in a biomimetic phantom, for which ground truth size estimates were available. The results show a good agreement between the estimated sizes and ground truth values. |
| 3420 | A New Phantom to Study a Restricted Diffusion Introduction | |
| Sergey Magnitsky1 | ||
1CHOP, Philadelphia, PA, United States |
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Diffusion-weighted imaging is instrumental in the evaluation of bone quality. However, an interpretation of the data obtained from porous material is complex due to the effects of restricted diffusion. In this study, we are presenting a new restriction diffusion phantom, which was developed for an optimization of acquisition protocols for bone studies. The phantom consists of microscopic-slides separated by glass spheres (~10 μm). The space between slides was filled with water. NMR data were collected and diffusion-properties of the phantom were documented. The proposed phantom can be easily replicated in any laboratory and will assist in investigations of restriction diffusion. |
| 3421 | Effect of the training set on supervised-learning parameter estimation: Application to the Standard Model of diffusion in white matter | |
| Ying Liao1, Santiago Coelho1, Jelle Veraart1, Els Fieremans1, and Dmitry S. Novikov1 | ||
1Radiology, NYU School of Medicine, New York, NY, United States |
||
Maximum likelihood estimation is challenging in multicompartmental models due to the degeneracy of the optimization landscape. As a result, machine learning (ML) methods are often applied for parameter estimation, interpolating the mapping of measurements to model parameters. Such mapping can essentially depend on the training set (prior), decreasing the sensitivity to the measurements, and yielding artificially “clean” maps. Here we quantify the effect of the training set on the Standard Model of diffusion in white matter as function of signal-to-noise ratio, in simulations and in vivo. |
| 3422 | Feasibility of white matter Standard Model parameter estimation in clinical settings | |
| Santiago Coelho1, Steven Baete1, Gregory Lemberskiy1, Benjamin Ades-aron1, Jelle Veraart1, Dmitry S. Novikov1, and Els Fieremans1 | ||
1Radiology, NYU School of Medicine, New York, NY, United States |
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Robust parameter estimation of the Standard Model (SM) for diffusion in white matter has been elusive due to intrinsic model degeneracies and insufficient measurements. To design optimal scanner-specific protocols, we couple multidimensional protocol optimization for estimation of microstructural tissue properties in 15 minute acquisitions on clinical scanners with varying gradient performance. We show reproducible scan-rescan results and assess inter-scanner variability ranging from 1 to 8% depending on parameters. Results suggest that combining denoising, protocol optimization, and robust parameter estimation may enable quantitative microstructure mapping in clinical settings. |
| 3423 | Estimating cortical soma and neurite densities from diffusion MRI measures using a machine learning approach | |
| Tianjia Zhu1,2, Minhui Ouyang1, Nikou Lei3, David Wolk4, Paul Yushkevich5, and Hao Huang1,5 | ||
1Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, United States, 2Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, United States, 3Department of Physics, University of Washington Seattle, Seattle, WA, United States, 4Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States, 5Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States |
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Diffusion MRI (dMRI) has ushered in a new era in which conventional brain cortical histological measures such as soma and neurite densities may be assessed noninvasively through advanced dMRI. However, analytical dMRI microstructural models are restricted by the model assumptions and lack of validation from quantitative histology data. Individual dMRI parameters characterize only limited microstructural information. By leveraging a variety of dMRI-based parameters delineating cortical microstructure from multiple aspects, we established a machine learning based method accurately estimating cortical soma and neurite densities in the cortex, paving the way for data-driven noninvasive virtual histology for potential applications to Alzheimer’s diseases. |
| 3424 | Mapping apparent soma and neurite density in the in-vivo mouse brain using SANDI | |
| Andrada Ianus1, Francisca F. Fernandes1, Joana Carvalho1, Cristina Chavarrias1, Marco Palombo2, and Noam Shemesh1 | ||
1Champalimaud Centre for the Unknown, Lisbon, Portugal, 2University College London, London, United Kingdom |
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Measuring micro-architectural features involving cell body morphologies is emerging as a frontier of diffusion MRI. This work aimed to map the apparent soma size and density and neurite density via the SANDI methodology in the mouse brain in-vivo at 9.4T. Our results show consistent parameters values between N=3 animals in both gray and white matter ROIs. Moreover, we have also compared the effects of using different number of shells and maximum b-values in the SANDI analysis. Our work augurs well for future investigations in animal models of plasticity and disease. |
| 3425 | Not all voxels are created equal: reducing estimation bias in regional NODDI metrics using tissue-weighted mean | |
| Christopher S Parker1, Thomas Veale2, Martina Bocchetta2, Catherine F Slattery2, Nick Fox2, Jonathan M Schott2, Dave M Cash1,2, and Hui Zhang1 | ||
1Centre for Medical Image Computing, Department of Computer Science, UCL, London, United Kingdom, 2Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square, Institute of Neurology, UCL, London, United Kingdom |
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Region-of-interest (ROI) metrics are typically computed as a mean over ROI voxels. However, for some NODDI metrics, this approach produces biased estimates in the presence of cerebrospinal fluid partial volume. We address this by introducing a tissue-weighted alternative. We compare the proposed mean to its conventional counterpart for periventricular and non-periventricular ROIs in healthy subjects and patients with young onset Alzheimer’s disease (YOAD). Results show the conventional mean overestimates orientation dispersion index and inflates inter-subject variation, particularly for periventricular ROIs and the YOAD cohort. This technique may improve detection of true regional effects in future group studies of neurodegenerative diseases. |
| 3426 | Relevance of NODDI to Characterise In Vivo the Microstructural Abnormalities of Multiple Sclerosis Cortex and Cortical Lesions: A 3T Study | |
| Elisabetta Pagani1, Paolo Preziosa1,2, Raffaello Bonacchi1,2, Laura Cacciaguerra1,2,3, Massimo Filippi1,2,3,4,5, and Maria A. Rocca1,2,3 | ||
1Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy, 2Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy, 3Vita-Salute San Raffaele Unversity, Milan, Italy, 4Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy, 5Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy |
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In multiple sclerosis (MS), cortical damage is a relevant predictor of clinical disability. We applied Neurite orientation dispersion and density imaging (NODDI) to characterize microstructure of normal-appearing cortex (NA-cortex) and cortical lesions (CLs) and their relations with disease clinical phenotypes and disability. We found that a significant neurite loss occurs in MS NA-cortex, being more severe with longer disease duration, more severe disability and progressive MS. CLs show a further reduction of neurite density, together with an increased extracellular space, possibly due to inflammation and gliosis, and a reduced dispersion suggestive of increased tissue coherence and simplification of neurite complexity. |
| 3427 | Deep Learner estimated isotropic volume fraction enables reliable single-shell NODDI reconstruction | |
| Abrar Faiyaz1, Marvin M Doyley1,2,3, Giovanni Schifitto2,4, Jianhui Zhong2,3,5, and Md Nasir Uddin4 | ||
1Department of Electrical and Computer Engineering, University of Rochester, Rochester, NY, United States, 2Department of Imaging Sciences, University of Rochester, Rochester, NY, United States, 3Department of Biomedical Engineering, University of Rochester, Rochester, NY, United States, 4Department of Neurology, University of Rochester, Rochester, NY, United States, 5Department of Physics and Astronomy, University of Rochester, Rochester, NY, United States |
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The study explores the possibility to create neurite orientation dispersion and density imaging (NODDI) parameter maps with single-shell diffusion MRI data, using isotropic volume fraction (fISO) as prior. Proposed dictionary based deep learning prior NODDI (DLpN) framework leverages fISO estimation with a diffusion imaging scalar and T2 weighted non-diffusion signal. fISO estimation was validated in simulation and in-vivo. DLpN derived NDI and ODI maps for single-shell protocols are comparable with original multi-shell NODDI (error <5%) and may allow NODDI evaluation of retrospective brain studies on single-shell diffusion MRI data by multi-shell scanning of two subjects for DictNet fISO training. |
| 3428 | B-value influence on IVIM MRI for juvenile idiopathic arthritis in the knee | |
| Kilian Stumpf1, Anna-Katinka Bracher2, Thomas Hüfken1, Britta Huch2, Meinrad Beer2, Henning Neubauer2, and Volker Rasche1 | ||
1Department of Internal Medicine II, Ulm University Medical Center, Ulm, Germany, 2Department of Diagnostic and Interventional Radiology, Ulm University Medical Center, Ulm, Germany |
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Intravoxel incoherent motion imaging allows the quantification of diffusion and pseudo-perfusion in tissues and can be used as an alternative to conventional T1-weighted scans that require the use of contrast agents. Its benefits for diagnosing juvenile idiopathic arthritis(JIA) in the knee has previously be demonstrated, but usually requires multi-b-value DWI scans with long scan times. In this work we investigate the influence of different b-value combinations on the calculated diffusion and perfusion fraction values and explore the possibility for IVIM MRI of JIA with fewer b-values and shorter scan times. |
| 3429 | Fast and accurate quantification of intra-voxel incoherent motion (IVIM) with spherical-tensor-encoded diffusion MRI | |
| Alberto De Luca1,2, Geert-Jan Biessels1, Ofer Pasternak3, and Chantal MW Tax4,5 | ||
1Department of Neurology, University Medical Center Utrecht, Utrecht, Netherlands, 2PROVIDI Lab, Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands, 3Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States, 4Cardiff University Brain Research, Imaging Centre (CUBRIC), University of Cardiff, Cardiff, United Kingdom, 5Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands |
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Diffusion MRI scans sensitive to intra-voxel incoherent motion (IVIM) are increasingly being applied to derive properties of capillary blood pseudo-diffusion in-vivo. A robust quantification of pseudo-diffusion measures requires the acquisition of diffusion MRI with multiple weightings and directions, which is time-consuming. Here, we investigate whether the isotropic averaging of spherical tensor diffusion encoding (STE) can improve IVIM estimates and shorten the acquisition time. Our simulations and in-vivo data show that STE can substantially shorten the acquisition time required to robustly quantify pseudo-diffusion while also removing a previously unreported bias in voxels containing complex white matter fiber configurations. |
| 3430 | Effect of the Signal-to-noise Ratio on the Optimal Model Mapping for Intravoxel Incoherent Motion MRI | |
| Yen-Peng Liao1,2, Shin-ichi Urayama1,2, Tadashi Isa1,2,3, and Hidenao Fukuyama2,4 | ||
1Department of Neuroscience, Kyoto University Graduate School of Medicine, Kyoto, Japan, 2Human Brain Research Center, Kyoto University Graduate School of Medicine, Kyoto, Japan, 3Institute for the Advanced Study of Human Biology (ASHBi), Kyoto University, Kyoto, Japan, 4Yasu City Hospital, Yasu, Japan |
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To improve the uncertainties caused by the inappropriate diffusion model fitting in the IVIM-MRI, an optimal model mapping method has been proposed and demonstrated its usefulness. Here, we investigated the effect of the SNR in the method. Six different SNR data sets, derived by changing the numbers of average (NA) of six sets of DWI volumes, were analyzed. Then, the resultant maps reached a steady-state when the NA is four or higher. This study revealed that further investigations on b-value distribution optimization and denoising are necessary to obtain such high SNR data within practical scan time. |
| 3431 | Gaussian Mixture for Peak Identification in Non-Negative Least Squares Fitting of the IVIM Signal | |
| Lucas M da Costa1, Bruno Hebling Vieira1, Renata Ferranti Leoni1, and Andre Monteiro Paschoal1,2 | ||
1InBrain Lab - University of Sao Paulo, Ribeirao Preto, Brazil, 2LIM44, Instituto e Departamento de Radiologia, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil |
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The analysis of the Intravoxel Incoherent Motion (IVIM) signal can be performed with the Non-Negative Least Squares (NNLS) method. It allows detecting an indeterminate number of peaks associated with the multiple exponentials that compose the IVIM signal. Thus, it becomes essential to identify and classify these peaks. We performed a new method to analyze the NNLS spectrum applying the Gaussian Mixture. We obtained pseudo-diffusion maps with better contrast to visualize gliomas. Gaussian Mixture seems to replace the traditional peak search and classification algorithms, opening up possibilities to explore the NNLS spectrum. |
| 3432 | Model-based reconstruction for IVIM and combined IVIM-DTI fitting: Initial experience | |
| Susanne Rauh1, Oliver Maier2, Oliver Gurney-Champion3, Melissa Hooijmans3, Rudolf Stollberger2,4, Aart Nederveen3, and Gustav Strijkers1 | ||
1Department of Biomedical Engineering and Physics, Amsterdam UMC, location AMC, Amsterdam, Netherlands, 2Institute of Medical Engineering, Graz University of Technology, Graz, Austria, 3Department of Radiology and Nuclear Medicine, Amsterdam UMC, location AMC, Amsterdam, Netherlands, 4BioTechMed-Graz, Graz, Austria |
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Model-based reconstruction can overcome many short-comings of IVIM and DTI by accelerating the acquisition, suppressing systematic errors from Rician noise and improving SNR. In this study we assess the feasibility of model-based reconstruction to obtain IVIM and combined IVIM-DTI parameter maps in the liver and kidneys in healthy volunteers. Results were compared to a conventional IVIM and IVIM-DTI least-squares fitting. Model-based reconstructions produced maps with less artifacts in liver and more details in the kidneys as compared to those from conventional fitting. Mean parameter values were similar for both methods. |
| 3433 | Physically Motivated Deep-Neural Networks of the Intravoxel Incoherent Motion Signal Decay Model for Quantitative Diffusion-Weighted MRI | |
| Shira Nemirovsky-Rotman1, Elad Rotman1, Onur Afacan2, Sila Kurugol2, Simon Warfield2, and Moti Freiman1 | ||
1Biomedical Engineering, Technion, Haifa, Israel, 2Boston's Children's Hospital, Harvard Medical School, Boston, MA, United States |
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Quantitative Diffusion-Weighted MRI with the Intra-Voxel Incoherent Motion (IVIM) model shows potential to produce quantitative biomarkers for multiple clinical applications. Recently, deep-learning (DL) models were proposed for the estimation of the IVIM model parameters from DW-MRI data. While the DL models produce more accurate parameter estimates compared to classical methods, their capability to generalize the IVIM model to different acquisition protocols is very limited. For that end, we introduce a physically motivated DL model, by incorporating the acquisition protocol into the network architecture. Our approach provides a DL-based method for IVIM parameter estimates that is agnostic to the acquisition protocol. |
| 3434 | Self-supervised IVIM DWI parameter estimation with a physics based forward model | |
| Serge Vasylechko1,2, Simon K. Warfield1,2, Onur Afacan1,2, and Sila Kurugol1,2 | ||
1Computational Radiology Laboratory, Boston Children's Hospital, Boston, MA, United States, 2Harvard Medical School, Boston, MA, United States |
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The goal of this study was to assess the robustness and repeatability of intravoxel incoherent motion model (IVIM) parameter estimation for the diffusion weighted MRI in the abdominal organs under the constraints of noisy diffusion signal using a novel neural network training method. The method is based on the principle of a physics guided self-supervised neural network that does not require supervision for training. Such approach is beneficial in conditions where the reference methods are not available, or are not robust enough to provide good supervision. This work is targeting evaluations towards accelerated IVIM DWI scanning which exhibit low SNR. |
| 3435 | Intravoxel Incoherent Motion Reconstruction with Multi-Orientation Acquisition using Three b-Values | |
| Sam Sharifzadeh Javidi1 and Hamidreza Saligheh Rad1,2 | ||
1Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran (Islamic Republic of), 2Quantitative MR Imaging and Spectroscopy Group, Research Center for Molecular and Cellular Imaging, Tehran, Iran (Islamic Republic of) |
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The IVIM model is capable of extracting functional and structural information simultaneously without the injection of contrast agents. The main limitation of this technique is the inaccuracy of the output of this model in low SNR regimes. In this study, we proposed the use of twelve diffusion imaging orientations and three b-values instead of three orthogonal DW imaging and several b-values. Simulation and in-vivo results showed that the proposed method outperforms the conventional IVIM reconstruction method. Improved quality and reproducibility can make this method more practical and attractive in clinical settings. |
| 3436 | Time-dependent and TE-dependent Diffusivity in Human Brain using Multi-TE Oscillating Gradient Spin Echo in High Gradient 3.0T MRI (MAGNUS) | |
| Ante Zhu1, Luca Marinelli1, and Thomas K.F. Foo1 | ||
1GE Global Research, Niskayuna, NY, United States |
||
Oscillating gradient spin echo (OGSE) diffusion imaging achieves a short diffusion time and has been performed to assess tissue characteristics at short length scale, including the correlation length of the brain tissues which may provide information on axonal beading and swelling in disease. Time-dependent diffusivity has been measured from OGSE acquisition at a fixed TE in a high-performance head-only high-gradient 3.0T MRI scanner (MAGNUS). In this study, we characterized time-dependent diffusivity at varying frequencies (0~80 Hz) and TEs (72~158 ms) using multi-TE OGSE acquisition in healthy volunteers. Preliminary results showed increased mean/parallel diffusivities in corpus callosum at shorter TE. |
| 3437 | A novel clinically viable method to quantify T2 of intra and extra axonal compartmental tissue properties | |
| Sudhir Kumar Pathak1, Vishwesh Nath2, B V Rathish Kumar3, and Walter Schneider1 | ||
1Psychology, University of Pittsburgh, Pittsburgh, PA, United States, 2Nvidia, Bethesda, MD, United States, 3Mathematics, Indian Institute of Technology Kanpur, Kanpur, India |
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Diffusion MRI based microstructural imaging is used to estimate voxel wise intra/extra-cellular volume fraction and compartment diffusivities. Previously proposed techniques like NODDI, SMT models are used to estimate intra/extra-axonal volume fraction, axial and radial diffusivity for each voxel. TEdDI is a framework to estimate intra/extra-axonal T2 in human brain. The proposed TEdDI model requires multiple sets of diffusion dataset varies with echo time. In this study we are proposing SMT based formulation to estimate intra/extra-axonalT2. We also used this formulation to design numerical algorithm that approximate T2 and other parameters for a typical multi-shell diffusion acquisition. |
| 3438 | Nonparametric 5D D-R2 distribution imaging with single-shot EPI at 21.1 T: Initial results for in vivo rat brain | |
| Jens T Rosenberg1, Samuel Colles Grant1,2, and Daniel Topgaard3 | ||
1National High Magnetic Field Laboratory, Florida State University, Tallahassee, FL, United States, 2Chemical and Biomedical Engineering, FAMU-FSU College of Engineering, Tallahassee, FL, United States, 3Physical Chemistry, Lund University, Lund, Sweden |
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In vivo diffusion MRI is by default performed using single-shot EPI with TE>50 ms and associated signal loss from transverse relaxation. The individual benefits of the current trends of increasing B0 to boost SNR and employing more advanced signal preparation schemes to improve the specificity for selected microstructural properties eventually may be cancelled by increases in relaxation rates at high B0 and TE with advanced encoding. Here, we make initial attempts to translate state-of-the-art diffusion-relaxation correlation methods to 21.1T to identify hurdles that need to be overcome to fulfill the promises of both high SNR and readily interpretable microstructural information. |
| 3439 | MR Fingerprinting with B-tensor encoding scheme for simultaneous measure of relaxation and microstructure diffusion | |
| Maryam Afzali1, Lars Mueller1, Ken Sakaie2, Siyuan Hu3, Yong Chen4, Mark Griswold4, Derek K Jones1, and Dan Ma3 | ||
1Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom, 2Imaging Institute, Cleveland Clinic, Cleveland, OH, United States, 3Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States, 4Radiology, Case Western Reserve University, Cleveland, OH, United States |
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Diffusion magnetic resonance imaging provides information about microstructural features of a sample. Relaxometry on the other hand is sensitive to the biochemical environment of the underlying microstructure. Recent studies show that using conventional Stejskal-Tanner experiment, separating compartmental features is challenging and therefore b-tensor encoding and diffusion-relaxometry were proposed to mitigate this challenge. Magnetic resonance fingerprinting (MRF) can quantify multiple tissue parameters in one scan. Here, we implement multi-dimensional MR Fingerprinting scan with linear and spherical tensor encoding (LTE, and STE) and show the feasibility of estimating $$$T_1,\;\rm{and}\;T_2$$$ relaxation times and diffusivity on NIST, microstructure phantom and in vivo brain scans. |
| 3440 | Multicomponent Diffusion Analysis using L1-norm Regularized NNLS for an Accurate and Robust Detection of Alternations in Spinal Cord | |
| Jin Gao1,2, Weiguo Li2,3, Richard Magin3, and Danilo Erricolo1,3 | ||
1Department of Electrical and Computer Engineering, University of Illinois at Chicago, Chicago, IL, United States, 2Research Resources Center, University of Illinois at Chicago, Chicago, IL, United States, 3Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, United States |
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Multiple components analysis of nuclear magnetic resonance (MR) relaxation data using L2-norm regularized non-negative least squares (NNLS) method has been widely used in myelin imaging for neurological diseases. When this analysis is applied to diffusion-weighted MR imaging to investigate water diffusion properties of biological tissues, noise corruption becomes a major problem which affects the accuracy and robustness of results. In this study, a L1-norm regularized method was developed to process diffusion-weighted MRI data from spinal cords of amyotrophic lateral sclerosis affected mice. |
| 3637 | Recovering almost everything that diffusion could reveal | |
| Evren Özarslan1,2 | ||
1Department of Biomedical Engineering, Linköping University, Linköping, Sweden, 2Center for Image Science and Visualization, Linköping University, Linköping, Sweden |
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Diffusion magnetic resonance has been employed for determining the distribution of net displacements (ensemble average propagator), moments and correlations of net displacements, and the steady-state distribution of magnetized particles. All such quantities are accessible via the diffusion propagator, which characterizes the diffusion process fully. Here, a novel diffusion encoding and data analysis framework is introduced with which the diffusion propagator can be recovered. |
| 3638 | Validation of between-bundle differences and within-bundle continuity of microstructural indices in ex vivo human brain tissue | |
| Robert Jones1, Chiara Maffei1, Qiuyun Fan1, Jean Augustinack1, Barbara Wichtmann2, Aapo Nummenmaa1, Susie Huang1, and Anastasia Yendiki1 | ||
1Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States, 2Department of Radiology, University Hospital Bonn, Bonn, Germany, Bonn, Germany |
||
We take advantage of the high spatial resolution that is feasible ex vivo on a preclinical 9.4T system to investigate between-bundle differences and within-bundle continuity of microstructural indices. In a human brain sample that has also undergone optical imaging to obtain direct measurements of axonal orientations, we identify regions occupied by motor fibers or association fibers. We collect diffusion-weighted images with two diffusion times and eight q-shells and use them to estimate the parallel and perpendicular diffusion coefficient in each fiber bundle. We show that the diffusion coefficients vary smoothly along each bundle, and have different profiles between bundles. |
| 3639 | Oscillating Gradient Spin Echo-Based Time-dependent Diffusivity Reflects Regional Microstructure Differences in Human White Matter | |
| Ante Zhu1, J. Kevin DeMarco2,3, Robert Y. Shih2,3, Radhika Madhavan1, Tim Sprenger4, Chitresh Bhushan1, Maureen Hood2,3, Luca Marinelli1, Vincent B. Ho2,3, and Thomas K.F. Foo1 | ||
1GE Global Research, Niskayuna, NY, United States, 2Uniformed Services University of the Health Sciences, Bethesda, MD, United States, 3Walter Reed National Military Medical Center, Bethesda, MD, United States, 4GE Healthcare, Stockholm, Sweden |
||
Diffusivity measurements of the human brain have been shown to increase at short diffusion time by using oscillating gradient spin echo (OGSE). The time-dependent diffusivity averaged in large white matter parcels has been measured to assess microstructure characteristics. In this study, we assessed time-dependent diffusivity in finer white matter parcels to study the regional microstructure differences. In four healthy volunteers, we consistently observed higher parallel diffusivity values and higher increasing rate over OGSE frequencies in two sub-parcels of the genu and two of the splenium in the corpus callosum, compared to other regions, indicating regional microstructure differences of the brain. |
| 3640 | A tale of two frequencies: optimizing oscillating gradients for frequency dependent differential kurtosis mapping | |
| Kevin B Borsos1,2, Desmond HY Tse2, Paul I Dubovan1,2, and Corey A Baron1,2,3 | ||
1Department of Medical Biophysics, Western University, London, ON, Canada, 2Centre for Functional and Metabolic Mapping, Western University, London, ON, Canada, 3Robarts Research Institute, Western University, London, ON, Canada |
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Frequency dependent diffusion kurtosis has historically been difficult to measure with oscillating gradient spin echo (OGSE) sequences and even more so without the use of gradient insert coils. Here we present a new OGSE gradient waveform and determine the optimal frequency to observe kurtosis differences between PGSE and OGSE acquisitions using a conventional gradient system. Using this method we present in vivo differential kurtosis maps based on the frequency dependence. |
| 3641 | When Averaging Only Gets You So Far: Repulsion and Peanut Squashing in Diffusion Tensor MRI | |
| Samuel Bryce Jones1, Emre Kopanoglu2, Chantal Tax2, and Derek Jones2 | ||
1Radyr Comprehensive School, Cardiff, United Kingdom, 2CUBRIC, School of Psychology, Cardiff, United Kingdom |
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This work asks a very simple but important question: To what extent can we recover lost SNR by signal averaging in a standard diffusion tensor MRI experiment? Based on the theory that if SNR of a signal is reduced by a factor (1/m), then m2 signal averages will recover that SNR, the diffusion MRI literature often assumes that averaging is the 'magic bullet'. Here, using Monte Carlo simulations, we show that this only true to a certain extent and, despite averaging, low SNR data results in biased DTI estimates. |
| 3642 | Computing the Orientational-Average of Diffusion-Weighted MRI Signals: A Comparison of Different Techniques | |
| Maryam Afzali1, Hans Knutsson2,3, Evren Özarslan2,3,4, and Derek K Jones1,5 | ||
1Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom, 2Department of Biomedical Engineering, Linköping University, Linköping, Sweden, 3Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden, 4These authors share last authorship, Linköping, Sweden, 5These authors share last authorship, Cardiff, United Kingdom |
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Numerous applications in diffusion MRI involve computing the orientationally-averaged diffusion-weighted signal. Most approaches assume that the gradient vectors are uniformly distributed on a sphere, computing the orientationally-averaged signal through arithmetic averaging. One challenge is that not all acquisition schemes have gradient vectors distributed over perfect spheres. Alternative averaging methods include: weighted signal averaging; spherical harmonic; and Mean Apparent Propagator MRI (MAP-MRI). Here, these methods are compared under different signal-to-noise (SNR) realizations. With dense and isotropically-distributed sampling, all methods give comparable results. As the SNR and number of data points are reduced, MAP-MRI-based approaches give pronounced improvements over the other methods. |
| 3643 | Towards a computational framework for task-driven experimental design | |
| Sean C Epstein1, Timothy J.P. Bray2, Margaret A. Hall-Craggs2, and Hui Zhang1 | ||
1Department of Computer Science & Centre for Medical Image Computing, University College London, London, United Kingdom, 2Centre for Medical Imaging, University College London, London, United Kingdom |
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We present a novel computational method for quantitative assessment of experimental design choices for diffusion-weighted imaging (DWI). This approach is motivated by the observation that real-world tasks (e.g. clinical classification) are assessed by metrics (e.g. AUC) that depend non-trivially on the accuracy and precision of DWI-derived parameters. The proposed method enables, for the first time, the assessment of such metrics in the course of computational experimental design. Evaluation with clinical datasets demonstrates its ability to accurately predict real-world task performance for a range of experimental designs. Illustrative use cases are presented to demonstrate its advantages over existing computational approaches. |
| 3644 | Multi-component diffusion technique acquisition protocol optimization for different microstructure models | |
| Tommaso Ciceri1, Alberto De Luca2,3, Filippo Arrigoni1,4, and Denis Peruzzo1 | ||
1NeuroImaging Unit, Scientific Institute IRCCS Eugenio Medea, Bosisio Parini, Italy, 2Neurology Department, UMC Utrecht, Utrecht, Netherlands, 3PROVIDI Lab, Image Sciences Institute UMC Utrecht, Utrecht, Netherlands, 4Radiology Unit, Fatebenefratelli Hospital, Milan, Italy |
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Complementary aspects of the tissue microstructure can be addressed using different models to quantify diffusion MRI. However, there is no consensus on a common acquisition scheme within a clinical feasible time to support the quantification of multiple models. We acquired a large dataset with multiple b-values and directions, and recursively subsampled it to identify the minimum acquisition scheme (MAS) for each model. Finally, we investigated the impact of the MAS on the parameter estimates in the main fiber bundles of the brain. This work supports the transition of advanced analyses to the clinical practice. |
| 3645 | Optimizing DWI b-value Sampling for Accurate Metabolic and Cytometric Parameter Extraction: Activity MRI [aMRI] | |
| Xin Li1, Eric M. Baker1, Brendan Moloney1, Cory Wyatt1, Eric Baetscher1, Erin W. Gilbert2, Charles S. Springer1, Alexander R. Guimaraes1,3, and William D. Rooney1 | ||
1Advanced Imaging Research Center, Oregon Health & Science University, Portland, OR, United States, 2Surgery, Oregon Health & Science University, Portland, OR, United States, 3Diagnostic Radiology, Oregon Health & Science University, Portland, OR, United States |
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The optimal data acquisition strategy for accurate metabolic and cytometric parameter extraction using a digital DWI library is investigated using simulations under the constant data-acquisition time (same number of b-values) constraint. Base on DWI data from pancreatic tail tissue and using a seven b-value approach, the optimal maximum b-value is found to be data signal-to-noise ratio dependent, and generally should be below 3,000 s/mm2. In addition, evenly-spaced b-values are generally within the optimal b-spacing range. |
| 3646 | Data driven algorithm for multicomponent T2 analysis based on identification of spatially global sub-voxel features | |
| Noam Omer1, Neta Stern1, Tamar Blumenfeld-Katzir1, Meirav Galun2, and Noam Ben-Eliezer1,3,4,5,6 | ||
1Department of Biomedical Engineering, Tel-Aviv University, Tel-Aviv, Israel, 2Department of Computer Science and Applied Mathematics, Weitzman institute of science, Rehovot, Israel, 3Department of Orthopedics, Shamir Medical Center, Zerifin, Israel, 4Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel, 5Sagol School of Neuroscience, Tel-Aviv University, Tel-Aviv, Israel, 6Center for Advanced Imaging Innovation and Research (CAI2R), New-York University Langone Medical Center, New York, NY, United States |
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Multicomponent T2 analysis (mcT2) yields a voxel-wise distribution of T2 values, which can be used to estimate sub-voxel information such as myelin content. Producing such data, however, remains challenging due to the large ambiguity in the T2 space. We present a data-driven approach for mcT2 analysis, which learns the anatomy in question and identifies microscopic tissue-specific features as a preprocessing step. It then utilizes them for analyzing each voxel locally using a designated optimization scheme. Experiments in human brain data show reproducible myelin content estimations at clinical settings without any prior assumptions. |
| 3647 | Ultra-strong gradient diffusion MRI at 7T with a head insert | |
| Chantal Tax1,2, Edwin Versteeg1, Dennis J.W. Klomp1, Martijn F. Froeling1, Alberto de Luca1, and Jeroen C.W. Siero1,3 | ||
1University Medical Center Utrecht, Utrecht, Netherlands, 2CUBRIC, Cardiff University, Cardiff, United Kingdom, 3Spinoza Centre for Neuroimaging Amsterdam, Amsterdam, Netherlands |
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Diffusion weighting is achieved by the application of external field gradients typically for tens of milliseconds, during which the signal substantially decays due to inherent T2 relaxation. This work focuses on the benefits of strong gradients - here provided by a gradient head insert - for high SNR and short TE diffusion imaging at 7T. Proof-of-principle images show that a short TE (21 ms) at a b-value of 1000 s/mm2 is achievable at 7T using an EPI-readout. |
| 3648 | Brain microstructure at 1.5mm resolution via RMT reconstruction on a high-slew rate MAGNUS system | |
| Gregory Lemberskiy1, Santiago Coelho1, Thomas K.F. Foo2, Radhika Madhavan2, Luca Marinelli2, Jaemin Shin3, Els Fieremans1, and Dmitry S Novikov1 | ||
1Radiology, NYU School of Medicine, New York, NY, United States, 2GE Research, Niskayuna, NY, United States, 3GE Healthcare, New York, NY, United States |
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A multishell diffusion neuro protocol at 1.5 mm isotropic resolution was acquired in 10 minutes with a high performance MAGNUS head gradient coil (200 mT/m with 500 mT/m/ms slew) at 3.0 T, and reconstructed using random matrix theory (RMT) denoising at the coil level. The SNR enhancement due to RMT reconstruction, and the nearly distortion-free images due to high slew rate, yield precise diffusion and kurtosis maps, fiber-dispersion, as well as microstructure parameters estimated using 3-compartment Standard Model of diffusion. We draw compartment fractions and diffusivities on fiber-tracts reconstructed based on fiber ODFs estimated by deconvolving model-based local fiber response. |
| 3649 | Comparison of DCE-MRI and FEXI in the measurement of vascular water exchange in high-grade glioma | |
| Zejun Wang1, Bao Wang2, Yingchao Liu3, and Ruiliang Bai1,4 | ||
1Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China, 2Department of Radiology, Qilu Hospital of Shandong University, Jinan, China, 3Department of Neurosurgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China, 4Department of Physical Medicine and Rehabilitation, Interdisciplinary Institute of Neuroscience and Technology, The Affiliated Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China |
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Vascular water exchange is a highly sensitive marker of BBB dysfunction and a potential biomarker of metabolic activity. In this study, we compared two different MRI methods for vascular water exchange measurement, including shutter speed (SS) DCE-MRI and filter-exchange imaging (FEXI) in high-grade glioma patents. Our results demonstrated consistent vascular water exchange assessments by SS DCE-MRI and FEXI in both normal-appearing white matter and tumor. |
| 3650 | Directions or Averages? An Ablation Study for in vivo Cardiac DTI | |
| Jaume Coll-Font1,2,3, Shi Chen1, Robert A Eder1, and Christopher T. Nguyen1,2,3 | ||
1Cardiovascular Research Center, Cardiology Division, Massachusetts General Hospital, Charlestown, MA, United States, 2Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States, 3Harvard Medical School, Boston, MA, United States |
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Recent advances in in vivo cardiac DTI have enabled rapid acquisition of the required diffusion weighted (DW) images. With the possibility of acquiring more DW images, it is not clear what is the best sampling strategy. Here we evaluate whether there are any differences between acquiring twice as many directions versus duplicating the number of repetitions. Our results indicate that it is marginally better to acquire multiple directions and that the loss of accuracy is produced by the reduction in the total number of DW images. |
| 3651 | Time-dependent anisotropic diffusion in the mouse heart: feasibility of motion compensated tensor-valued encoding on a 7T preclinical scanner | |
| Samo Lasic1,2, Henrik Lundell1, Beata Wereszczyńska3, Matthew Budde4, Nadira Yuldasheva3, Filip Szczepankiewicz5, Erica Dall’Armellina3, Jürgen E. Schneider3, and Irvin Teh3 | ||
1Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Copenhagen, Denmark, 2Random Walk Imaging, Lund, Sweden, 3Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom, 4Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, United States, 5Clinical Sciences, Lund University, Lund, Sweden |
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Tensor-valued diffusion encoding with simultaneous nulling of velocity, acceleration and concomitant gradients can be applied with high b-values on a preclinical 7T scanner. Results for ex-vivo mouse hearts confirm that time-dependent diffusion can significantly affect estimation of mean diffusivity. The estimated restriction sizes are consistent with results from pig hearts. Signal attenuations at high b-values suggest relatively low microscopic anisotropy and a strong influence of time-dependent diffusion on microstructure characterization. |
| 3652 | Evaluation of Synthetic-DWI with T2-based Water Suppression for DTI | |
| Tokunori Kimura1, Kousuke Yamashita1, and Kouta Fukatsu1 | ||
1Department of Radiological Science, Shizuoka College of Medicalcare Science, Hamamatsu, Japan |
||
We evaluated our proposed T2wsup-DWI method of reducing CSF-partial volume effects (PVE) on DTI. We assessed the errors in ADC and FA and the comparison of the ADC SNRs with several methods with simulation, and brain study. We clarified that our proposed T2wsup-DWI technique was superior to already proposed water suppression DWI methods of FLAIR and non-b-zero (NZE) methods in both of the ADC-SNR and the reduction effects of CSF-PVE in DTI parameters of ADC, FA, and tractograpy, typically at the portion of the fornix crus or genu of the corpus callosum which are close to the ventricle. |
| 3653 | Toward high-resolution mapping of microscopic anisotropy in the cortex using b-tensor diffusion imaging with a spiral readout at 7 Tesla | |
| Sajjad Feizollah1,2 and Christine L. Tardif1,2,3 | ||
1Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada, 2McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal, QC, Canada, 3Department of Biomedical Engineering, McGill University, Montreal, QC, Canada |
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High-resolution diffusion-weighted imaging has been used to investigate the microstructure of the cortex in vivo. However, conventional linear diffusion encoding provides limited insight into the underlying microstructural differences between cortical areas. b-Tensor encoding disentangles macroscopic from microscopic anisotropy in voxels with complex fiber geometries. The SNR and thus resolution of these scans are limited by the longer diffusion encoding times. A DWI sequence with b-tensor encoding was implemented at 7T with a spiral readout trajectory and dynamic field monitoring to image cortical microstructure. Microscopic anisotropy maps of the brain are presented at 1.4 mm isotropic, within minimal distortions and blurring. |
| 3654 | Reducing Rician noise bias in axial-symmetric Diffusion Kurtosis Imaging and biophysical tissue models | |
| Jan Malte Oeschger1, Karsten Tabelow2, and Siawoosh Mohammadi1,3 | ||
1Institute of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany, 2Weierstrass Institute for Applied Analysis and Stochastics, Berlin, Germany, 3Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany |
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Five out of eight axial-symmetric Diffusion Kurtosis Imaging (AxDKI) parameters are directly related to biophysical microstructure parameters including intra- and extra-axonal diffusivities, fiber dispersion and axonal-water fraction. Their estimation, however, is biased at small signal-to-noise ratios (SNR). Here, based on simulations, we investigated the Rician noise bias’s effect and its correction (RBC) on estimated AxDKI and biophysical parameters at varying SNRs for the standard and AxDKI model. Our study suggests AxDKI to be better than standard DKI, here least biased AxDKI estimators were produced with RBC while for biophysical parameters results were branch-dependent (SNR≥23 with RBC and SNR≥33 without RBC). |
| 3655 | Cerebrospinal Fluid Partial Volume Effects in Microscopic Fractional Anisotropy Imaging | |
| Nico J. J. Arezza1,2 and Corey A. Baron1,2 | ||
1Medical Biophysics, Western University, London, ON, Canada, 2Centre for Functional and Metabolic Mapping, Robarts Research Institute, London, ON, Canada |
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Microscopic fractional anisotropy (μFA) quantifies diffusion anisotropy independent of fiber orientation, giving it high specificity to microstructure. However, it is underestimated in brain regions containing cerebrospinal fluid (CSF) partial volumes. Here, we investigated two methods to reduce CSF partial volume effects: the free-water elimination method and a shifted kurtosis method. Compared to diffusion tensor imaging and diffusion kurtosis imaging, these techniques produced more accurate diffusivity estimates in simulations and higher μFA estimates in brain tissue. This preliminary work demonstrates the potential for CSF-suppressing techniques to improve μFA estimation in regions where CSF partial volume effects are prevalent. |
| 3656 | Development of in vivo human brain DTI-MRE: Optimization of experimental parameters | |
| Shujun Lin1, Bradley Sutton2, Richard Magin1, Aaron Anderson2, and Dieter Klatt1 | ||
1Richard and Loan Hill Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, United States, 2Beckman Institute, University of Illinois at Urbana-Champaign, Urbana-Champaign, IL, United States |
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Simultaneous acquisition of diffusion tensor imaging (DTI) and magnetic resonance elastography (MRE) has been proven feasible in a preliminary study of in vivo human brain. However, the experimental parameters have to be optimized in order to prevent mutual interferences of DTI and MRE acquisitions. We identified in simulations three experimental parameter sets for in vivo human brain DTI-MRE that we classify as good, moderate and poor with regard to optimization and present a pilot study using these parameter sets. The experimental results verify the simulations as we found the best performance of DTI-MRE for the good parameters set. |
| 3657 | Correcting B0 inhomogeneity-induced distortions in whole-body diffusion MRI of bone metastases | |
| Leonardino A. Digma1, Christine H. Feng1, Christopher C. Conlin2, Ana E. Rodriguez-Soto2, Kanha Batra3, Aaron Simon1, Roshan Karunamuni1, Joshua Kuperman2, Rebecca Rakow-Penner2, Michael E. Hahn2, Anders M. Dale2, and Tyler M. Seibert1,4 | ||
1Department of Radiation Medicine and Applied Sciences, UCSD School of Medicine, La Jolla, CA, United States, 2Department of Radiology, UCSD School of Medicine, La Jolla, CA, United States, 3Department of Electrical and Computer Engineering, UC San Diego, La Jolla, CA, United States, 4Department of Bioengineering, UC San Diego, La Jolla, CA, United States |
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Bone is among the most common sites of cancer metastases. Diffusion weighted imaging (DWI) can be used to detect these metastases. However, when acquired with echo-planar imaging, DWI suffers distortions due to static magnetic field inhomogeneities. In this study, we first used the reverse polarity gradient (RPG) technique to measure spatial distortions of bone metastases on DWI. Next, we demonstrated that RPG can be used to correct these distortions and produce diffusion images that more accurately reflect the underlying anatomy. Taken together, findings support the use of distortion correction techniques to improve localization of bone metastases on DWI. |
| 3658 | Developing a multi-parametric model of response based on biomarkers derived from Whole-Body Diffusion Weighted Imaging | |
| Antonio Candito1, Matthew D Blackledge1, Fabio Zugni2, Richard Holbrey1, Sebastian Schäfer3, Matthew R Orton1, Ana Ribeiro4, Matthias Baumhauer3, Nina Tunariu1, and Dow-Mu Koh1 | ||
1The Institute of Cancer Research, London, United Kingdom, 2IEO, European Institute of Oncology IRCCS, Milan, Italy, 3Mint Medical, Heidelberg, Germany, 4The Royal Marsden NHS Foundation Trust, London, United Kingdom |
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We develop a model of treatment response in patients with advanced prostate cancer (APC), based on measurements of median Apparent Diffusion Coefficient (ADC) and tumour Diffusion Volume (tDV) derived using Whole-Body Diffusion Weighted Imaging (WBDWI) and blood biomarkers. The model showed that change in ADC is positively correlated with response in this patient population. Furthermore, our model predicted response with an accuracy of 87%, and sensitivity/specificity of 75/93% using a probability cut-off of 0.5. |
| 3659 | Developing a deep learning model to classify normal bone and metastatic bone disease on Whole-Body Diffusion Weighted Imaging | |
| Antonio Candito1, Matthew D Blackledge1, Fabio Zugni2, Richard Holbrey1, Sebastian Schäfer3, Matthew R Orton1, Ana Ribeiro4, Matthias Baumhauer3, Nina Tunariu1, and Dow-Mu Koh1 | ||
1The Institute of Cancer Research, London, United Kingdom, 2IEO, European Institute of Oncology IRCCS, Milan, Italy, 3Mint Medical, Heidelberg, Germany, 4The Royal Marsden NHS Foundation Trust, London, United Kingdom |
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We employed a deep transfer-learning model to classify whether images from whole-body diffusion-weighted MRI (WBDWI) contain metastatic bone lesions. Our results demonstrate sensitivity/specificity of 0.87/0.89 on 8 test patients, who were not included in the model training. Such a model may accelerate radiological assessment of disease extent from WBDWI, which currently can be cumbersome to interpret due to the large quantity of data (approximately 200-250 images per patient). |
| 3660 | Improved assessment of prostate-cancer bone metastases through multicompartmental analysis of whole-body DWI data | |
| Christopher C Conlin1, Christine H Feng2, Leonardino A Digma2, Ana E Rodriguez-Soto1, Joshua M Kuperman1, Dominic Holland3, Rebecca Rakow-Penner1, Tyler M Seibert1,2,4, Michael E Hahn1, and Anders M Dale1,3,5 | ||
1Department of Radiology, UC San Diego School of Medicine, La Jolla, CA, United States, 2Department of Radiation Medicine and Applied Sciences, UC San Diego School of Medicine, La Jolla, CA, United States, 3Department of Neurosciences, UC San Diego School of Medicine, La Jolla, CA, United States, 4Department of Bioengineering, UC San Diego Jacobs School of Engineering, La Jolla, CA, United States, 5Halıcıoğlu Data Science Institute, UC San Diego, La Jolla, CA, United States |
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Whole-body DWI is increasingly used to assess bone involvement in prostate cancer. Multicompartmental diffusion modeling can outperform conventional DWI techniques for evaluating tumors, but has yet to be applied to whole-body imaging. In this study, we determined an optimal multicompartmental model for describing whole-body diffusion and applied it to examine metastatic bone lesions in vivo. We found that a 4-compartment model best characterized whole-body diffusion. Compartmental signal-contributions revealed by this model show improved bone-lesion conspicuity and may help to assess microstructural changes that accompany prostate-cancer bone involvement. |
| 3661 | Assessment the Preponderant Diagnostic Performances of Oligometastatic Prostate Cancer Using Diffusion Kurtosis Imaging | |
| Suhong Qin1, Ailian Liu1, SHUANG MENG1, Lihua Chen1, Qinhe Zhang1, Qingwei Song1, and Yunsong Liu1 | ||
1The First Affiliated Hospital of Dalian Medical University, Dalian, China |
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It remains a challenge to diagnose the oligometastatic prostate cancer (PCa) due to the ambiguous definition of oligometastatic PCa. Previous studies had shown that diffusion kurtosis imaging (DKI) is a non-gaussian diffusion weighted imaging (DWI) method that yields more accurate results on the microstructural complexity of prostate cancer tissue structure. This study indicated that performances of DKI cannot differentiate between oligometastatic and widely metastatic PCa, however it has the potential to assess tumor load and aggressiveness in metastatic PCa. |
| 3662 | Methodological considerations on segmenting MRI data of rhabdomyosarcoma | |
| Cyrano Chatziantoniou1,2, Reineke Schoot2, Roelof van Ewijk2, Simone ter Horst2, Rick van Rijn3, Hans Merks2, Alexander Leemans1, and Alberto de Luca1 | ||
1Image Science Institute, UMC Utrecht, Utrecht, Netherlands, 2Princess Máxima Center for Pediatric Oncology, Utrecht, Netherlands, 3Department of Radiology, Academic Medical Centre Amsterdam, Amsterdam, Netherlands |
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Rhabdomyosarcoma is a rare form of cancer that is particularly prevalent in children. There is a pressing need for new imaging biomarkers for monitoring treatment response, such diffusion. No standards currently exist to annotate rhabdomyosarcoma on MRI and measure the diffusion. This work analyses segmentation strategies in recent literature on saromas and compares them on a toy example. It shows that there is a large inconsistency in the application of segmentation strategies and that the different methods for segmenting the tumor can yield high variation in measured diffusion. |
| 3663 | Non-gaussian IVIM DW-and fast exchange regime DCE- MRI for predicting of locoregional failure in nasopharyngeal carcinoma | |
| Ramesh Paudyal1, Linda Chen2, Jung Hun Oh1, Kaveh Zakeri2, Vaios Hatzoglou3, Chiaojung Jillian Tsai2, Nancy Lee2, and Amita Shukla-Dave1,3 | ||
1Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States, 2Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States, 3Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States |
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The study aims to assess quantitative imaging (QI) metrics from pre-treatment (TX) non-gaussian intravoxel incoherent DW- and fast exchange regime (FXR) DCE-MRI for predicting locoregional failure (LRF) in nasopharyngeal carcinoma (NPC) patients. Cumulative incidence analysis (CIA) was performed on the two subgroups dichotomized with Youden’s index. Competing-risks regression based on Fine and Gray’s (FG) proportional sub hazards model was used to estimate survival subdistribution hazard ratios (SHRs). The pre-TX ADC, D, f, and ti cutoff values from CIA analysis and K cutoff value from the competing risk regression analysis indicated these QI’s could predict the LRF in NPC patients. |
| 3664 | Repeatability of VERDICT diffusion MRI in a model of human neuroendocrine tumour | |
| Lukas Lundholm1, Mikael Montelius1, Oscar Jalnefjord1, Eva Forssell-Aronsson1, and Maria Ljungberg1 | ||
1Department of Radiation Physics, Institute of Clinical Sciences, Gothenburg, Sweden |
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VERDICT dMRI allows for estimation of microstructural parameters in tumours which could facilitate planning and assessment of treatment. Due to the complexity of the model there is a risk for overfitting to data and there is hence a need to determine the reliability of the estimated parameters. A mouse model of human SI-NETs (n=5) was measured twice using the same dMRI protocol and the VERDICT model was fitted to data. Results showed an overall good repeatability of the tumour mean parameter values estimated by VERDICT. However, some local clusters of voxels showed larger differences between repeated scans. |
| 3665 | Qualitative and quantitative comparison between IVIM-DKI and PET/CT imaging in lymphoma | |
| Archana Vadiraj Malagi1, Devasenathipathy Kandasamy2, Kedar Khare3, Deepam Pushpam4, Rakesh Kumar5, Sameer Bakhshi4, and Amit Mehndiratta1,6 | ||
1Centre for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India, 2Department of Radiodiagnosis, All India Institute of Medical Sciences Delhi, New Delhi, India, 3Department of Physics, Indian Institute of Technology Delhi, New Delhi, India, 4Department of Medical Oncology, Dr. B.R. Ambedkar Institute-Rotary Cancer Hospital (IRCH), All India Institute of Medical Sciences Delhi, New Delhi, India, 5Department of Nuclear Medicine, All India Institute of Medical Sciences Delhi, New Delhi, India, 6Department of Biomedical Engineering, All India Institute of Medical Sciences Delhi, New Delhi, India |
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PET/CT plays an important role in diagnosis and assessment of treatment response in lymphoma. The goal of this study was to evaluate the role of IVIM-DKI parameters in comparison to PET parameters in lymphoma. PET images were registered onto IVIM-DKI at b=0s/mm2 images for tumor ROI using 3D-multimodal affine registration. Qualitatively, IVIM parameters with state-of-the-art Total-Variation produced better quality parameter maps. Tumor appeared hyperintense in SUV and K maps and hypointense in diffusion and perfusion parameters. No correlation was observed between IVIM-DKI with PET parameters. IVIM with Total-Variation showed substantial reproducibility as compared to conventional IVIM, DKI and SUV parameters. |
| 3666 | Preliminary Study on Monitoring Drug Resistance of Colon Cancer with Intravoxel Incoherent Motion MRI In Vivo | |
| Qi Xie1, Wenjuan He1, Zhilin Tan1, Yajie Wang1, Jinbin Wu1, Xiyan Shao2, Yiming Yang3, Jing Zhang4, Kangwei Wang5, Guiqin Wang6, Qifeng Pan1, and Yunzhu Wu7 | ||
1Medical Imaging Department, Nansha Hospital, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China, 2Ultrasound Imaging Department, Longgang District People’s Hospital, Shenzhen, China, 3Department of Radiology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Traditional Chinese Medicine, Guangzhou, China, 4Department of Pathology, Cancer Center, Sun Yat-sen University, Guangzhou, China, 5Department of Pathology, Nansha Hospital, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China, 6Medical Record Department, Nansha Hospital, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China, 7MR Scientific Marketing, SIEMENS Healthcare Ltd., Guangzhou, China |
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This study has demonstrated that ADC value of DWI with single-exponential model and diffusion coefficient D of IVIM are valuable for discriminating 5-FU-responsive and 5-FU-resistant colon cancer in vivo. IVIM is expected to be a simple and practical way to quantitatively monitor tumor resistance in vivo, and ADC &D value may be an imaging biomarker. |
| 3667 | Evaluation of bone marrow infiltration in the newly diagnostic Multiple Myeloma with Intravoxel Incoherent Motion Diffusion-weighted MRI | |
| Xiaojiao Pei1, Tao Jiang1, Zhenyu Pan1, Yufei Lian1, Yueluan jiang2, and qinglei Shi 3 | ||
1Radiology, Beijing Chaoyang Hospital Affiliated to Capital Medical University, Beijing, China, 2MR Scientific Marketing, Diagnosis Imaging, Siemens Healthineers China, Beijing, China, 3Scientific Marketing, Diagnosis Imaging, Siemens Healthineers China, Beijing, China |
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Intravoxel incoherent motion diffusion-weighted MR imaging (IVIM-DWI) can simultaneously acquire diffusion parameters and perfusion parameters without intravenous administration, compared with conventional diffusion imaging. This study investigated the application of IVIM in the newly diagnostic multiple myeloma (NDMM) patients. |
| 3668 | Diffusion and perfusion MRI predicts response preceding and shortly after stereotactic radiosurgery to brain metastases | |
| Amaresha Shridhar Konar1, Akash Deelip Shah2, Ramesh Paudyal1, Jung Hun Oh1, Eve LoCastro1, David Aramburu Nuñez1, Nathaniel Swinburne2, Robert J. Young2, Andrei I. Holodny2, Kathryn Beal3, Vaios Hatzoglou2, and Amita Shukla-Dave1,2 | ||
1Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States, 2Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States, 3Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States |
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In the clinical settings it is essential to accurately assess, whether or not a brain metastases has been successfully treated or whether it requires additional treatment, especially in high dose radiation therapy, such as stereotactic radiosurgery (SRS). The present prospective study aims to determine the ability of Diffusion Weighted (DW)- and Dynamic Contrast Enhanced (DCE)-MRI to predict the long-term response of brain metastases within 72 hours of SRS. The preliminary results are promising as it will inform the treating physicians at an early time point about which patients will benefit from SRS (or not). |
| 3669 | The utility of IVIM maps in the assessment of microvascular perfusion of brain glioma | |
| Andre Monteiro Paschoal1,2, Raquel Andrade Moreno3,4, Antonio Carlos dos Santos5, and Renata Ferranti Leoni6 | ||
1LIM44, Instituto e Departamento de Radiologia, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil, 2InBrain Lab, University of Sao Paulo, Ribeirao Preto, Brazil, 3Instituto do Cancer do Estado de Sao Paulo, Sao Paulo, Brazil, 4Memorial Sloan-Kettering Cancer Center, New York, NY, United States, 5Departamento de Clinica Medica, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo, Ribeirao Preto, Brazil, 6InBrain Lab - University of Sao Paulo, Ribeirao Preto, Brazil |
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The assessment perfusion in glioma is an important information in the tumor characterization. Traditional MRI methods employed to analyze glioma are based on the application of contrast agents to enhance the T1 signal and/or to measure perfusion within the tumor cells. The analysis of tumor microvasculature however is hampered by the size of contrast agent molecules. In that sense, SWI can be employed, although it does not provide quantitative information. IVIM maps showed to be an interesting alternative for such assessment, even showing potential of an early biomarker to assess early changes in perfusion, specially in low grade gliomas. |
| 3670
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Diffusion-time-dependent diffusion MRI based microstructural mapping for grading and categorizing in pediatric brain tumor | |
| ruicheng ba1, Hongxi Zhang2, Zhongwei Gu3, Yuhao Liao1, Xingwang Yong1, Zhiyong Zhao1, Yi Zhang1, and Dan Wu1 | ||
1Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hang zhou, Zhejiang, China, 2Children's Hospital, Zhejiang University School of Medicne，Department of Radiology, Hang zhou, Zhejiang, China, 3Children's Hospital, Zhejiang University School of Medicne, Department of Pathology, Hangzhou, Zhejiang, China |
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Diffusion-time dependent diffusion MRI (dMRI) has been proposed to characterize tumor microstructure. This study aimed to evaluate diagnostic value of time-dependent dMRI based microstructural mapping to grade and categorize pediatric brain tumor at 3T. Oscillating and pulsed gradient dMRI was performed in 35 pediatric patients. Cell diameter (d), intracellular fraction (fin) and extracellular diffusivity (Dex) were fitted based on the IMPULSED model. Higher cellularity (fin/d) and fin and lower Dex were found in high-grade glioma than low-grade ones. The cellularity further increased in medulobastoma compared with glioma. Cellularity achieved the highest area-under-the-curve than the other dMRI metrics in grading glioma. |
| 3671 | Imaging attributes of H3K27M mutation in Diffuse Midline Gliomas on Multiparametric MRI | |
| Richa Singh Chauhan1, Nihar Kathrani2, Jitender Saini1, Maya D Bhat1, Karthik Kulanthaivelu1, Vani Santosh3, Nishanth S4, and Subhas Konar4 | ||
1Neuroimaging and Interventional Radiology, NIMHANS, BENGALURU, India, 2Interventional Radiology, Paras Hospital, Gurgaon, India, 3Neuropathology, NIMHANS, BENGALURU, India, 4Neurosurgery, NIMHANS, BENGALURU, India |
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H3K27M mutant diffuse midline gliomas are a newly classified entity in the 2016 World health organization classification of CNS tumors. They are high grade tumors, with the mere presence of this mutation confers them a WHO grade IV designation, irrespective of their histologic morphology. Patients harboring these tumors have dismal prognosis and shorter overall survival. Furthermore, since these are deep-seated lesions involving the eloquent brain areas, biopsy can be challenging with substantial risk of morbidity. Our work proposes non-invasive multiparametric MRI-based imaging attributes to detect the H3K27M mutation pre-operatively. Results demonstrate a considerable accuracy on 123 patients. |
| 3672 | Grading of glioma with histogram analysis of multiparameter using advanced diffusion models | |
| Gao Eryuan1, Gao Ankang1, Zhang Huiting2, Wang Shaoyu2, Yan Xu2, Bai Jie1, and Cheng Jingliang1 | ||
1Dept. of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China, Zhengzhou, China, 2MR Scientific Marketing, Siemens Healthcare, Shanghai, China, Shanghai, China |
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This study aimed to investigate the efficiency of four advanced diffusion models, including diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), neurite orientation dispersion and density imaging (NODDI) and mean apparent propagator (MAP) in grading of glioma. Through histogram analysis of parameters, we found that axial diffusivity (AD)maximum, mean diffusivity (MD)maximum and radial diffusivity (RD)maximum from DTI, and Q-space inverse variance (QIV)maximum and QIVrange from MAP had significant differences and good diagnostic efficiency in all comparisons among different grading of glioma. |
| 3673 | Histogram analysis in prediction of Isocitrate Dehydrogenase Genotype in Gliomas with MRI: The Gaussian versus non-Gaussian Diffusion Models | |
| Gao Ankang1, Gao Eryuan1, Zhang Huiting2, Wang Shaoyu2, Yan Xu2, Bai Jie1, and Cheng Jingliang1 | ||
1Dept. of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China, 2MR Scientific Marketing, Siemens Healthcare, Shanghai, China, Shanghai, China |
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The Isocitrate dehydrogenase (IDH) genotyping and epigenetic 1p/19q codeletion as two key molecular markers are included in the glioma WHO 2016 classification. Gaussian or non-Gaussian diffusion models were recently proposed to provide additional microstructure information. In present work, we applied four diffusion models in glioma grading and genotyping, including DTI, DKI, MAP-MRI and NODDI models, which could be acquired within a single scan. |
| 3674 | Neurite Orientation Dispersion and Density Imaging in Evaluation of Glioma-induced Corticospinal Tract Injury | |
| Rifeng Jiang1, Kaiji Deng1, Yixin Guo2, and Zhongshuai Zhang3 | ||
1Fujian Medical University Union Hospital, Fuzhou, China, 2Fujian Medical University, Fuzhou, China, 3MR Scientific Marketing, Siemens Healthcare, Shanghai, China |
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This study found that NODDI seems to be a more potent approach in evaluating the early CST infiltration by HGG, and can evaluate the CST destruction with a similar performance to MD by providing additional information about neurite density for HGG-induced CST injury. |
| 3675 | Beyond cellularity: Which microstructural features determine the mesoscopic mean diffusivity in meningiomas? | |
| Jan Brabec1, Filip Szczepankiewicz2, Jaromír Šrámek3, Elisabet Englund4, Johan Bengzon5, Linda Knutsson1,6, Carl-Fredrik Westin7,8, Pia C Sundgren2,9, and Markus Nilsson2 | ||
1Medical Radiation Physics, Lund University, Lund, Sweden, 2Diagnostic Radiology, Lund University, Lund, Sweden, 3Institute of Histology and Embryology, First Faculty of Medicine, Charles University, Prague, Czech Republic, 4Division of Oncology and Pathology, Department of Clinical Sciences, Lund University, Lund, Sweden, 5Division of Neurosurgery, Department of Clinical Sciences, Lund University, Lund, Sweden, 6Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States, 7Harvard Medical School, Boston, MA, United States, 8Radiology, Brigham and Women’s Hospital, Boston, MA, United States, 9Lund University Bioimaging Center, Lund University, Lund, Sweden |
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Mean diffusivity (MD) in tumors is often too readily interpreted as cellularity. Here, we investigated which microstructural features explain the MD in meningioma tumors. We performed high-resolution MRI and histological imaging on excised mengioma tumor samples and coregistered MD to histology. We found that cellularity alone was a poor predictor of MD, and that the prediction improved markedly by considering also the microcyst density. A qualitative analysis also indicated that collagen fibers, stroma and psammoma bodies affect the MD. |
| 3676 | Diffusion MRI based on a gamma distribution model for the differentiation of primary central nervous system lymphomas and glioblastomas | |
| Osamu Togao1, Akio Hiwatashi2, Toru Chikui3, Kazufumi Kikuchi2, Yukiko Kami3, Kenji Tokumori4, and Kousei Ishigami2 | ||
1Molecular Imaging & Diagnosis, Kyushu University, Fukuoka, Japan, 2Clinical Radiology, Kyushu University, Fukuoka, Japan, 3Oral and Maxillofacial Radiology, Kyushu University, Fukuoka, Japan, 4Clinical Radiology, Teikyo University, Omuta, Japan |
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The aim of the present study was to determine whether the gamma distribution (GD) model is useful in the differentiation of glioblastomas (GBs) and primary CNS lymphomas (PCNSLs). The GD model well described the histological features of PCNSLs and GBs, and its use enabled the significant differentiation of these tumors. The κ, f2, and f3 values were significantly smaller and the f1 values were significantly larger in the PCNSLs than in the GBs. The GD model-derived parameters correlated well with the IVIM-derived parameters. The GD model may therefore contribute to the characterization of brain tumor from the histological viewpoint. |
| 4282 | Where do streamlines come from? Seeding strategies impact on streamline distribution | |
| Manon Edde1, Etienne St-Onge1, Antoine Théberge1,2, Guillaume Theaud1, Emmanuelle Renauld1, and Maxime Descoteaux1 | ||
1Sherbrooke Connectivity Imaging Lab (SCIL), Université de Sherbrooke, Sherbrooke, QC, Canada, 2Videos & Images Theory and Analytics Laboratory (VITAL), Université de Sherbrooke, Sherbrooke, QC, Canada |
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Tractography algorithms require a seeding map in which each point initiates one streamline. We can determine how many streamlines end in each voxel from one of their ends, but their initial point is unknown. We propose a method to compute the initial streamline points (IPS) in each voxel and evaluate their distribution depending on two strategies of seeding. With the surface-based interface, IPSs maps are more uniform along the cortex independently of the cortical volume, allowing a greater cortical coverage and specificity at the level of the cortical regions both at the whole-brain and bundle level. |
| 4283 | Blurred streamlines: a new concept to improve tractography accuracy by spatially blurring signal contributions | |
| Alessandro Daducci1, Francesco Gobbi1, Nicola Febbrari1, Matteo Battocchio1, and Simona Schiavi1 | ||
1University of Verona, Verona, Italy |
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Tractography is a powerful tool to study brain connectivity but it suffers from an intrinsic trade-off between sensitivity and specificity. The former can be increased by constructing more streamlines, while filtering techniques can improve the latter. However, creating many streamlines may introduce redundancy in the tractograms and negatively affect the performances of filtering methods, especially those based on linear optimization. Here, we present the “blurred streamlines”, a novel concept based on a combination of streamline clustering and spatial blurring of their signal contributions. Preliminary results show the potential of this formulation and open new perspectives for improving tractography accuracy. |
| 4284 | Robust residual bootstrapping algorithm for accurate SH representation of DW MRI signal that contains outliers | |
| Viljami Sairanen1,2 and Chantal M. W. Tax3,4 | ||
1Department of Computer Science, University of Verona, Verona, Italy, 2Translational Imaging in Neurology, Department of Medicine and Biomedical Engineering, University of Basel, Basel, Switzerland, 3CUBRIC, Cardiff University, Cardiff, United Kingdom, 4Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands |
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Diffusion MRI measurements are affected by noise which propagates into the model estimation. Residual bootstrapping has been proposed to assess the uncertainty of parameter estimates, but do not consider the confounding effect of measurement outliers (e.g. due to subject motion), limiting their usage on clinical data. We present a robust bootstrapping algorithm and demonstrate its performance on the estimation and uncertainty quantification of rotationally invariant spherical harmonic (RISH) features with simulations and clinical data. Our algorithm can improve the reliability of cross-scanner harmonization relying on RISH and probabilistic tractography. |
| 4285 | ODF-Fingerprinting Improves Reconstruction of Fibers Crossing at Shallow Angles: A Study on Diffusion Phantom | |
| Patryk Filipiak1, Lee Basler2, Anthony Zuccolotto2, Ying-Chia Lin1, Dimitris G. Placantonakis3, Timothy Shepherd1, Walter Schneider4, Fernando E. Boada1, and Steven H. Baete1 | ||
1Center for Advanced Imaging Innovation and Research (CAI2R), NYU School of Medicine, New York, NY, United States, 2Psychology Software Tools, Inc., Pittsburgh, PA, United States, 3Department of Neurosurgery, Perlmutter Cancer Center, Neuroscience Institute, Kimmel Center for Stem Cell Biology, NYU School of Medicine, New York, NY, United States, 4University of Pittsburgh, Pittsburgh, PA, United States |
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ODF peak finding typically fails to reconstruct fibers crossing at angles below 45 degrees. We aim to break this barrier with ODF-Fingerprinting. Our approach replaces the peak finding mechanism with pattern matching, allowing to use all the information stored in ODFs. In this work, we study the ability of ODF-Fingerprinting to reconstruct fibers crossing at 90, 45, and 30 degrees in a diffusion phantom composed of textile tubes with 0.8µm diameter, approaching the anatomical scale of axons. Our approach reaches much higher sensitivity (84-100%) than the ODF peak finding (0-33%), especially at the shallow angles. |
| 4286 | Quantitative comparison of fiber orientation distribution functions obtained with constrained spherical deconvolution and fiber ball imaging | |
| Hunter Moss1 and Jens Jensen1 | ||
1Neurosciences, Medical University of South Carolina, Charleston, SC, United States |
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The fiber orientation distribution function (fODF) can be estimated with diffusion MRI and gives the angular probability density of axon orientations in white matter. Here fODFs, as estimated with constrained spherical deconvolution (CSD) and fiber ball imaging (FBI), are compared quantitatively in order to assess their consistency. An important distinction between these two approaches is that CSD relies on a globally defined, empirical response function while FBI does not. For two measures of anisotropy, similar results are found for the CSD and FBI fODFs. However, a distance metric reveals significant differences in fODF peak directions and fine structure. |
| 4287 | Group Average Tractography of the Human Brain using Direct Streamline Mapping | |
| Zifei Liang1 and Jiangyang Zhang1 | ||
1Center for Biomedical Imaging, Dept. of Radiology, New York University School of Medicine, NEW YORK, NY, United States |
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Diffusion MRI based tractography is widely used to examine structural connectivity in the brain. Due to noises and motions, tractography in individual subject may contain erroneous results, which may be removed by averaging over a group. Although several group average tractography (GAT) approaches are available, their accuracy has not been thoroughly examined. In this study, we compared GAT based on spatial normalization of fiber orientation distribution maps and direct streamline mapping. Our results suggest that direct streamline mapping better preserve small and secondary axonal projections and is better-suited for studying group average tractography of the brain. |
| 4288 | StND: Non-Rigid Partial Deformation Tractography Registration | |
| Bramsh Qamar Chandio1 and Eleftherios Garyfallidis1 | ||
1Intelligent Systems Engineering, Indiana University Bloomington, Bloomington, IN, United States |
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StND is a method for non-rigid registration of white matter tracts in streamline-space. StND performs two-step registration to align the moving bundle with a static (reference) bundle. In the first step, it affinely registers the two given tracts, and in the second step, it partially deforms the moving bundle to better align it with the static bundle. This partial deformation allows us to improve registration by deforming only areas where there is higher correspondence between streamlines of the tracts. This also helps in preserving the original anatomical structure of the moving bundle. |
| 4289 | On false positive control in Fixel-Based Analysis | |
| Robert Smith1,2, Daan Christiaens3,4, Ben Jeurissen5, Maximillian Pietsch3, David Vaughan1,2,6, Graeme Jackson1,2,6, and J-Donald Tournier3 | ||
1Florey Institute of Neuroscience & Mental Health, Melbourne, Australia, 2Florey Department of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Australia, 3School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom, 4Department of Electrical Engineering, KU Leuven, Leuven, Belgium, 5Department of Physics, University of Antwerp, Antwerp, Belgium, 6Department of Neurology, Austin Health, Melbourne, Australia |
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While the Fixel-Based Analysis (FBA) framework provides familywise error control across a whole-brain template accounting for the presence of crossing fibres in the white matter, its typical usage fails to correct for multiple hypothesis tests due to the utilisation of multiple quantitative metrics. We demonstrate different methods that can be employed to provide more comprehensive false positive control in this context. |
| 4290 | Probabilistic Tractography of the Arcuate Fasciculus: Sensitivity and Specificity of Standardised fMRI and Atlas-based Approaches | |
| Jane Ansell1,2, Irène Brumer3, Jonathan Ashmore4, Enrico de Vita5, Josef Jarosz2, and Marco Borri2 | ||
1King's College London, London, United Kingdom, 2Department of Neuroradiology, King's College Hospital, London, United Kingdom, 3Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany, 4Department of Medical Physics and Bioengineering, NHS Highland, Inverness, United Kingdom, 5Department of Biomedical Engineering, School of Biomedical Engineering and Imagine Sciences, King's College London, London, United Kingdom |
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Atlas and fMRI-based approaches to standardise seed and end regions for probabilistic tractography of the arcuate fasciculus are investigated. fMRI-based approaches use spheres centered on language task peak activation. Within this pilot cohort, an atlas-based approach demonstrates the greatest sensitivity. fMRI-based approaches are more specific, but sensitivity can be increased by enlarging sphere size. Within each approach, a trade-off between sensitivity and specificity is seen as seed/end region size increases. For patients with abnormalities or lesions, where atlas approaches might be compromised, fMRI methods may be preferred. Further work to optimise fMRI-based approach is warranted, alongside application to patient data. |
| 4291 | Advantage of simultaneous multi-slice readout-segmented echo-planar imaging on diffusion MRI measurements of the human optic nerve | |
| Hiromasa Takemura1,2, Wei Liu3, Hideto Kuribayashi4, and Ikuhiro Kida1,2 | ||
1Center for Information and Neural Networks (CiNet), National Institute of Information and Communications Technology, Suita-shi, Japan, 2Graduate School of Frontier Biosciences, Osaka University, Suita-shi, Japan, 3Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen, China, 4Siemens Healthcare K.K., Tokyo, Japan |
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Diffusion MRI measurements of the human optic nerve remain challenging due to susceptibility-induced artifacts, despite their importance in neuro-ophthalmology research. Here, we demonstrate that simultaneous multi-slice (SMS) readout-segmented echo-planar imaging (rsEPI) acquisition has advantages in measuring the human optic nerve over conventional SMS single-shot EPI (ssEPI) with respect to image quality. This result was confirmed with statistical comparisons demonstrating higher fractional anisotropy along the optic nerve in SMS rsEPI data compared with that in SMS ssEPI data. Taken together, this study demonstrates the utility of SMS rsEPI for diffusion MRI measurements of tissue properties of the optic nerve. |
| 4292 | Enhancing tractography filtering by accounting for outliers and partial voluming in diffusion weighted measurements | |
| Viljami Sairanen1,2, Mario Ocampo-Pineda1, Cristina Granziera2, Simona Schiavi1, and Alessandro Daducci1 | ||
1Department of Computer Science, University of Verona, Verona, Italy, 2Translational Imaging in Neurology, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland |
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The white matter structures of the human brain can be represented via diffusion tractography. Unfortunately, tractography is prone to find false-positive streamlines causing a severe decline in its specificity and limiting its clinical feasibility. Filtering algorithms have been proposed to reduce these invalid streamlines. We augmented the COMMIT filtering algorithm to adjust for two typical artifacts present in diffusion-weighted images: partial voluming and signal drop-outs due to subject motion. We demonstrate that our robust algorithm is capable to properly filter tractography reconstructions despite these artifacts and could be useful especially for clinical studies with uncooperative patient groups such as neonates. |
| 4293 | Robust Estimation of Fascicle-based Fractional Anisotropy on Fiber Crossings | |
| Erick Hernandez-Gutierrez1, Ricardo Coronado-Leija2, Gabrielle Grenier3, Maxime Descoteaux3, and Alonso Ramirez-Manzanares1 | ||
1Computer Science, CIMAT A.C., Guanajuato, Mexico, 2New York University School of Medicine, New York, NY, United States, 3Université de Sherbrooke, Sherbrooke, QC, Canada |
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In this work, a novel multi-shell modelling method is proposed to compute fascicle-based fractional anisotropy that is shown accurate and robust in the centrum semiovale of human brain clinical multi-shell datasets. It does not require tractography and it is informed by the local modelling estimations provided by the method called MRDS. The effectiveness of our methodology is also shown on synthetic experiments. |
| 4294 | White Matter Inter-tract Connectivity Using Cosine Similarity between Population Kernel Densities of Diffusion Measures | |
| David Lee1, Ashish Sahib1, Antoni Kubicki1, Katherine Narr1, and Shantanu Joshi1 | ||
1UCLA, Los Angeles, CA, United States |
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Pairwise inter-tract correlations of the mean diffusion measures have been used to infer structural connectivity among major white matter (WM) fiber tract pathways. Instead of using the mean, we propose a novel approach of constructing kernel density distributions to represent population variability of fractional anisotropy. We also propose the cosine similarity metric between the full shapes of the kernel densities to investigate inter-tract connectivity among the fiber tracts. Our representation and the shape similarity measure is a better predictor of the short- and long-range connectivity disruptions in WM tracts in major depressive disorder patients compared to the conventional mean-based approach. |
| 4295 | The test-retest reliability and robustness of diffusion-MRI based tractometry | |
| John Kruper1,2, Jason D Yeatman3,4, Adam Richie-Halford2, David Bloom1,2, Mareike Grotheer5,6, Sendy Caffarra3,4,7, Greg Kiar8, Iliana I. Karipidis9, Ethan Roy3, and Ariel Rokem1,2 | ||
1Department of Psychology, University of Washington, Seattle, WA, United States, 2eScience Institute, University of Washington, Seattle, WA, United States, 3Graduate School of Education, Stanford University, Stanford, CA, United States, 4Division of Developmental-Behavioral Pediatrics, Stanford University School of Medicine, Stanford, CA, United States, 5Center for Mind, Brain and Behavior - CMBB, Hans-Meerwein-Straße 6, Marburg, Germany, 6Department of Psychiatry, University of Marburg, Marburg, Germany, 7Basque Center on Cognition (BCBL), Brain and Language, Donostia‐San Sebastián, Spain, 8Department of Biomedical Engineering, McGill University, Montreal, QC, Canada, 9Center for Interdisciplinary Brain Sciences Research, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, United States |
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Tractometry from diffusion MRI estimates the tissue properties along the length of major white matter tracts, using: computational tractography; tract segmentation using atlases or other classification methods; and microstructural modeling in voxels along the length of the estimated tracts. Given previous concerns about the sensitivity of dMRI-based analysis to variations in methodology, we tested: the reliability of tractometry results within individuals across measurements; and within measurement, across variations in the analysis methods. We found that although there are variations that arise from differences in tractography methods, bundle segmentation methods, microstructural modeling, and different software implementations, tractometry is overall quite robust. |
| 4296 | Improving tractography Reconstruction using Local-phase Features | |
| Alireza Shirazinodeh1,2 and Hamidreza Saligheh Rad1,2 | ||
1Department of Medical Physics and Biomedical Engineering, Tehran university of Medical Science, Tehran, Iran (Islamic Republic of), 2Quantitative MR Imaging and Spectroscopy Group, Research Center for Molecular and Cellular Imaging, Tehran, Iran (Islamic Republic of) |
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Tractography of the brain fibers from diffusion signals in magnetic resonance imaging needs to be more sensitive to structures of diffusion images to reduce the number of ODF used to predict tracts and avoid determining false-positive cases in pixels whose values may have changed due to noise or other unwanted factors. The local-based methods can be improved tractography results. In this abstract, we designed a mask based on the local structures of the diffusion phantom images in 64 directions. Using this mask we reduced the number of gradients and false-positive predicted results from the outputs of the tractography algorithm. |
| 4297 | Surface-based Short Association Fibre Tractography | |
| Dmitri Shastin1,2,3, Sila Genc1, Greg Parker1, Kristin Koller1, Chantal M.W. Tax1,4, John Evans1, Khalid Hamandi1,3,5, Derek Jones1,3, William Gray1,2,3, and Maxime Chamberland1 | ||
1Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom, 2Department of Neurosurgery, University Hospital of Wales, Cardiff, United Kingdom, 3BRAIN Biomedical Research Unit, Health & Care Research Wales, Cardiff, United Kingdom, 4Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands, 5Department of Neurology, University Hospital of Wales, Cardiff, United Kingdom |
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We propose a method of utilising mesh representations of cortical surfaces for generating tractograms of short association fibres facilitating a focused investigation into superficial white matter in health and disease. The method additionally allows to relate streamline metrics to surface topology in native space before registration for comparisons within and between subjects is performed. Our approach is applied to state-of-the-art test-retest data and shows good-to-excellent repeatability. |
| 4298 | Surface-based Shape Morphometry Analysis of Human White Matter Tracts | |
| Yi-Chia Kung1, Chu-Chung Huang2, Chih-Chin Heather Hsu1,3, Shin Tai Chong1, Ching-Po Lin1, and Chun-Hung Yeh4,5 | ||
1Institute of Neuroscience, National Yang-Ming University, Taipei, Taiwan, 2Institute of Cognitive Neuroscience, School of Psychology and Cognitive Science, East China Normal University, Shanghai, China, 3Center for Geriatrics and Gerontology, Taipei Veterans General Hospita, Taipei, Taiwan, 4Institute for Radiological Research, Chang Gung University and Chang Gung Memorial Hospital, Taoyuan, Taiwan, 5Department of Child and Adolescent Psychiatry, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan, Taiwan |
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This study proposes a novel framework for quantifying the alteration in shape morphometry of white matter (WM) fiber tracts. The surface of each WM bundle is segmented from diffusion MRI data using TractSeg, followed by surface reconstruction, parameterization, and modelling. With the M-rep parameterization and vertex-wise model distance, the proposed method was able to differentiate the level of morphological lateralization between bilateral arcuate fasciculi and cortical spinal tracts. |
| 4299 | Improving white matter bundle recovery: A fast & practical ensemble tractography pipeline | |
| Alexandre Joanisse1, Guillaume Theaud1, Jon Haitz Legarreta1, François Rheault1,2, and Maxime Descoteaux1 | ||
1Computer Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada, 2Electrical Engineering, Vanderbilt University, Nashville, TN, United States |
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In most tractography settings, users choose a single tracking algorithm and a single set of tracking parameters, which may limit the quality and impact of the bundle reconstruction results. The present ensemble tractography processing pipeline aims at producing diverse whole brain tractograms faster by tuning and automatically concatenating multiple tractograms from different combinations of parameters and algorithms. Compared to classical tractography, our optimized ensemble tractography obtains improved or similar white matter bundle recovery but in 62% of the processing time. |
| 4300 | GPU-accelerated diffusion MRI tractography in DIPY | |
| Ariel Rokem1, Mauro Bisson2, Josh Romero2, Thorsten Kurth2, Massimiliano Fatica2, Pablo Damasceno3, Xihe Xie3, Adam Richie-Halford4, Serge Koudoro5, and Eleftherios Garyfallidis5 | ||
1Psychology, University of Washington, Seattle, WA, United States, 2NVIDIA, Menlo Park, CA, United States, 3University of California, San Francisco, San Francisco, CA, United States, 4University of Washington, Seattle, WA, United States, 5Indiana University, Bloomington, IN, United States |
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Tractography based on diffusion-weighted MRI provides non-invasive in vivo estimates of trajectories of long-range brain connections. These estimates are important in research that measures individual differences in brain connections and in clinical use-cases. But the computational demands of tractography present a barrier to progress. Here, we present a GPU-based tractography implementation that accelerates tractography algorithms implemented as part of the Diffusion Imaging in Python (DIPY) project. This implementation speeds up tractography by at least a factor of ~200X, providing tractographies that closely match CPU-based solutions. These speedups enable applications of tractography in clinical data, and in very large datasets. |
| 4301 | Connectoflow: A cutting-edge Nextflow pipeline for structural connectomics | |
| Francois Rheault1,2, Jean-Christophe Houde2, Jasmeen Sidhu3, Sami Obaid2,4, Guido Guberman5, Alessandro Daducci6, and Maxime Descoteaux2 | ||
1Electrical Engineering, Vanderbilt University, Nashville, TN, United States, 2Computer Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada, 3Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, QC, Canada, 4Centre de Recherche du Centre Hospitalier, Université de Montréal, Montréal, QC, Canada, 5Department of Neurology and Neurosurgery, McGill University, Montréal, QC, Canada, 6Computer Science, University of Verona, Verona, Italy |
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Tractography involves complicated processing and connectomics include even more complexity. To facilitate structural connectome reconstruction we present: Connectoflow. Connectoflow requires simple inputs, has simple options and provides simple outputs, all with cutting-edge processing. By leveraging the simplicity of Nextflow and Docker/Singularity, Connectoflow is robust and efficient. By combining Tractoflow with Connectoflow, one can go from raw DW-images to structural connectomes in a few simplified steps. The proposed pipeline innovates by including connection-wise cleaning/filtering, provides connection weights that go beyond streamline count (COMMIT) as well as advanced connection-wise metrics (similarity and AFD). |
| 4302 | False-positive potential of tractography-derived connections improves network reconstruction for disease spreading models | |
| Anna Schroder1, Neil P. Oxtoby1, Marco Palombo1, Simona Schiavi2, Alessandro Daducci2, and Daniel C. Alexander1 | ||
1Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom, 2Department of Computer Science, University of Verona, Verona, Italy |
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Network spreading models of disease propagation utilise functional or anatomical connectivity to predict regional pathology in-vivo. Models based on anatomical connectivity are likely to be disrupted by the inevitable presence of errors from tractography. To mitigate this problem, we propose a method to evaluate the potential of each tractography-derived connection to be false-positive. By incorporating this false-positive potential into a network spreading model, we are able to predict a pattern of tau accumulation more closely aligned with the pathology observed in a cohort of Alzheimer’s Disease patients. |
| 4303 | Spatial Entropy Mapping of the Connectome using White Matter Fibrography: Quantifying the Effects of Age. | |
| Ryan McNaughton1, Hernan Jara1,2, Ning Hua2,3, Andy Ellison2,3, Osamu Sakai2, Lee Goldstein1,2,3, and Stephan Anderson2,3 | ||
1Boston University, Boston, MA, United States, 2Boston University Medical Center, Boston, MA, United States, 3Center for Translational Neuroimaging, Boston, MA, United States |
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Purpose: To develop algorithms for mapping the spatial entropy (SE); extending white matter fibrography (WMF) for quantifying whole-brain information content. Methods: SE algorithms were applied to WM texture images of four individuals of increasing age, optimized for maximum information content, and implemented to calculate the whole-brain WM complexity. Results: SE was positively correlated with subject age. Conclusion: SE is a promising quantitative metric for objectively distinguishing the state of WM architecture from fibrograms, particularly as it relates to age effects. |
| 4304 | Automatic tractography for brain tumor surgery: towards clinical application | |
| Stephan Meesters1,2, Maud Landers2, Geert-Jan Rutten2, and Luc Florack1 | ||
1TU/e Eindhoven University of Technology, Eindhoven, Netherlands, 2ETZ Elisabeth-TweeSteden hospital, Tilburg, Netherlands |
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We have introduced an automatic pipeline based on diffusion-weighted tractography for the reconstruction of four white-matter structures of interest. These anatomical reconstructions are visualized during brain tumour surgery to aid in the prevention of sensorimotor, visual and language deficits. The automatic tractography pipeline produces robust results, owing in part to the deep-learning based segmentation of brain regions which is robust to deformations of the brain due to brain shift, and the post-tractography filtering method which can remove spurious fibers. |
| 4305 | Quantitative evaluation of white matter tracts reconstruction with an anatomically curated atlas in patients with brain tumours | |
| Umberto Villani1,2, Erica Silvestri1,2,3, Colpo Maria2, D'Avella Domenico3, Della Puppa Alessandro4, Maurizio Corbetta1,3, Cecchin Diego5, and Alessandra Bertoldo1,2 | ||
1Padova Neuroscience Center, University of Padova, Padova, Italy, 2Department of Information Engineering, University of Padova, Padova, Italy, 3Department of Neuroscience, University of Padova, Padova, Italy, 4Department of Neurosurgery, University of Firenze, Firenze, Italy, 5Department of Medicine, Unit of Nuclear Medicine, University of Padova, Padova, Italy |
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We propose an application of the open-source whitematteranalysis software which moves a step towards the goal of reproducible and quantitative evaluation of anatomical tracts reconstruction by dMRI tractography. We quantify the tractogram in 11 patients suffering from brain tumours with four different algorithms, perform the automated spectral clustering procedure implemented in the software and evaluate simple metrics to compare the tractograms to an available anatomically curated atlas. Independently from the tumour position, the four investigated algorithms failed to properly reconstruct certain anatomical tracts. Evaluating the overall streamline representation of all tracts, the iFOD2 algorithm was found to perform best. |
| 4306 | Assessment of structural connectivity matrices sensitivity to tractography termination criteria in glioma patients | |
| Maria Colpo1, Erica Silvestri1,2,3, Umberto Villani1,2, Domenico D'Avella3, Alessandro Della Puppa4, Diego Cecchin2,5, Maurizio Corbetta2,3, and Alessandra Bertoldo1,2 | ||
1Department of Information Engineering, University of Padova, Padova, Italy, 2Padova Neuroscience Center, University of Padova, Padova, Italy, 3Department of Neuroscience, University of Padova, Padova, Italy, 4Department of Neurosurgery, University of Firenze, Firenze, Italy, 5Department of Medicine, Unit of Nuclear Medicine, University of Padova, Padova, Italy |
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Varying termination criteria values of tractography algorithms produce tangible effects on the reconstructed tractograms. While these effects are extensively documented in the state-of-the-art literature for healthy subjects, little is known about streamline reconstruction differences in presence of brain tumours. In this work we apply a statistical framework to assess the impact of the cut-off value on the resulting structural connectivity matrices in 11 patients suffering from gliomas. Results show how varying the cut-off value in the studied range does not produce significant changes in the matrix structure, thus validating literature recommendations for healthy subjects in the case of glioma patients. |
| 4307 | DTI fiber tracking reveals positive effects of motor training on stroke recovery | |
| Bastian Maus1,2, Lydia Wachsmuth1,2, Maike Hoppen3, Jens Minnerup3, Antje Schmidt-Pogoda3, and Cornelius Faber1,2 | ||
1Radiology, University Hospital Münster, Münster, Germany, 2Medical Faculty, Experimental Magnetic Resonance, Westfälische-Wilhelms-Universität Münster, Münster, Germany, 3Department of Neurology with Institute for Translational Neurology, University Hospital Münster, Münster, Germany |
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Ex vivo diffusion tensor imaging (DTI) was used to study the effects of motor training on interhemispheric connectivity after ischemic stroke in mice. Training increased the number of fibers of the corpus callosum by one third. No overall effect of lesion size on DTI parameters and general interhemispheric connectivity was observed. Trained animals with large lesions, however, had higher fiber counts and axial diffusivity compared to non-trained animals with similarly large lesions. A larger benefit of motor training on animals with more severe stroke is implied. |
| 4308 | Classification of bipolar patients using a macroscopic dispersion measure of the white matter tractogram | |
| Ali Demir1,2, Mehmed Özkan1, and Aziz Müfit Uluğ1,3 | ||
1Institute of Biomedical Engineering, Boğaziçi University, Istanbul, Turkey, 2Istanbul Medipol University, Istanbul, Turkey, 3Coretech Labs Inc., San Diego, CA, United States |
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Imaging based bio-markers are important in classification of psychiatric disorders for accurate diagnosis. We evaluated the performance of using a macroscopic dispersion measure of the white matter tractogram in the random forest classifier for identifying bipolar subjects. The macroscopic dispersion of the white matter tractogram enables increased performance of the bipolar/normal classification. Multidimensional scaling plots support that the macroscopic changes along the brain white matter improves the discrimination of bipolar and normal groups. |
| 4309 | Comparison of differences in brain structure area and differences through tractography analysis: patients with subclinical depression | |
| Sang Jin Im1, Jeong hwan Lee2, and Sie kyeong Kim3 | ||
1Gacheon University, Incheon, Korea, Republic of, 22Department of Psychiatry, Chungbuk National University College of Medicine, Cheongju, Korea, Republic of, 3Department of Psychiatry, Chungbuk National University College of Medicine, Cheongju, Korea, Republic of |
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Structural and functional changes in the subcortical area affect cognitive function and can cause increased vulnerability to mood symptoms such as anxiety and depression. However, studies on changes in subcortical structures show inconsistencies. This research shows the structural differences in segmented subcortical regions between control and depression groups and visualizes the pathway between structures according to the connection strength through tractography analysis to confirm functional differences. |
| 4310 | Diffusion MRI and fibertracking of brachial plexus to diagnose injury | |
| Nyoman Dana Kurniawan1, Jin Jin2, Clare Berry3, Wei Liu4, Aiman Al-Najjar1, Katie L McMahon5, Tom Lloyd6, Silvia Manzanero7, James Powell8, Michael Schuetz7, Trevor Gervais9, and Paul McEniery9 | ||
1Centre for Advanced Imaging, The University of Queensland, St Lucia, Australia, 2Siemens Healthcare, Brisbane, Australia, Brisbane, Australia, 3Metro North Hospital and Health Service, Brisbane, Australia, 4Application Department, Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen, China, 5School of Clinical Sciences, Queensland University of Technology, Brisbane, Australia, 6Department of Radiology, Princess Alexandra Hospital, Brisbane, Australia, 7Jamieson Trauma Institute, Metro North Hospital and Health Service, Brisbane, Australia, 8Orthopaedics Department, Royal Brisbane and Women’s Hospital, Brisbane, Australia, 9Orthopedics Department, Royal Brisbane and Women’s Hospital, Brisbane, Australia |
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We describe the utility, optimization of a diffusion weighted imaging protocol, and the post-processing for fibertracking reconstruction of the brachial plexus nerve at 3T using a prototype Simultaneous Multi-Slice RESOLVE Diffusion-Weighted Imaging (SMS RESOLVE DWI) sequence. Best tractography profile was obtained for the acquisition acquired at 2.7 mm isotropic 3D resolution, using 7 segmentations, and 30 diffusion encoding directions at b-value of 800 s/mm2, combined with tractography reconstruction using a probabilistic tensor algorithm. |
| 4311 | Fractional Anisotropy Thresholding for Deterministic Tractography of the Roots of the Brachial Plexus | |
| Ryckie George Wade1, Irvin Teh1, Gustav Andersson2, Fang-Cheng Yeh3, Mikael Wiberg2, and Grainne Bourke1 | ||
1University of Leeds, Leeds, United Kingdom, 2Umeå University, Umeå, Sweden, 3University of Pittsburgh, Pittsburgh, PA, United States |
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We acquired high-angular resolution DTI from 10 healthy adults. We investigated how altering the fractional anisotropy threshold changed tractograms and tract-related metrics. At thresholds above 0.06, the propagation of valid tracts reduced significantly. The fractional anisotropy thresholds required to generate valid tractograms of the roots of the brachial plexus are lower than thresholds conventionally used in the brain. We provide estimates of the probability of generating valid tracts for each spinal nerve root of the brachial plexus, at different fractional anisotropy thresholds. |
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High angular resolution diffusion MRI tractography-based thalamic parcellation of postmortem fetal brain in the second trimester | |
| Sheng-Min Huang1, Kuan-Hung Cho1, Koping Chang2, Pei-Hsin Huang2,3, and Li-Wei Kuo1,4 | ||
1Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Miaoli, Taiwan, 2Department of Pathology, National Taiwan University Hospital, Taipei, Taiwan, 3Graduate Institute of Pathology, National Taiwan University College of Medicine, Taipei, Taiwan, 4Institute of Medical Device and Imaging, National Taiwan University College of Medicine, Taipei, Taiwan |
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Proper fiber connections between cerebral areas are particularly essential to build brain functions. As a central relay, the thalamus plays an important role in regulating diverse brain functions. Here, we aimed to investigate the thalamo-cortical connections and thalamic parcellation of ex vivo fetal brains in the second trimester using high-resolution postmortem diffusion MRI tractography on 3T. Diffusion images with 333 µm isotropic voxel size were acquired and tractography-based thalamic parcellation was performed. The segregated thalamic patterns were found as similar as adult’s ones reported previously. Our results showed the thalamic development and demonstrated the capability of postmortem diffusion MRI tractography. |
| 4313 | Exploring the thalamus of the human brain using tractography analysis in 3Tesla MRI | |
| Sang Jin Im1 and Hyeon-Man Baek2 | ||
1Gacheon University, Incheon, Korea, Republic of, 2Lee Gil Ya Cancer and Diabetes Institute, Incheon, Korea, Republic of |
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Although there are discrepancies between studies, it can be deduced that the thalamus region has a clear effect on neurological disorders due to a strong relationship between the thalamus and neurological functions such as emotional control and processing. In this study, MPRAGE and DTI data were acquired using 3Tesla MRI, and thalamus regions were segmented by subdivisions based on the THOMAS atlas 4. In addition, tractography analysis was performed to investigate the connectivity between the thalamus subregions. |
| 4314 | Mapping white matter bundle tracts and cortical myelin from multi-contrast imaging in the awake macaque monkey | |
| Rakshit Dadarwal1,2, Fabien Balezeau3, Marcus Haag4, Michael C. Schmid3,4, Susann Boretius1,2, and Michael Oritz-Rios1,3 | ||
1Functional Imaging Laboratory, German Primate Center, Göttingen, Germany, 2Georg August Universität Göttingen, Göttingen, Germany, 3Biosciences Institute, Newcastle University, Newcastle upon Tyne, United Kingdom, 4Faculty of Science and Medicine, University of Fribourg, Fribourg, Switzerland |
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In-vivo whole-brain multi-contrast awake imaging enables the detection of structural and functional features in brain networks without anesthesia. In this work, we demonstrated the feasibility and robustness of multi-contrast MRI data acquisitions across sessions and subjects in awake macaque monkeys. |
| 4315 | Cognitive and motor topography of human dentate nuclei identified with tractography and clustering methods | |
| Fulvia Palesi1,2, Matteo Ferrante3, Marta Gaviraghi4, Anastasia Misiti4, Giovanni Savini5, Alessandro Lascialfari3, Egidio D'Angelo1,2, and Claudia A. M. Gandini Wheeler-Kingshott1,2,6 | ||
1Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy, 2Brain Connectivity Center Research Department, IRCCS Mondino Foundation, Pavia, Italy, 3Department of Physics, University of Pavia, Pavia, Italy, 4Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy, 5Advanced Imaging and Radiomics Center, Neuroradiology Department, IRCCS Mondino Foundation, Pavia, Italy, 6NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London (UCL), London, United Kingdom |
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The dentate nuclei (DNs) represent the main output relay of the cerebellum and yet are often unexplored especially in human studies. For the first time, we used both tractography and an unsupervised fuzzy c-means classification algorithm to identify DNs topography on the basis of their connectivity to cerebellar and cerebral areas as well as their microstructural features. Our findings indicate that DNs can be parcellated in two main areas: one predominant non-motor representation and one motor representation. Furthermore, connectivity-based and microstructure-based atlases provide complementary information. These results represent a step-forward that could help interpretating pathological conditions involving cerebro-cerebellar circuits. |
| 4316 | Patient specific tracts-based analysis of diffusion compartment models: application to multiple sclerosis patients with acute optic neuritis | |
| Olivier Commowick1, Renaud Hédouin1, Charlotte Laurent2, and Jean-Christophe Ferré1,3 | ||
1Univ Rennes, Inria, CNRS, Inserm, IRISA UMR 6074, Empenn - ERL U1228, Rennes, France, 2Ophthalmology department, CHU Rennes, Rennes, France, 3Radiology department, CHU Rennes, Rennes, France |
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Multiple sclerosis is a complex disease where voxel-based, group-based statistics of the brain microstructure have shown their limits in explaining patient evolution. This is first due to too simple diffusion models, mixing information. Voxel-based studies also lack knowledge on brain structural connectivity. Finally, group-based analysis does not describe well the specific patient status (a crucial point for clinicians). We propose an atlas-based framework, combined with advanced diffusion compartment models, for patient specific analysis of microstructural disease burden on major fiber bundles. We apply our framework to the analysis of optic radiations of MS patients with acute optic neuritis. |
| 4317 | Anatomical assessment of retinogeniculate visual pathway tractography: a comparison of multiple tractography methods | |
| Jianzhong He1,2, Fan Zhang2, Guoqiang Xie2,3, Shun Yao2,4, Yuanjing Feng1, Dhiego C.A. Bastos2, Yogesh Rathi2, Nikos Makris2, Ron Kikinis2, Alexandra J. Golby2, and Lauren J. O'Donnell2 | ||
1Zhejiang University of Technology, HangZhou, China, 2Harvard Medical School, Boston, MA, United States, 3Nuclear Industry 215 Hospital of Shaanxi Province, XianYang, China, 4The First Affiliated Hospital, GuangZhou, China |
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In this work, we investigate the performance of four widely used tractography methods (SD-Stream, iFOD1, UKF-1T, and UKF-2T) for the complete retinogeniculate visual pathway (RGVP) reconstruction. Anatomical measurement and expert judgement results indicate that UKF-2T and iFOD1 produce the best performance. The percentage of decussating fibers in the iFOD1 method was more similar to the known percentage from anatomical studies, while the UKF-2T method produced reconstructed RGVPs that were judged to better correspond to the anatomical course of the RGVP. |
| 4318 | Microstructural Properties of Major White Matter Tracts in Constant Exotropia before and after Strabismus Surgery | |
| Yanming Wang1, Xiaoxiao Wang1, Hongmei Shi2,3, Lin Xia2, Jiong Dong2, Benedictor Alexander Nguchu1, Jean De Dieu Uwisengeyimana1, Yanpeng Liu1, Du Zhang1, Lixia Feng2, and Bensheng Qiu1 | ||
1Hefei National Lab for Physical Sciences at the Microscale and the Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, China, 2Department of Ophthalmology, The First Affiliated Hospital of Anhui Medical University, Hefei, China, 3Department of Ophthalmology, The People's Hospital of Bozhou, Bozhou, China |
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This study apply AFQ, in conjunction with MRtrix3 and ConTrack, to identify 24 major white matter fiber bundles in HCs, patients with XT before and after strabismus surgery. Meanwhile, we evaluate ocular dominance (OD) and stereo acuity of post-operative patients. We found that microstructures (MD) of vision-related fibers changed after surgery. Moreover, these changes were associated with indicators of OD. We infer that microstructural changes of the visual spatially related fiber bundles might contribute to the restoration of stereopsis, and the balanced binocular input may be more conducive to the improvements and restoration of binocular visual function. |
| 4319 | TractLearn: comparison with the General Linear Model for optic pathways exploration | |
| Clement Jean1, Arnaud Attyé1,2, Alexandre Krainik1, Sylvie Grand1, Christophe Chiquet3, Olivier Casez4, Laurent Lamalle5, Felix Renard6, and Fernando Calamante2,7 | ||
1Neuroradiology, Grenoble University Hospital, Grenoble, France, 2School of Biomedical Engineering, The University of Sydney, Sydney, Australia, 3Ophthalmology, Grenoble University Hospital, Grenoble, France, 4Neurology, Grenoble University Hospital, Grenoble, France, 5IRMaGe, Inserm US 17, CNRS UMS 3552, Grenoble, France, 6Pixyl Medical, Grenoble, France, 7Sydney Imaging, Sydney, Australia |
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TractLearn was recently proposed for tract-based MRI quantitative analyses, based on Riemannian distances between anatomical structures. It allows to detect joint quantitative variations in a group of voxels, and in theory to decrease the number of false negatives compared with the General Linear Model (GLM). TractLearn also takes advantage of a manifold approach to capture controls variability as standard reference. Here we aim at comparing the performance of TractLearn with the GLM in detecting optic nerve voxel alteration, using the side of visual impairment as clinical reference. |
| 4320 | Tractography analysis of dopamine transporter genetic mouse models in Parkinson's disease | |
| Sang-Jin Im1 and Hyeon-Man Baek1 | ||
1Lee Gil Ya Cancer and Diabetes Institute, Incheon, Korea, Republic of |
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Parkinson's disease is characterized by degeneration of dopaminergic nigrostriatal neurons with dysfunctional cortico–striatal–thalamic loops mainly in the basal ganglia. However, Parkinson’s disease studies on the neural connections between brain structural regions have not reached a clear consensus on how Parkinson’s disease effects the mouse brain. In this study, probabilistic tractography analysis was performed on important mouse brain structures related to Parkinson's disease mechanism, and pathways between each domain were visualized. |
| 4321 | The frontal aslant tract and its role in executive functions: a lesion-symptom study and awake electrical mapping study | |
| Maud Landers1, Stephan Meesters2, Wouter de Baene3, and Geert-Jan Rutten1 | ||
1Department of Neurosurgery, Elisabeth TweeSteden Hospital, Tilburg, Netherlands, 2Department of mathematics and Computer Science, University of Technology, Eindhoven, Netherlands, 3Department of Cognitive Neuropsychology, University of Tilburg, Tilburg, Netherlands |
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Currently there is insufficient knowledge about the right frontal aslant tract’s exact cognitive importance. The aim of this study was to investigate the role of the right frontal aslant tract in executive functions via a lesion-symptom approach. The results suggest that the right frontal aslant tract is involved in shifting attention and phonemic fluency. As a follow-up the main findings were tested and validated in an awake mapping study where stimulation of the right frontal aslant tract lead to deficits in executive functioning. |