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| 4297
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SNR efficient diffusion imaging at 7T with B1+ mitigated multi-shot SMS-EPI, using semi adiabatic PINS RF and low-rank completion reconstruction | |
| SoHyun Han1, Rebecca E. Feldman2, Mary Kate Manhard3,4, Congyu Liao3,4, Seong-Gi Kim1, Priti Balchandani5, and Kawin Setsompop3,4 | ||
1Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, Korea, Republic of, 2Department of Computer Science, Mathematics, Physics, and Statistics, University of British Columbia, Kelowna, BC, Canada, 3Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States, 4Department of Radiology, Harvard Medical School, Boston, MA, United States, 5Biomedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States |
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B1+ inhomogeneity, SAR, and shortened T2-relaxation are the main challenges to leverage the higher SNR at ultra-high-field MRI. Here, we develop a new method by combining navigation-free multi-shot SMS-EPI with low-rank matrix completion reconstruction with semi-adiabatic PINS pulse for B1+ insensitive SMS imaging. Using this combined approach, we demonstrated mitigated B1+ inhomogeneity by comparing with conventional-SE pulse and the feasibility of low-rank completion reconstruction at high b-value. Finally, 1.2 mm isotropic whole-brain diffusion MRI was acquired across 64 diffusion directions with high-SNR in 11 minutes at 7T. |
| 4298 | Noninvasive Detection of Cell Membrane Permeability with Filter-Exchange Imaging | |
| Athanasia Kaika1,2, Mathias Schillmaier1,2, Geoffrey J. Topping1,2, and Franz Schilling1,2 | ||
1Technical University of Munich, Munich, Germany, 2Nuclear Medicine, Klinikum rechts der Isar, Munich, Germany |
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Filter-Exchange Imaging (FEXI) is a noninvasive double-diffusion imaging method, sensitive to transmembrane water exchange, which is strongly connected to cell viability. A FEXI sequence was implemented and tested in vitro with baker’s yeast. Upon permeabilization with ethanol, AXR increased whereas ADC decreased, more so with increasing ethanol concentration. AXR reduced over time, but only minor changes in ADC, intracellular volume and Trypan staining were detected. |
| 4299 | Rapid DTI-based free water elimination and mapping with explicit T2 modelling using a dual-echo Stejskal-Tanner EPI sequence | |
| Ezequiel Farrher1, Richard P. Buschbeck1, Kuan-Hung Cho2, Ming-Jye Chen2, Seong Dae Yun1, Zaheer Abbas1, Chang-Hoon Choi1, Li-Wei Kuo2,3, and N. Jon Shah1,4,5,6 | ||
1Institute of Neuroscience and Medicine 4, Forschungszentrum Jülich, Jülich, Germany, 2Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Miaoli, Taiwan, 3Institute of Medical Device and Imaging, National Taiwan University College of Medicine, Taipei, Taiwan, 4Department of Neurology, RWTH Aachen University, Aachen, Germany, 5JARA - BRAIN - Translational Medicine, Aachen, Germany, 6Institute of Neuroscience and Medicine 11, JARA, Forschungszentrum Jülich, Jülich, Germany |
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We propose and investigate a dual-echo (DE) Stejskal-Tanner EPI sequence for rapid DTI-based free water elimination and mapping with explicit T2 modelling (FWET2) in vivo. DTI maps from the DE sequence are artefact-free and similar to the standard, individual echo (IE) approach. Compared to the IE case, an underestimation of T2 values calculated from the DE sequence is observed. The T2 underestimation stems from reduced signal amplitudes in the second echo of the DE sequence, which we demonstrate to correlate with imperfect refocusing RF pulses. A simple correction method is proposed. FWET2 model parameters derived from both sequences are comparable. |
| 4300 | Time-dependent and anisotropic diffusion in the heart: linear and spherical tensor encoding with varying degree of motion compensation | |
| Samo Lasic1,2, Henrik Lundell2, Filip Szczepankiewicz3,4,5, Markus Nilsson3, Jürgen E. Schneider6, and Irvin Teh6 | ||
1Random Walk Imaging, Lund, Sweden, 2Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Copenhagen, Denmark, 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 |
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Spherical tensor encoding (STE) can potentially shorten acquisition of mean diffusivity (MD) compared to the traditional linear tensor encoding (LTE). To avoid negative effects of motion, e.g. in the heart, motion compensation is needed. However, motion compensation requires altering diffusion gradient waveforms and their sensitivities to time-dependent diffusion. To exclude motion, we first investigated LTE and STE with different degrees of motion compensation in ex vivo pig hearts. We observed significantly different MD, which can be attributed to time-dependent diffusion and microscopic diffusion anisotropy. Our analysis suggests that time-dependent diffusion is a critical determinant of MD in the myocardium. |
| 4301 | SENSE accelerated multishot spiral diffusion: application in brain on a clinical platform | |
| Maarten J. Versluis1, Kim van de Ven1, Velmurugan Gnanaprakasam1, Viswanath Kasireddy2, Suthambhara Nagaraj2, and Silke Hey1 | ||
1BIU MR, Philips Healthcare, Best, Netherlands, 2BIU MR, Philips Healthcare, Bangalore, India |
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In this study we compare SENSE accelerated multi-shot variable density spiral diffusion to the current clinical standards: single shot EPI and MultiVane TSE diffusion. A variable density sampling strategy was employed to correct for the phase of the different shots and iterative SENSE was used to reduce the number of shots and scanning duration. This technique was applied on a clinical platform with clinically acceptable reconstruction times. We showed that spiral diffusion reduces distortions in difficult to shim brain regions compared to ssh-EPI, and spiral diffusion has at a reduced scan duration compared to the TSE-based approach. |
| 4302 | Robust Diffusion-Weighted Imaging near Metallic Objects with Inner-FOV Single-Shot STEAM based on 2D-Selective RF Excitations | |
| Caspar Florin1 and Jürgen Finsterbusch1 | ||
1Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany |
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The potential of a single-shot stimulated echo acquisition mode (STEAM) sequence based on RF refocused echoes for DW imaging close to metallic objects is evaluated. It is optimized for spinal cord applications by combining it with inner-FOV technique based on 2D-selective RF (2DRF) excitations and half-Fourier sampling which improves its signal-to-noise ratio (SNR) efficiency significantly. Its robustness in the presence of metallic objects is investigated and compared to EPI showing a better performance with smaller regions suffering from signal losses. |
| 4303 | Simultaneous Acquisition of Dynamic Diffusion Imaging and Diffusion Tensor Imaging in the Brain | |
| Mihika Gangolli1, Wen-Tung Wang1, Neville Gai2, Dzung L. Pham1, and John Butman1,2 | ||
1Center for Neuroscience and Regenerative Medicine, Bethesda, MD, United States, 2National Institutes of Health, Bethesda, MD, United States |
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We propose a diffusion acquisition scheme, called “nested cubes”, consisting of five triplets of three unique mutually orthogonal directions, providing diffusion weighted data sampled across fifteen noncollinear directions distributed uniformly across a spherical shell. Data acquired using this setup facilitates the simultaneous acquisition of dynamic maps of trace and other diffusion metrics while producing DTI measurements comparable to those from a standard DTI sequence. |
| 4304 | Diffusion tensor imaging in human subjects wearing metallic orthodontic braces | |
| Xinyuan Miao1,2, Yuankui Wu1,2,3, Dapeng Liu1,2, Hangyi Jiang1, Qin Qin1,2, Peter C.M van Zijl1,2, Jay J. Pillai4,5, and Jun Hua1,2 | ||
1Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, 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 Medical Imaging, Nanfang Hospital, Southern Medical University, Guangzhou, China, 4Johns Hopkins University School of Medicine, Division of Neuroradiology, Russell H. Morgan Department of Radiology and Radiological Science, Baltimore, MD, United States, 5Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, United States |
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Metallic objects such as dental braces bring substantial susceptibility artifacts in MR images acquired using echo-planar-imaging (EPI) sequences. Here, we demonstrate that diffusion-prepared diffusion tensor imaging (DTI) with three-dimensional fast gradient-echo readout can significantly reduce susceptibility artifacts that are commonly seen in conventional spin-echo (SE) EPI DTI in the presence of metallic orthodontic braces. |
| 4305 | Reproducibility of Diffusion MRI Metrics Using 4-way Phase-Encoding Acquisition Design | |
| M. Okan Irfanoglu1, Neda Sadeghi2, Joelle Sarlls3, and Carlo Pierpaoli2 | ||
1QMI, NIBIB/NIH, Bethesda, MD, United States, 2NIBIB/NIH, Bethesda, MD, United States, 3NINDS/NIH, Bethesda, MD, United States |
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In this work, we assessed the reproducibility of diffusion MRI metrics w.r.t different experimental and acquisition designs within the same scan time limits. The design that employed identical diffusion gradients and b-values for blip-up phase-encoding and blip-down phase-encoding provided significant improvements in terms of data reproducibility compared to the design using a single b=0 blip-down image in terms of distortions. The proposed 4-way encoding scheme not only improved upon this design but also consistently reduced the effects of other imaging artifacts; therefore, is suggested to be the acquisition scheme of choice for dMRI studies where biological differences are subtle. |
| 4306 | Improving X-PROP with a more stable echo train for diffusion weighted MRI | |
| Zhiqiang Li1, Melvyn B Ooi1,2, and John P Karis1 | ||
1Neuroradiology, Barrow Neurological Institute, Phoenix, AZ, United States, 2Philips Healthcare, Gainesville, FL, United States |
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EPI-based DWI is widely used in the clinic but suffers from geometric distortions. DW-PROPELLER, based on FSE, is free from geometric distortions but has low scan efficiency. X-PROP was developed to improve FSE-based DW-PROPELLER scan efficiency by employing a GRASE readout. Although more efficient, XY2 phase modulation used in X-PROP is sensitive to the flip angles of the RF pulse train. This project improves X-PROP image quality by incorporating LRX phase modulation to increase SNR and signal stability. Image quality improvement was illustrated by comparing in vivo images produced with LRX phase modulation, XY2 phase modulation, and SPLICE PROPELLER imaging. |
| 4307 | Practical considerations of DW-MRS with ultra-strong diffusion gradients | |
| Christopher Jenkins1, Elena Kleban1, Lars Mueller1, John Evans1, Umesh Rudrapatna1, Derek Jones1, Francesca Branzoli2, Itamar Ronen3, and Chantal M.W Tax1 | ||
1CUBRIC, School of Psychology, Cardiff University, Cardiff, United Kingdom, 2Centre for NeuroImaging Research - CENIR, Brain and Spine Institute - ICM, Paris, France, 3Department of Radiology, Leiden University Medical Center, Leiden, Netherlands |
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Diffusion-weighted magnetic resonance spectroscopy benefits from the use of ultra-strong gradients. Slow diffusing metabolites necessitate a large range of b-values to accurately model the diffusion properties. Ultra-strong gradients open the possibility of higher b-values and reduced diffusion times, alleviating some of these constraints. We present initial data acquired with DW-PRESS on a 300mT/m gradient Connectom scanner, and introduce the practical considerations associated with ultra-strong gradients. |
| 4308 | 50-Fold Acceleration of Diffusion MRI via Slice-Interleaved Diffusion Encoding (SIDE) | |
| Yoonmi Hong1, Wei-Tang Chang1, Geng Chen2, Ye Wu1, Weili Lin1, Dinggang Shen1, and Pew-Thian Yap1 | ||
1University of North Carolina at Chapel Hill, Chapel Hill, NC, United States, 2Inception Institute of Artificial Intelligence, Abu Dhabi, United Arab Emirates |
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We present a sampling and reconstruction scheme that, when combined with multi-band imaging, accelerates dMRI acquisition by as much as 50 folds. In contrast to the conventional approach of acquiring a full diffusion-weighted (DW) volume for each diffusion wavevector, we acquire for each repetition time (TR) a volume consisting of interleaved slice groups, each corresponding to a different diffusion wavevector. This in effect results in a subsample of slices for each diffusion wavevector, based on which we can recover the full volumes for all wavevectors using a graph convolutional neural network (GCNN). |
| 4309 | Investigating the effect of diffusion MRI acquisition parameters on free water signal fraction estimates from 3-tissue CSD techniques | |
| Benjamin T Newman1,2, Thijs Dhollander3,4, and T. Jason Druzgal1,2 | ||
1Department of Radiology & Medical Imaging, Division of Neuroradiology, University of Virginia Health System, University of Virginia, Charlottesville, VA, United States, 2Brain Institute, University of Virginia, Charlottesville, VA, United States, 3The Florey Department of Neuroscience, University of Melbourne, Melbourne, Australia, 4The Florey Institute of Neuroscience and Mental Health, Melbourne, Australia |
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The CSF-like free water signal fraction is an advanced diffusion MRI metric representing the freely diffusing water in brain tissue. Different methods to calculate the free water signal fraction using constrained spherical deconvolution exist but it is still unknown how variation in data quality and acquisition affect measurements. Using a large clinical dataset with highly variable acquisition schemes, this study shows that the various acquisition parameters significantly affect outcome free water signal fraction, though the multi-shell analysis method is more susceptible than the single-shell method. This highlights the importance of harmonization and quality clinical imaging. |
| 4310 | Clinical Microscopic Fractional Anisotropy Imaging in 4 Minutes: an Optimization Approach | |
| Nico J. J. Arezza1,2, Desmond H. Y. Tse2, Aidin Arbabi2, and Corey A. Baron1,2 | ||
1Medical Biophysics, Western University, London, ON, Canada, 2Center for Functional and Metabolic Mapping, Robarts Research Institute, London, ON, Canada |
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Microscopic diffusion anisotropy ($$$\mu A$$$) and microscopic fractional anisotropy ($$$\mu FA$$$) quantify water diffusion anisotropy in tissue with no influence from neuron fiber orientation. Here, we characterized $$$\mu A^2$$$ signal-to-noise ratio using standard error propagation to determine the b-value and ratio of linear to isotropic encodings needed to maximize image quality. This optimization enabled an MRI protocol that utilizes efficient isotropic diffusion encoding to acquire high-quality full-brain $$$\mu A^2$$$ and $$$\mu FA$$$ maps in 2.4 and 4 minutes, respectively, which are demonstrated in two healthy volunteers at 3T. |
| 4311 | Novel practical SNR determination method for MRI using combined largest b-value and echo time (COLBET) | |
| Hirotaka Oyabu1, Tosiaki Miyati1, Naoki Ohno1, Toshifumi Gabata1, and Satoshi Kobayashi1 | ||
1Graduate School of Medical Sciences, Kanazawa University, Kanazawa, Japan |
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We developed a novel practical SNR measurement method using combined the largest b-value and echo time (COLBET). The COLBET method makes it possible to simply and practically perform image SNR quantitation including the long T2 region in human with parallel imaging. |
| 4312 | Investigating the reproducibility of 4th order Spherical Harmonics dMRI Rotation Invariant Features in White Matter | |
| Mauro Zucchelli1, Samuel Deslauriers-Gauthier1, and Rachid Deriche1 | ||
1Athena Project-Team, Inria Sophia Antipolis - Méditerranée, Université Côte d'Azur, Sophia Antipolis - Méditerranée, France |
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Rotation invariant features can potentially be used as biomarkers for diffusion MRI. One of the most important characteristics of biomarkers is their reproducibility. In the case of diffusion MRI, reproducibility means that if we acquire data from the same subject twice with a short time gap between the two acquisitions we should obtain the same values for the biomarkers. In this work, we investigate the reproducibility of 12 new rotation invariant features that we obtained from 4th order spherical harmonics. Our results suggest that the new invariants are reproducible and can be selected as biomarker-candidates for white matter. |
| 4313 | Whole-Tumor Histogram Analysis of Breast Lesions Based on Simultaneous Multi-slice Readout-segmented Echo-planar Imaging | |
| Xue Li1, Kun Sun1, Wei Liu2, Robert Grimm3, Caixia Fu2, and Fuhua Yan1 | ||
1Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China, 2Application Development, Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China, 3Application Predevelopment, Siemens Healthcare, Erlangen, Germany |
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This study compared the diagnostic performance of the ADC derived from the diffusion-weighted readout-segmented EPI DWI accelerated with SMS technique (SMS rs-EPI DWI) with that derived from the conventional rs-EPI DWI on breast lesions using whole-tumor histogram analysis. Our results showed that the SMS technique can increase the spatial resolution of the rs-EPI DWI sequence without prolonging the scan time. It can also improve the diagnostic performance of the derived ADC map based on whole-tumor histogram analysis in distinguishing benign and malignant breast lesions. |
| 4314 | Determination of the optimal set of b-values for Intravoxel Incoherent Motion (IVIM) parameter mapping in liver Diffusion-Weighted MRI | |
| Óscar Peña-Nogales1, Rodrigo de Luis-Garcia1, and Santiago Aja-Fernández1 | ||
1Laboratorio de Procesado de Imagen, Universidad de Valladolid, Valladolid, Spain |
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Estimation of Intravoxel Incoherent Motion (IVIM) parameter maps from a set of diffusion-weighted (DW) images acquired at multiple b-values usually suffers from low SNR, which may increase the variance of the estimated maps. Unfortunately, there is no consensus on the optimal b-values to maximize the noise performance of IVIM parameters. In this work, we determine the optimal b-values to maximize the performance of IVIM parameter mapping by using a Cramér-Rao Lower Bound approach under realistic noise assumptions. The reduction of the estimation variance on the IVIM parameters compared to state-of-the-art b-values suggests the utility of this approach to optimize DW-MRI. |
| 4315 | Intravoxel incoherent motion analysis of the brain with second-order motion-compensated diffusion encoding | |
| Naoki Ohno1, Tosiaki Miyati1, Tetsuo Ogino2, Yu Ueda2, Yuki Koshino1,3, Yudai Shogan1,3, Toshifumi Gabata4, and Satoshi Kobayashi1 | ||
1Faculty of Health Sciences, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa, Japan, 2Philips Japan, Tokyo, Japan, 3Radiology Division, Kanazawa University Hospital, Kanazawa, Japan, 4Department of Radiology, Kanazawa University Graduate School of Medical Sciences, Kanazawa, Japan |
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In this study, we compared diffusion parameters with intravoxel incoherent motion (IVIM) analysis of the brain between second-order motion-compensated (2nd-MC) and conventional (non-MC) diffusion encoding schemes. Perfusion-related diffusion coefficient with non-MC was strongly affected by bulk motion in the pons which has the largest motion in the brain. By contrast, the 2nd-MC diffusion gradients compensated the bulk motion-induced signal loss and improved the fitting accuracy of biexponential model. The 2nd-MC diffusion encoding reduces the bulk motion effect on IVIM analysis of the brain, thereby improving the measurement accuracy. |
| 4316 | Oscillating Gradient (OG) Prepared 3D-GRASE Sequence for Improved OG-Diffusion MRI | |
| Dan Wu1, Dapeng Liu2, Yi-Cheng Hsu3, Haotian Li1, Yi Sun3, Qin Qin2, and Yi Zhang1 | ||
1Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China, 2Johns Hopkins University School of Medicine, BALTIMORE, MD, United States, 3MR Collaboration, Siemens Healthcare Ltd., Shanghai, China |
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Oscillating gradient enables access of short diffusion times for time-dependent diffusion MRI (dMRI), but poses challenges for clinical use, including limited oscillating frequencies and b-values, low SNR, and relatively long scan times. This study proposes a 3D oscillating gradient prepared gradient spin-echo sequence (OGprep-GRASE) to improve the SNR and shorten the acquisition time for OG-dMRI. The proposed sequence reduced the scan time by a factor of 1.38 and increased the SNR by 1.74 times, compared with the existing 2D echo-planar imaging (EPI) approach, leading to improved diffusion tensor reconstruction. Diffusivity measurements showed similar time-dependency using the GRASE and EPI sequences. |
| 4317 | TGSE diffusion-weighted pulse sequence in the evaluation of optic neuritis: A comprehensive comparison of image quality with RESOLVE DWI | |
| Ting Yuan1, Yan Sha2, Zhongshuai Zhang3, Xilan Liu4, Xinpei Ye5, Yaru Sheng5, Kun Zhou6, and Caixia Fu6 | ||
1Shanghai Insititute of Medical Imaging, Shanghai, China, 2Eye & ENT Hospital of Shanghai Medical School, Fudan University, Shanghai, China, 3Siemens Healthcare Ltd, Shanghai, China, 4Department of Radiology, Shanghai Ninth People’s Hospital, Shanghai JiaoTong University, Shanghai, China, 5Department of Radiology, Eye & ENT Hospital of Shanghai Medical School, Fudan University, Shanghai, China, 6Department of Digitalization, Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China |
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This study investigated the role of RESOLVE and TGSE DWI sequences in the evaluation of optic neuritis and compared their image qualities qualitatively and quantitatively. We found that TGSE significantly improved the image quality for the evaluation of optic neuritis by reducing the susceptibility induced image distortion compared with RESOLVE. However, it appeared lower SNR and CNR than that of RESOLVE images. |
| 4318 | Automatic no-reference image quality evaluation of DWI in uterine malignancy at 3T with iShim, RESOLVE, and ss-EPI sequences – a feasibility study | |
| Qi Zhang1, Xiaoduo Yu1, Jieying Zhang1, Xinming Zhao1, Han Ouyang1, Hongmei Zhang1, Qinglei Shi2, Xiang Feng2, and Xiaoye Wang2 | ||
1Department of Imaging Diagnosis, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China, 2MR Scientific Marketing, Diagnostic Imaging, Siemens Healthcare Ltd, Beijing, China |
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This study proposed an automatic image quality evaluation method using no-reference image quality metrics of structural similarity index (SSIM), blind/referenceless image spatial quality evaluator (BRISQUE), perception based Image quality evaluator (PIQE), SNR Wavelet and Contrast. The SNR Wavelet was calculated by the quotient of the image before wavelet filtering and the difference between the image before wavelet filtering and the image after wavelet filtering. The contrast was calculated using the average signal difference of three to five gray bars in the middle position. This study showed the automatic no-reference image quality metrics have potentials in future application of evaluating the image quality of uterine malignancy DWI at 3T with a higher efficiency. |
| 4319 | Performance comparison of three b-value sampling schemes in multiple diffusion models, including DTI, DKI, NODDI and MAP-MRI | |
| Huiting Zhang1, Ankang Gao2, Shaoyu Wang1, Yang Song3, Jingliang Cheng2, Guang Yang3, and Xu Yan1 | ||
1MR Scientific Marketing, Siemens Healthcare, Shanghai, China, 2The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China, 3Shanghai Key Laboratory of Magnetic Resonance, East China Normal Univeristy, Shanghai, China |
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This study aimed to evaluate the performance of three b-value sampling schemes in calculating multiple diffusion models, including the DTI, DKI, NODDI and the newly proposed mean apparent propagator (MAP)-MRI models. The three schemes includes the conventional diffusion spectrum imaging (DSI) acquisition scheme based on Cartesian grid sampling in q-space, multi-shell sampling with the same (MDDW) or different (FREE) gradient directions in each shell. Each scheme supports the estimation of all the four models. The results showed that generally three schemes generated very similar parameters, and could be all used in future studies. |
| 4320 | Isotropic sampling for skewed encoding: novel rotation schemes for non-axisymmetric encoding objects in diffusion MRI | |
| Carl-Fredrik Westin1,2 and Filip Szczepankiewicz1,2 | ||
1Harvard Medical School, Boston, MA, United States, 2Brigham and Women's Hospital, Boston, MA, United States |
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In this work we propose novel sampling schemes for diffusion MRI required for encoding with objects with more than one directional axis. The presented solution is general and suitable for both axisymmetric and non-axisymmetric encoding schemes. An important feature of the presented sampling schemes is that they can be interleaved and be complimentary. This means that any combination of them can be used to define an isotropic sampling scheme with number of samples: (15, 30, 45, 60, 75, 90). |
| 4321 | Optimal experimental design for multi-tissue spherical deconvolution of diffusion MRI | |
| Jan Morez1, Jan Sijbers1, and Ben Jeurissen1 | ||
1imec-Vision Lab, Dept. Physics, University of Antwerp, Antwerp, Belgium |
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Multi-tissue constrained spherical deconvolution of multi-shell diffusion weighted MRI data estimates the white matter fiber orientation distribution function, together with the densities of gray matter and cerebrospinal fluid. In this work, we propose a 5-minute scanning protocol that allows a more precise estimation of WM and GM densities, while maintaining a high angular resolution. |
| 4322 | Ultra-high b-value single-shot echo planar diffusion-weighted imaging with Compressed SENSE | |
| Kayoko Abe1, Kazufumi Suzuki1, Masami Yoneyama2, and Shuji Sakai1 | ||
1Diagnostic Imaging and Nuclear Medicine, Tokyo Women's Medical University, Tokyo, Japan, 2Philips Japan, Tokyo, Japan |
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High b-value single-shot echo planar diffusion-weighted imaging (EPI-DWI) has been expected to provide more detail information about brain structure and diseases. However, higher b-value causes lower image quality due to an increase in noise-like artifacts. Compressed SENSE (C-SENSE), which is a combination of compressed sensing and parallel imaging technique: SENSE is an accelerating scan technique, which includes noise reduction methods. In this study, we revealed that EPI-DWI images with C-SENSE using high b-values (b:1000, 2000, 3000, 4000, 5000 s/mm2) showed higher SNR and ADC values than EPI-DWI images with SENSE. |
| 4323 | Q-Space Trajectory Imaging Using the MAGNUS High-Performance Head Gradient | |
| Grant Kaijuin Yang1,2, Ek Tsoon Tan3, Eric Fiveland4, Thomas Foo4, and Jennifer McNab2 | ||
1Electrical Engineering, Stanford University, Stanford, CA, United States, 2Radiology, Stanford University, Stanford, CA, United States, 3Hospital for Special Surgery in Manhattan, New York, NY, United States, 4GE Global Research, Niskayuna, NY, United States |
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In this work, q-space trajectory imaging was implemented on a whole-body system equipped with a high-performance head-only gradient system capable of 200 mT/m maximum gradient amplitude and 500 T/m/s slew rate. The improved gradient performance enabled the acquisition of q-space trajectory imaging with sub-millimeter in-plane resolution and reduced voxel volume compared to previously published work, while simultaneously improving head coverage, and reducing susceptibility induced image distortions. |
| 4324 | Implementation of a Diffusion-Weighted Echo Planar Imaging sequence using the Open Source Hardware-Independent PyPulseq Tool | |
| Rita G. Nunes1, Keerthi Sravan Ravi2, Sairam Geethanath2, and J. Thomas Vaughan Jr2 | ||
1Instituto Superior Técnico, Lisbon, Portugal, 2Columbia University Magnetic Resonance Research Center, New York, NY, New York, NY, United States |
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Diffusion-weighted imaging is an essential sequence for many clinical applications. While the post-processing tools for diffusion are widely available, vendor-neutral, open-source acquisition implementations have not been shared for research purposes. We develop a cross-vendor, open source package of a multi-slice single-shot spin echo-planar imaging based diffusion pulse sequence, capable of multiple b values and directions. We demonstrate this on an in vitro phantom, measuring plausible Apparent Diffusion Coefficient values and in vivo human brain data, obtaining good quality Fractional Anisotropy and Mean Diffusivity maps. We process our data with freely available post-processing tools to generate quantitative diffusion maps. |
| 4325 | Feasibility and evaluation of whole brain single-slab 3D DWI and comparison to 2D multi-slice DWI | |
| Neville D Gai1 and John A Butman1 | ||
1National Institutes of Health, Bethesda, MD, United States |
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While most brain imaging sequences now favor their 3D counterparts, diffusion imaging is an exception. This is due to large diffusion gradients resulting in increased sensitivity to motion exhibited by 3D acquisition. Prior schemes have used limited brain coverage and/or triggering or acquired multiple 3D slabs along with modified reconstruction schemes. The modified sequence used here employs first-order motion compensated diffusion gradients in addition to real-time alignment to acquire whole brain 3D-DWI images as a single slab. Relatively shorter TE (using enhanced gradients) and TR along with other modifications result in faster, reduced artifact diffusion images while providing higher SNR. |
| 4326 | Investigating restricted diffusion within different cortical regions using double-diffusion encoding | |
| Qiuyun Fan1, Thomas Witzel1, Slimane Tounekti1, Qiyuan Tian1, Chanon Ngamsombat1, Maya Polackal1, Aapo Nummenmaa1, and Susie Huang1 | ||
1Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States |
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We report the acquisition of whole brain, 2-mm isotropic resolution DDE data in a healthy volunteer using an orientationally invariant sampling scheme and quantify the mean DDE signal intensity across cortical regions as a measure of diffusion restriction within different cortices. Higher mean signal intensities were observed in the cerebellum and limbic cortices, which are thought to reflect a higher degree of restriction in the tissue microstructural environment and may correspond to densely packed, small granule and pyramidal cells known to be present in these regions. |
| 4327 | Radial diffusion-weighted MRI enables motion-robustness and reproducibility for orthotopic pancreatic cancer in mouse | |
| Jianbo Cao1, Stephen Pickup1, Hanwen Yang1, Victor Castillo1, Cynthia Clendenin2,3, Peter O’Dwyer2,3, Mark Rosen1,3, and Rong Zhou1,3 | ||
1Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States, 2Pancreatic Cancer Research Center, University of Pennsylvania, Philadelphia, PA, United States, 3Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, United States |
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Diffusion weighted (DW)-MRI is sensitive to tumor microenvironment (TME) thus useful for assessing pancreatic cancer responses to stroma-directed drugs, as they change TME by degradation or reduction of extracellular matrix. Motion-sensitive location of pancreatic tumor and fast respiration rate of mice impose a big challenge for quantitative DW-MRI. We compared radial k-space and echo-planar imaging based DW protocol for their accuracy and test-retest reproducibility. EPI-DW consistently underestimates water ADC value at 37C (reference to literature) where radial-DW does not. Better test-retest producibility measured by within-subject CV is obtained with radial-DW compared to EPI-DW. |
| 4328 | Correction for the influence of transmit-inhomogeneity in DW-SSFP on signal and ADC estimates in whole post-mortem brains at 7T | |
| Benjamin C Tendler1, Sean Foxley2, Moises Hernandez-Fernandez3, Michiel Cottaar1, Olaf Ansorge4, Saad Jbabdi1, and Karla Miller1 | ||
1Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom, 2Department of Radiology, University of Chicago, Chicago, IL, United States, 3Centre for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, United States, 4Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom |
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Diffusion-weighted steady-state free precession (DW-SSFP) generates high SNR diffusivity estimates in whole, post-mortem human brains. Improved estimates at 7T has motivated its use at ultra-high field. However, the DW-SSFP signal has a strong dependence on flip angle. This translates into both variable signal amplitude and diffusion contrast. At 7T, transmit-($$$B_{1}^{+}$$$) inhomogeneity leads to $$$B_{1}^{+}$$$-dependent SNR and ADC estimates. Previous work corrected for $$$B_{1}^{+}$$$-inhomogeneity by acquiring DW-SSFP datasets at two flip angles. Here, this approach is extended, utilising the full Buxton model of DW-SSFP to model non-Gaussian diffusion. A noise-floor correction and signal weighting are also incorporated to improve diffusivity estimates. |
| 4329 | Acceleration of multidimensional diffusion MRI data acquisition and post-processing using convolutional neural networks | |
| Yuan Zheng1, Tao Feng1, Sirui Li2, Wenbo Sun2, Qing Wei3, Samo Lasic4, Danielle van Westen5, Karin Bryskhe4, Daniel Topgaard4,5, and Haibo Xu2 | ||
1UIH America, Houston, TX, United States, 2Zhongnan Hospital of Wuhan University, Wuhan, China, 3United Imaging Healthcare, Shanghai, China, 4Random Walk Imaging, Lund, Sweden, 5Lund University, Lund, Sweden |
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Multidimensional diffusion MRI (dMRI) is a powerful tool that even in its simplest form provides more detailed microstructural information than conventional dMRI, such as microscopic anisotropy (µFA) unconfounded by orientation dispersion. However, it requires multiple diffusion encoding modes (usually directional and isotropic encodings) and, for the more advanced versions, prolonged scan and post-processing times. We proposed using convolutional neural networks (CNN) to accelerate multidimensional dMRI data acquisition and analysis, and have demonstrated that satisfactory µFA maps can be generated in real-time with only 50% of the encodings, which might help to better adapt multidimensional dMRI to clinical practices. |
| 4330 | Accelerating myelin-water imaging by extracting myelin content from anatomical and diffusion images through machine learning | |
| Gerhard S Drenthen1,2, Walter H Backes1, and Jacobus FA Jansen1,2 | ||
1Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, Netherlands, 2Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands |
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In this study we aim to accelerate the acquisition time of myelin-water imaging by acquiring fewer slices and applying machine learning to extract myelin-specific information from anatomical (T1w and T2w) and diffusion-weighted imaging (DWI), which are commonly available in many clinical research studies. It is shown that with a 6-fold acceleration (from 7:30min to 1:15min) the myelin content can be reconstructed using neural networks with an agreement to the ground-truth that is comparable to the reproducibility of the scan itself. |
| 4331 | Single-Shot Diffusion-Weighted Spatiotemporal Encoding (SPEN) using Polarities Average Mode (PAM) to Correct Spatial-Dependent b-Values | |
| Lisha Yuan1, Yi-Cheng Hsu2, Dan Wu1, Hongjian He1, and Jianhui Zhong1,3 | ||
1Center for Brain Imaging Science and Technology, Department of Biomedical Engineering, Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, China, 2MR Collaboration, Siemens Healthcare Ltd., Shanghai, China, 3Department of Imaging Sciences, University of Rochester, Rochester, NY, United States |
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Compared to traditional echo-planar imaging (EPI)-based schemes, spatiotemporal encoding (SPEN) is largely insensitive to magnetic field and chemical shift heterogeneities. However, excitation gradient has different effects for each position, thus the interaction between imaging and diffusion gradients introduces spatial-dependent diffusion weightings along the SPEN axis. A new method named polarities average mode (PAM) was proposed to obtain accurate apparent diffusion coefficient (ADC) map, with two acquisitions of different polarities between excitation and diffusion gradients. Simulation, phantom, and human experiments were designed to assess method performance. The proposed method enables SPEN to obtain ADC maps easily and accurately. |
| 4332 | Feasibility Study of applying Simultaneous Multi-slice technique in Diffusion Weighted Imaging of Breast Lesions | |
| Fei Wang1, Mengxiao Liu2, and Juan Zhu1 | ||
1Department of MRI,AnQing Municipal Hospital, Anqing, China, 2MR scientific Marketing, Diagnostic Imaging, Siemens Healthcare Ltd, Shanghai, China |
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To evaluate the feasibility of applying simultaneous multi-slice (SMS) single-shot echo planar imaging (EPI) to accelerate MR diffusion imaging for breast carcinoma, fibroadenoma of breast and normal breast. SMS sequences with double and triple acceleration were compared with conventional DWI sequences, respectively. These SMS DWI sequences were compared to conventional DWI in terms of image quality parameters (5-point Likert scale) and SNR, ADC measurements. Comparing with conventional EPI-DWI, the SMS markedly reduces the diffusion scan time and the image SNR still shows a good quality. Thus, SMS technique is recommended for DWI of the MR breast examinations. |
| 4333 | The Use of Stimulated-Echo EPI to Obtain High b-Value DTI Data at Short TEs on a Clinical Scanner | |
| R. Allen Waggoner1, Thorsten Feiweier2, and Keiji Tanaka1 | ||
1Laboratory for Cognitive Brain Mapping, RIKEN - Center for Brain Science, Wako-shi, Japan, 2Siemens Healthcare GmbH, Erlangen, Germany |
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On clinical scanners, high b-value diffusion studies using SE-EPI suffer from the need for long TEs, which leads to signal loss due to T2 decay. Stimulated-Echo EPI permits high b-values together with short TEs on clinical scanners. We demonstrate that tractograms obtained from high b-value STE-EPI images are clean even in regions where tractograms from SE-EPI images with the same b-values break down. |
| 4334 | Evaluating Diffusion Kurtosis Imaging Precision at Varying Gradient Strength in High Spatial Resolution 3T MRI | |
| Loxlan W Kasa1, Terry Peters2, Roy AM Haast3, and Ali R Khan4 | ||
1School of Biomedical Engineering, Imaging Research Laboratories, Robarts Research Institute, Western University, LONDON, ON, Canada, 2Imaging Research Laboratories, Robarts Research Institute, School of Biomedical Engineering,,Department of Medical Biophysics,Departments of Medical Imaging, Western University, London, ON, Canada, 3Imaging Research Laboratories, Robarts Research Institute, Western University, London, ON, Canada, 4Imaging Research Laboratories, Robarts Research Institute, School of Biomedical Engineering, Department of Medical Biophysics, Western University, London, ON, Canada |
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Diffusion kurtosis imaging (DKI), an extension to diffusion tensor imaging (DTI), aims to improve quantification of the hindered/restricted diffusion pattern due to microstructural complexity in the brain. But in order to capture the non-Gaussian diffusion behaviour of water molecules in biological tissues, stronger gradients larger than those employed in standard diffusion weighted imaging (DWI) are required. Here, we explored the test-retest reliability of DKI derived metrics with respect to different gradient strength in a high spatial resolution dataset. It was observed that DKI precision was comparable between b-value=1000, 2000, 3000 s/mm2 and b-value=1000 & 3000 s/mm2 dataset. |
| 4335 | Comparison of iShim, RESOLVE, and ss-EPI diffusion-weighted MR imaging with high b value at 3T MR in the evaluation of uterine malignancy | |
| Qi Zhang1, Jieying Zhang1, Xiaoduo Yu1, Han Ouyang1, Xinming Zhao1, Hongmei Zhang1, Qinglei Shi2, Xiang Feng2, and Xiaoye Wang2 | ||
1Department of Imaging Diagnosis, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China, 2MR Scientific Marketing, Diagnostic Imaging, Siemens Healthcare Ltd, Beijing, China |
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In the evaluation of uterine malignancy, conventional DWI based on single-shot echo-planar imaging (ss-EPI) is prone to imaging artifacts, including susceptibility artifacts from gas, imaging blurring, which limit its diagnostic value, especially in detecting and staging uterine malignancy. The purpose of this study is to compare the detection of uterine malignancy and image quality among DWI based on integrated slice-specific dynamic shimming (iShim), readout segmentation of long variable echo trains (RESOLVE) and ss-EPI sequence. Our results indicated that iShim DWI showed better image quality than ss-EPI and RESOLVE DWI in the terms of subjective image scores and objective quantitative metrics. |
| 4336 | Evaluation of simple acceleration strategy for advanced neural diffusion models based on half q-space under-sampling | |
| Min-xiong Zhou1, Huiting Zhang2, Yang Song3, Guang Yang3, and Xu Yan2 | ||
1Shanghai University of Medicine & Health Sciences, Shanghai, China, 2MR Scientific Marketing, Siemens Healthcare, Shanghai, China, 3Shanghai Key Laboratory of Magnetic Resonance, East China Normal Univeristy, Shanghai, China |
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Advanced diffusion models such as NODDI, MAP-MRI are of high interests in brain research, but suffer from long acquisition time. Advanced under-sampling scheme were reported in previous studies for acceleration but are not commercially available. This study evaluates a simple and commercial available under-sampling scheme using the symmetric property of q-space, which could accelerate the acquisition by 2 fold. Results showed that it did not significant sacrifice the accuracy of quantitative maps. In addition, a symmetrically data copy step is needed to improve the estimation accuracy for both MAP-MRI and NODDI models. |
| 4337 | Readout-Segment Echo-Planar Imaging of Prostate, a Strategy to Reduce Geometrical Distortion in Prostate Diffusion Weighted Imaging | |
| Melina Hosseiny1, KyungHyun Sung1, Teeravut Tubtawee1, Voraparee Suvannarerg1, Shabnam Mortazavi1, Soheil Kooraki1, Saurab Gupta1, Afshin Azadikhah1, Justin Ching1, Ely R Felker1, David Lu1, and Steven S Raman1 | ||
1Abdominal Radiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States |
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Single-Shot Echo-Planar Imaging (ssEPI)is highly susceptible to T2* blurring and geometrical distortion. This study aimed to compare the image quality between ssEPI and Readout-Segment Echo-Planar Imaging (rsEPI) for acquiring prostate DWI on 162 patients. Geometrical distortion was ranked on ssEPI and rsEPI using a five-point scale. The geometrical distortion was significantly less observed in rsEPI compared to ssEPI (P<0.01). Geometrical distortion scores of three and higher were observed in 30 individuals in ssEPI, with all having scores < 3 on rsEPI. In conclusion, using rsEPI for DWI acquisition may augment or replace ssEPI on 3T prostate mpMRI. |
| 4338 | DTI in early RRMS patients with correlation to clinical parameters and comparison to Healthy Controls | |
| Abdulaziz Alshehri1,2, Oun Al-iedani1,2, Jameen Arm1,2, Neda Gholizadeh1, Rodney Lea3, Jeannette Lechner-Scott3,4,5, and Saadallah Ramadan1,2 | ||
1School of Health Sciences, University of Newcastle, Newcastle, Australia, 2Imaging center, Hunter Medical Research Institute, Newcastle, Australia, 3Hunter Medical Research Institute, Newcastle, Australia, 4School of Medicine and Public Health, University of Newcastle, Newcastle, Australia, 5Department of Neurology, John Hunter Hospital, Newcastle, Australia |
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This study aims to evaluate and compare DTI parameters in relapsing-remitting MS patients with age and sex-matched healthy controls, and to correlate these DTI metrics with clinical symptoms and brain volumetric measures. As a result, There was a statistically significant increase in most of DTI parameters for RRMS patients compared with healthy controls. FA correlated positively with clinical parameters like EDSS and cognitive assessment. Both MD and RD correlated negatively with cognition parameters and positively with EDSS. Quantitative DTI parameters not only differentiate between RRMS patients and HCs, but are also associated with disability and mental health of RRMS. |
| 4339 | SENSE-based Multi-shot DWI Reconstruction with Extra-navigated Rigid Motion and Contrast Correction for Brain EPI | |
| Malte Steinhoff1, Alfred Mertins1, and Peter Börnert2,3 | ||
1Institute for Signal Processing, University of Luebeck, Luebeck, Germany, 2Philips Research Europe, Hamburg, Germany, 3Department of Radiology, LUMC, Leiden, Netherlands |
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We propose an extra-navigated SENSE-based multi-shot DWI reconstruction algorithm that comprises navigator-based phase and rigid in-plane motion corrections at fast reconstruction times. Furthermore, this approach exploits the low-resolution navigator signal to perform diffusion contrast corrections explicitly within the model. The extra-navigated method is compared in-vivo to a self-navigated reference algorithm. The extra-navigated motion estimation from low-resolution navigator data yields decent reconstructions which perfectly coincide with self-navigated results. Moreover, extra-navigation allows for fast reconstruction at the cost of lower scan efficiency and appears to be more robust for strong motion corruption and high segmentations. |
| 4340 | Diffusion Weighted Imaging using PROPELLER Acquisition and a Deep Learning based Reconstruction | |
| Xinzeng Wang1, Daniel Litwiller2, Ali Ersoz3, Marc Lebel4, Sagar Mandava5, Lloyd Estkowski3, Arnaud Guidon6, Ann Shimakawa7, and Ersin Bayram1 | ||
1Global MR Applications & Workflow, GE Healthcare, Houston, TX, United States, 2Global MR Applications & Workflow, GE Healthcare, New York, NY, United States, 3Global MR Applications & Workflow, GE Healthcare, Waukesha, WI, United States, 4Global MR Applications & Workflow, GE Healthcare, Calgary, AB, Canada, 5Global MR Applications & Workflow, GE Healthcare, Tucson, AZ, United States, 6Global MR Applications & Workflow, GE Healthcare, Boston, MA, United States, 7Global MR Applications & Workflow, GE Healthcare, Menlo Park, CA, United States |
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PROPELLER DWI, a FSE based DWI method, is increasingly used to reduce susceptibility artifacts and motion artifacts. Multi-shot Echo-Planar diffusion method also can reduce susceptibility artifacts, but PROPELLER DWI shows better image quality where susceptibility artifacts are most problematic, such as in skull base, head-neck and pelvis. However, the acquisition time is often longer compared to ms-DW-EPI, therefore SNR is usually compromised to reduce acquisition time. In this work, we evaluated a deep-learning based reconstruction method (DL Recon PROP) intended to improve image quality and ADC measurements by reducing the noise and artifacts without increasing acquisition time. |
| 4341 | Model-Free, Fast, and Automated Correction of Diffusion Gradient Orientations | |
| Ye Wu1, Yoonmi Hong1, Weili Lin1, Pew-Thian Yap1, and the UNC/UMN Baby Connectome Project Consortium1 | ||
1Department of Radiology and BRIC, University of North Carolina, Chapel Hill, Chapel Hill, NC, United States |
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We propose a rapid and automated method to rectify incorrect gradient orientations resulting from inconsistencies in coordinate frame conventions across scanners, file formats, and processing tools. Using these incorrect gradient orientations will invalidate subsequent derived quantities that are dependent on local orientation information, particularly tractography. Our approach to correcting the gradient orientations is based on maximizing an orientation continuity index that is computed directly from the diffusion-weighted images without the need for model fitting. |
| 4342 | High-resolution distortion-free single-shot EPI enabled by deep-learning | |
| Zhangxuan Hu1, Zhe Zhang2, Yishi Wang3, Yajing Zhang4, and Hua Guo1 | ||
1Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China, 2China National Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China, 3Philips Healthcare, Beijing, China, 4MR Clinical Science, Philips Healthcare (Suzhou), Suzhou, China |
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Single-shot EPI (SS-EPI) is widely used for diffusion-weighted imaging (DWI), but suffers from susceptibility-induced distortion and T2* blurring, which limit its resolution and ability to detect detailed structures. Parallel imaging and multi-shot techniques can be used to improve the resolution and reduce image distortion. However, these techniques have their own drawbacks, such as limited achievable acceleration factors or prolonged acquisition time. In this study, a deep-learning based method is proposed to achieve high-resolution distortion-free DWI using SS-EPI thus to improve the acquisition efficiency and clinical applicability. |
| 4343 | Segmented Diffusion Imaging with Iterative Motion Corrected Reconstruction for Self-navigated Brain Echo-planar Imaging at 7T | |
| Malte Steinhoff1, Itamar Ronen2, Andrew Webb2, Alfred Mertins1, and Peter Börnert2,3 | ||
1Institute for Signal Processing, University of Luebeck, Luebeck, Germany, 2Department of Radiology, LUMC, Leiden, Netherlands, 3Philips Research Europe, Hamburg, Germany |
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Segmented diffusion imaging with iterative motion corrected reconstruction (SEDIMENT) is studied at 7T for self-navigated multi-shot DWI reconstruction including rigid in-plane motion correction. Motion-corrupted datasets contain intra-shot motion corrupted data with imperfect diffusion-sensitizing gradient reversal, which have to be identified and removed. The iterative SEDIMENT framework is evaluated in-vivo in conjunction with tailored data rejection strategies to detect corrupted shot datasets and generally improve convergence. The proposed algorithm provides high-quality multi-shot DWI and DTI reconstructions in the presence of gross motion allowing for efficient navigator-free DWI acquisition schemes. |
| 4344 | NoiseFactors: Blind Denoising of dMRI via Randomized Factor Models | |
| Shreyas Fadnavis1, Hu Cheng2, and Eleftherios Garyfallidis1 | ||
1Intelligent Systems Engineering, Indiana University Bloomington, Bloomington, IN, United States, 2Psychological and Brain Sciences, Indiana University Bloomington, Bloomington, IN, United States |
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NoiseFactors is a probabilistic graphical model to suppress and remove additive noise in a single DWI image. It mitigates the issues caused by noise by preserving correlations in the signal components and suppressing the uncorrelated noise within local neighbourhoods. We solve the low-rank approximation problem by learning a best m-component approximation of a factor model. To do so we also introduce a novel flipped bi-crossvalidation to estimate the factor model. It outperforms the state-of-the-art PCA based methods such as Marchenko-Pastur PCA and Local PCA. The proposed method for denoising will be made available with an open-source implementation in DIPY. |
| 4345 | Phase-Constrained Reconstruction of High-Resolution Multi-shot Diffusion Weighted Image | |
| Yiman Huang1, Xinlin Zhang1, Hua Guo2, Huijun Chen2, Di Guo3, and Xiaobo Qu1 | ||
1Department of Electronic Science, Xiamen University, Xiamen, China, 2School of Medicine, Tsinghua University, Beijing, China, 3School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, China |
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Multi-shot DWI improves the image resolution, while it induces phase variation at the same time. We introduce a smooth phase constraint of each shot image into multi-shot DWI reconstruction procedures by imposing the low-rankness of Hankel matrix constructed from the k-space data. The image is further improved with a partial sum of singular values in low-rank matrix reconstruction. Results on brain imaging data show that the proposed method outperforms the state-of-the-art methods in terms of artifacts removal and is compatible to partial Fourier sampling in accelerated DWI. |
| 4346 | Joint estimation of phase and diffusion tensor parameters from multi-shot k-q-space data: a proof of concept | |
| Banafshe Shafieizargar1, Ben Jeurissen1, Arnold Jan den Dekker1, and Jan Sijbers1 | ||
1imec-Vision Lab, Department of Physics, University of Antwerp, Antwerp, Belgium |
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To address the issue of phase induced artifacts in multi-shot diffusion weighted imaging, we propose a model-based framework which enables the joint estimation of diffusion and phase parameters directly from the multi-shot k-q-space. In a simulation study, we show that using this framework, diffusion parameters can be estimated more accurately and precisely than with the conventional method (image reconstruction followed by voxel-wise model fitting) that ignores phase differences. |
| 4347 | Distortion Correction for Isotropic High-Resolution Diffusion Imaging Using 3D Simultaneous Multi-Slab (SMSlab) Acquisition | |
| Simin Liu1, Yuhui Xiong1,2, Erpeng Dai1,3, Jieying Zhang1, and Hua Guo1 | ||
1Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China, 2Neusoft Medical Systems Co., Ltd., Shanghai, China, 3Department of Radiology, Stanford University, Stanford, CA, United States |
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In EPI-based diffusion imaging, the geometric distortions become more severe with increased image resolution. Various post-processing methods have been proposed to correct for distortions, such as the top-up method and the field-mapping method. Nonetheless, for 3D isotropic high-resolution diffusion imaging, distortion correction becomes more challenging due to decreased SNR. In this study, we applied a modified distortion correction method, which was previously proposed for 2D imaging, to isotropic high-resolution diffusion imaging using 3D simultaneous multi-slab (SMSlab) acquisition. The modified distortion correction method performed well in both phantom and in vivo experiments. It also outperformed the conventional top-up and field-mapping methods. |
| 4348 | Rapid, structure-preserving denoising of DTI data via tight framelet thresholding. | |
| Gregory R. Lee1,2 | ||
1Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States, 2Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, United States |
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In this work it is demonstrated that computationally efficient deniosing can be done using thresholding of wavelet coefficients without sacrificing image quality relative to state-of-the-art patch-based methods. This is achieved by combining use of a redundant, directional tight wavelet frame with the Karhunen-Loeve transform along the "directions" dimension. An efficient GPU implementation of the algorithm required less than 30 seconds to process even relatively large DTI datasets (e.g. 96x96x60x203). The proposed approach should find use in SNR-challenged acquisitions such high resolution DTI, DKI and DSI. |
| 4349 | Automated Identification of Non-Brain Voxels for Clean Brain Extraction Using Diffusion MRI | |
| Ye Wu1, Yoonmi Hong1, Weili Lin1, Pew-Thian Yap1, and the UNC/UMN Baby Connectome Project Consortium1 | ||
1Department of Radiology and BRIC, University of North Carolina, Chapel Hill, Chapel Hill, NC, United States |
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Automated brain extraction using diffusion MRI is challenging owing to the low spatial resolution. Unremoved residual non-brain voxels characteristically manifest as voxels with high fractional anisotropy (FA). In this abstract, we introduce a fast and robust method to identify non-brain voxels for clean extraction of the brain using diffusion MRI. We show that our method is effective for both adult and infant data. |
| 4350 | A low-rank based reconstruction method for diffusion-weighted point-spread-function encoded EPI (PSF-EPI) | |
| Xinyu Ye1, Guangqi Li1, Yuan Lian1, Yishi Wang2, and Hua Guo1 | ||
1Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China, 2Philips Healthcare, Beijing, China |
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Recently, a distortion- and blurring-free acquisition method called PSF-EPI has been used in DWI. However, when field inhomogeneity is severe, DW images may become noisy and more shots are needed to get the reliable results. In this work, we introduce a low-rank based reconstruction method using signal correlation along the ky-encoding dimension in PSF-EPI to improve image quality and reduce needed shot number to shorten scan time. High-resolution in-vivo data were used to test the performance of the proposed method. The results show that the quality of the images is improved. |
| 4351 | Deep learning-based partial Fourier reconstruction for improved prostate DWI | |
| Fasil Gadjimuradov1,2, Seung Su Yoon1,2, Thomas Benkert2, Marcel Dominik Nickel2, Karl Engelhard3, and Andreas Maier1 | ||
1Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany, 2Magnetic Resonance, Siemens Healthcare GmbH, Erlangen, Germany, 3Department of Radiology, Martha-Maria Hospital, Nürnberg, Germany |
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Partial Fourier (PF) acquisition schemes are a common way to increase the inherently low signal-to-noise ratio in diffusion-weighted (DW) images. The naïve solution of zero-filling k-space results in visible blurring and Gibbs ringing. Based on the circumstance that traditional methods such as homodyne reconstruction or POCS often fail to remove blurring and ringing without introducing new artifacts, this work aims to use a Convolutional Neural Network for robust PF reconstruction in prostate DWI. We show that our data-driven approach, which efficiently uses correlations across different b-values, outperforms traditional methods in terms of quantitative measures and visual impression of the images. |
| 4352 | Acceleration of diffusion ADC mapping with phase-corrected SUPER | |
| Xin Tang1, Jun Xie2, Guobin Li2, Meng Jiang3, and Chenxi Hu4 | ||
1Department of Medical Information Engineering, Wuyuzhang honors college, Sichuan University, Chengdu, China, 2United Imaging Healthcare Co., Ltd, Shanghai, China, 3Department of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China, 4Institute of Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China |
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A novel method was proposed to accelerate apparent-diffusion-coefficient(ADC) mapping to shorten the EPI echo-train and/or improve resolution. The method was based on SUPER--a Cartesian k-space undersampling strategy for parametric mapping acceleration—and adapted to account for the nonlinear phase variation in diffusion-weighted imaging at different b-values. In healthy subjects, the phase-corrected SUPER(R=2) and SUPER-SENSE(combining SUPER and parallel imaging, R=4) demonstrated similar image quality, reasonable noise amplification, and similar reconstruction time compared with the non-acceleration gold standard, despite a 2-fold and 4-fold reduction of reconstruction data. This suggests that SUPER is a practical and accurate approach for accelerating ADC mapping. |
| 4353 | Practical correction of gradient nonlinearity bias for mean diffusion kurtosis model parameters | |
| Dariya Malyarenko1 and Thomas L Chenevert1 | ||
1University of Michigan, Ann Arbor, MI, United States |
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Quantitative tissue diffusion parameters derived from diffusion weighted imaging (DWI) models hold promise for diagnostic and prognostic clinical oncology applications. System-dependent spatial DW bias due to gradient nonlinearity (GNL) is known confounding factor for quantitative DWI metrics. Improved accuracy and multiplatform reproducibility was previously demonstrated for mono-exponential apparent diffusion coefficient with correction for platform-dependent GNL bias (GNC). Complex tumor microenvironment often exhibits multi-exponential diffusion described by isotropic kurtosis model. This study proposes analytical extension and demonstrates empirical confirmation for GNC of parametric maps derived from diffusion kurtosis model. |
| 4354 | Interleaved Block-Segmented Echo-Planar Imaging (iblocks-EPI) based Diffusion-Tensor Imaging with Retrospective Motion Correction | |
| Liyuan Liang1, Mei-Lan Chu2, Nan-Kuei Chen3,4, Shihui Chen1, and Hing-Chiu Chang1 | ||
1Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, China, 2Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan, 3Department of Biomedical Engineering, University of Arizona, Tucson, AZ, United States, 4Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, United States |
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Recently, a self-navigated interleaved block-segmented EPI (iblocks-EPI) has been proposed to acquire DTI data with high spatial resolution and less geometric diction. In addition, the oversampling of central k-space of iblock-EPI can benefit the SNR performance. However, same as the other multi-shot EPI techniques, iblocks-EPI is highly susceptible to minuscule and macroscopic motions during data acquisition. In this study, we developed a self-calibrated and collaborative iblocks-DTI reconstruction framework that can correct image artifacts and diffusion-encoding contrast change caused by minuscule and macroscopic motions. |
| 4355 | Use of 2D image registration parameters for correction of eddy-current magnetization-density ADC errors in presence of gradient nonlinearity | |
| Thomas L. Chenevert1 and Dariya I. Malyarenko1 | ||
1University of Michigan Hospitals, Ann Arbor, MI, United States |
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Systematic errors confound wide-spread clinical use of apparent diffusion coefficient (ADC) for diagnostic and prognostic applications. Standard clinical diffusion sequences using single-spin-echo echo-planner-imaging are susceptible to gradient channel-specific eddy-currents for b>0 inducing distortions of voxel magnetization-density (MD), as well as geometric distortion. Unlike geometric distortion that are largely correctable by image registration to b=0, persisting signal amplitude distortions lead to systematic spatially-dependent errors mimicking, but physically distinct from, non-uniform diffusion weighting induced by gradient nonlinearity (GNL). This study proposes the use of geometric distortion parameters derived from in-plane image registration for MD correction of ADC in presence of GNL. |
| 4356 | Accelerating Navigator-free Multi-shot Spiral DTI via Joint Calibrationless Reconstruction with Low-Rank Tensor Completion | |
| Xiaodong Ma1,2, Yilong Liu1,2, Zheyuan Yi1,2,3, Alex T. Leong1,2, Hua Guo4, and Ed X. Wu1,2 | ||
1Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong, China, 2Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China, 3Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China, 4Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China |
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We propose a novel joint calibrationless reconstruction for accelerating multi-shot navigator-free DTI, using a low-rank completion approach. The redundant information across different directions is utilized to facilitate the reconstruction, including sharable coil sensitivities and anatomical structures. A 3D Hankel tensor was constructed and its concatenated Hankel matrices were used for low-rank approximation. In vivo human brain DTI experiment shows that the proposed joint reconstruction can reduce artifacts in diffusion-weighted images, and yield more accurate DTI metrics, when compared with separate reconstruction for different directions. This method also presents a new potential reconstruction strategy for fast high-resolution DTI. |
| 4357 | PROPELLER Diffusion-Weighted Imaging of the Prostate with Deep-Learning Reconstruction | |
| Xinzeng Wang1, Ersin Bayram1, Daniel Litwiller2, Tetsuya Wakayama3, Alan B McMillan4, Lloyd Estowski5, Ty A Cashen5, and Ali Pirasteh4 | ||
1Global MR Applications & Workflow, GE Healthcare, Houston, TX, United States, 2Global MR Applications & Workflow, GE Healthcare, New York, NY, United States, 3Global MR Applications & Workflow, GE Healthcare, Hino, Japan, 4Radiology, University of Wisconsin Madison, Madison, WI, United States, 5Global MR Applications & Workflow, GE Healthcare, Waukesha, WI, United States |
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While echo-planar diffusion-weighted imaging (EP-DWI) is the main sequence for cancer detection in the prostate peripheral zone, it is susceptible to signal loss and distortion due to B0-field inhomogeneities secondary to a variety of causes, including rectal gas or metal hardware in the pelvis. We were able to demonstrate that a spin-echo based DWI sequence with radial k-space sampling (PROPELLER) can overcome such artifacts and the addition of a deep-learning reconstruction algorithm can overcome the poor signal-to-noise (SNR) profile of the PROPELLER-DWI, overall generating images with minimal-to-no appreciable artifact and favorable SNR. |
| 4358 | Towards individual direction-based deep learning of diffusion weighted images for standard diffusion model analysis. | |
| Peidong He1, Zifei Liang1, Marco Muccio1, Florian Knoll1, Jiangyang Zhang1, and Yulin Ge1 | ||
1Department of Radiology, New York University School of Medicine, New York, NY, United States |
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In diffusion MRI, a higher number of gradient directions benefit to SNR and robustness of fiber rotational invariant estimation for tensor computation, however, it makes the acquisition time to lengthy to be clinically viable. This study was to apply a deep learning approach to generate new individual direction diffusion weighted (DW) source images (e.g., 60 more directions) from original 30 direction DW images based on high-angular-resolution (90 directions) dataset. Such an approach not only significantly reduce the scan time using one-third original DW images, but also be able to compute dMRI-derived parametric maps using a standard tensor model. |
| 4359 | Mitigating Impacts of Tissue-Heterogeneity and Noise Bias on MP-PCA Denoising for High-Quality Diffusion MRI | |
| Cornelius Eichner1, Michael Paquette1, Angela D Friederici1, and Alfred Anwander1 | ||
1Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany |
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Advanced diffusion MRI (dMRI) data with high resolution and strong diffusion contrast typically suffer from low SNR levels. Therefore, denoising algorithms such as MP-PCA became an essential part of current dMRI processing pipelines. To overcome challenges related to violations of MP-PCAs assumption of tissue homogeneity in typical dMRI data, we here introduce an informed-MP-PCA (iMP-PCA) algorithm taking local differences in tissue composition into account. Denoising-performance of iMP-PCA was compared to conventional MP-PCA and evaluated on both magnitude and real-valued dMRI data. iMP-PCA was shown to significantly improve denoising-performance, especially at tissue boundaries and in regions of low SNR. |
| 4360 | Denoise magnitude diffusion magnetic resonance images via variance-stabilizing transformation and optimal singular-value manipulation | |
| Xiaoping Wu1 and Kamil Ugurbil1 | ||
1Center for Magnetic Resonance Research, Radiology, Medical School, University of Minnesota, Minneapolis, MN, United States |
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We introduce a new denoising framework for denoising magnitude diffusion MRI. The framework synergistically combines the variance stabilizing transform with optimal singular-value manipulation. The usefulness of the proposed framework is demonstrated using both simulation and real-data experiments. Our results show that the proposed denoising framework can significantly improve signal-to-noise ratios across the entire brain, leading to substantially enhanced performances for estimating diffusion-tensor-related indices and for resolving crossing fibers when compared to another competing method. As such, the proposed denoising method is expected to have great utility for high-quality, high-resolution whole-brain diffusion MRI, desirable for many neuroscience and clinical applications. |
| 4361 | SENSE reconstruction with simultaneous 2D phase correction and channel-wise noise removal (SPECTRE) | |
| Elizabeth Powell1,2, Torben Schneider3, Marco Battiston2, Francesco Grussu2,4, Ahmed Toosy2, Jonathan D Clayden5, and Claudia A. M. Gandini Wheeler-Kingshott2,6,7 | ||
1Medical Physics and Biomedical Engineering, University College London, London, United Kingdom, 2NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom, 3Philips Healthcare, Guildford, United Kingdom, 4Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom, 5Developmental Imaging and Biophysics Section, Great Ormond Street Institute of Child Health, University College London, London, United Kingdom, 6Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy, 7Brain MRI 3T Center, IRCCS Mondino Foundation, Pavia, Italy |
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Nyquist sampling errors in echo planar imaging (EPI) often require 2D phase correction during reconstruction to remove unwanted ghost artefacts; however, phase corrections can be challenging to translate to high b-value diffusion weighted imaging (DWI) owing to associated noise amplification. We introduce SPECTRE (SENSE with 2D PhasE CorrecTion and channel-wise noise REmoval), and demonstrate that the SNR gains achieved by denoising complex channel data enable robust ghost correction without biasing diffusion parameter estimates. |
| 4362 | Model-Based Deep Learning for Reconstruction of Joint k-q Under-Sampled Diffusion MRI | |
| Merry P. Mani1, Hemant Kumar Aggarwal2, Sanjay Ghosh1, and Mathews Jacob2 | ||
1Department of Radiology, University of Iowa, Iowa City, IA, United States, 2Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA, United States |
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We propose a model-based deep learning architecture for the reconstruction of highly accelerated diffusion MRI. We introduce the use of a pre-trained denoiser as the regularizer in a model-based recovery for diffusion weighted data from k-q under-sampled acquisition in a parallel MRI setting. The denoiser is designed based on a general tissue microstructure diffusion signal model with multi-compartmental modeling. A neural network was trained in an unsupervised manner using a convolutional auto-encoder to learn the diffusion MRI signal subspace. To demonstrate the acceleration capabilities of the proposed method, we perform MRI reconstruction experiments on a simulated brain dataset. |
| 4363 | Towards the clinical application of model‐based reconstruction framework for distortion correction in prostate diffusion weighted MRI. | |
| Lebina Shrestha Kakkar1, Muhammad Usman1, Alex Kirkham2, Simon Arridge1, and David Atkinson1 | ||
1Centre for Medical Imaging, University College London, London, United Kingdom, 2Department of Radiology, University College Hospital, London, United Kingdom |
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Prostate diffusion-weighted (DW) MRI based on single-shot echo planar imaging (EPI) can suffer from geometric distortions caused by off-resonance magnetic field at the prostate-rectal air interface. Although techniques exist for effective distortion correction in brain imaging, such approaches may struggle with the severe distortions observed in prostate imaging. Here we focus on applying a recently developed model-based reconstruction technique to correct distortions in typical clinically used prostate DW-MRI. The distortion correction is feasible and may improve prostatic zonal anatomy in DW-MRI. Additionally, corrected averaged high b-value datasets show higher SNR than uncorrected dataset and may further help to identify tumours. |
| 4364 | Highly Accelerated and High-Quality Intra-voxel Incoherent Motion DWI Enabled by Parametric POCS based multiplexed sensitivity-encoding | |
| Shihui Chen1, Mei-Lan Chu2, Chun-Jung Juan3, Liyuan Liang1, and Hing-Chiu Chang1 | ||
1The University of Hong Kong, Hong Kong, Hong Kong, 2Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan, Taipei, Taiwan, 3Department of Medical Imaging, China Medical University Hsinchu Hospital, Taiwan, Taipei, Taiwan |
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Low SNR and long acquisition time hinder the clinical feasibility of intra-voxel incoherent motion (IVIM) diffusion-weighted imaging. In this work, we used a joint reconstruction framework based on POCSMUSE algorithm to simultaneously reconstruct under-sampled multi-b multi-shot DW-EPI data without undesired noise amplification. A proposed parametric correction scheme (PCS) was incorporated into POCSMUSE algorithm for robust reconstruction based on either conventional bi-exponential or simplified IVIM model. The proposed method demonstrated that the high-quality brain IVIM images could be reconstructed from highly accelerated (R=4) data acquired with multi-b multi-shot DW-EPI. |
| 4365 | Fast Simultaneous Multi-Slice Multi-Shell Diffusion Tensor Imaging with Model-based Reconstruction | |
| Oliver Maier1, Stefan M Spann1, Lea Bogensperger1,2, and Rudolf Stollberger1,3 | ||
1Institute of Medical Engineering, Technical University Graz, Graz, Austria, 2Institute for Computer Graphics and Vision, Technical University Graz, Graz, Austria, 3Biotechmed, Graz, Austria |
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Multi-Shell DTI suffers from low SNR for high b-value data and prolonged scan time. The Gaussian noise assumption is typically violated due to multi-coil imaging and magnitude forming thus requiring special treatment to avoid biases in the DTI estimates. To this end, we propose a model-based reconstruction technique to exploit the Gaussian noise in the raw k-space data and enable acceleration of the DTI measurement. We show the acceleration potential and quantitative accuracy of the proposed method for mono- and bi-exponential fitting approaches on freely available DTI data and full brain DTI measurements of one healthy volunteer. |
| 4366 | Regularized Image Domain Split Slice-GRAPPA for Simultaneous Multi-Slice Diffusion MR Imaging | |
| SeyyedKazem HashemizadehKolowri1, Rong-Rong Chen1, Ganesh Adluru2,3, and Edward V. R. DiBella1,2,3 | ||
1Electrical and Computer Engineering, University of Utah, SALT LAKE CITY, UT, United States, 2Radiology and Imaging Science, University of Utah, SALT LAKE CITY, UT, United States, 3Biomedical Engineering, University of Utah, SALT LAKE CITY, UT, United States |
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Simultaneous multi-slice (SMS) acquisition combined with blipped controlled aliasing in parallel imaging is commonly used to accelerate diffusion imaging with single-shot EPI sequences. In this work, we propose a new method, termed regularized image domain split slice-GRAPPA (RI-SSG), which allows an efficient image domain implementation of SSG coupled with total variation regularization to improve the quality of SMS reconstruction. We process two single-shot EPI datasets acquired using diffusion protocol of Human Connectome Project in Aging to evaluate performance of SMS reconstructions. The RI-SSG yields less noisy results than SENSE and SSG in estimating diffusion-weighted images and parametric maps of diffusion. |
| 4367 | Magnitude-regularized Phase Estimation (MAPE) with U-Net Support for Self-navigated Multi-shot Echo-planar DWI in the Brain | |
| Malte Steinhoff1, Alfred Mertins1, and Peter Börnert2,3 | ||
1Institute for Signal Processing, University of Luebeck, Luebeck, Germany, 2Philips Research Europe, Hamburg, Germany, 3Department of Radiology, LUMC, Leiden, Netherlands |
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We propose a self-navigated iterative reconstruction algorithm for multi-shot DWI which effectively performs the shot phase updates with a fixed joint image prior. This framework further nicely incorporates deep learning generated image priors into the shot phase estimation while keeping the joint image production isolated. A U-Net is trained on extra-navigated data to mitigate phase cancellation artifacts. The algorithm with and without U-Net support is compared to self- and extra-navigated reference algorithms. The U-Net approach effectively mitigates phase-related signal cancellation artifacts. The improved multi-shot image prior regularizes the shot phase estimation enabling highly segmented self-navigated diffusion echo-planar imaging. |
| 4368 | An Evaluation of q-Space Regularization Strategies for gSlider with Interlaced Subsampling | |
| Yunsong Liu1, Congyu Liao2, Kawin Setsompop2, and Justin P. Haldar1 | ||
1Signal and Image Processing Institute, University of Southern California, Los Angeles, CA, United States, 2Martinos Center for Biomedical Imaging, Charlestown, MA, United States |
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gSlider is a diffusion MRI method that achieves fast high-resolution data acquisition using a novel slab-selective RF-encoding strategy. Recent work has proposed subsampling of the multidimensional gSlider encoding space (diffusion-encoding/RF-encoding) for further improved scan efficiency. Two different q-space regularization approaches (i.e., Laplace-Beltrami smoothness and spherical ridgelet sparsity) have been proposed to compensate for missing data, but there have been no systematic comparisons between the two. We compare and evaluate the potential synergies of these regularization approaches. Results suggest that there can be small advantages to combining both regularization strategies together, although Laplace-Beltrami regularization alone is simpler and not much worse. |
| 4369 | Whole-brain in-vivo submillimeter diffusion MRI in 10 minutes with combined gSlider-Spherical Ridgelets reconstruction | |
| Gabriel Ramos-Llordén1, Lipeng Ning1, Congyu Liao2, Rinat Mukhometzianov3, Oleg Michailovich3, Kawin Setsompop2, and Yogesh Rathi1 | ||
1Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States, 2Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States, 3University of Waterloo, Waterloo, ON, Canada |
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gSlider is an efficient, super-resolution, technique to achieve submillimeter diffusion MRI data circumventing the trade-off between image resolution and SNR. Yet, the long acquisition time is still an issue. In this work, we extend gSlider by allowing under-sampling both in q-space and Radio-Frequency (RF)-encoded data, achieving then shorter acquisition time that gSlider. Our method, gSlider-SR, uses a basis of Spherical-Ridgelets to exploit the redundancy of the dMRI data, while at the same time enhancing SNR. We demonstrate that only ten minutes are needed to reconstruct 64 diffusion directions (b=2000s/mm2) at 860 μm data with reliably signal preservation. |
| 4370 | Simultaneously multi-slice VAT-DIADEM at ultra-high field | |
| Yi-Hang Tung1, Frank Godenschweger1, Myung-Ho In2, Alessandro Sciarra3, and Oliver Speck1 | ||
1Biomedical Magnetic Resonance, Otto-von-Guericke University Magdeburg, Magdeburg, Germany, 2Department of Radiology, Mayo Clinic, Rochester, MN, United States, 3Medicine and Digitalization, Otto-von-Guericke University Magdeburg, Magdeburg, Germany |
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VAT-DIADEM is able to accelerate the distortion-free T2 weighting and diffusion weighting imaging sequence DIADEM at ultra-high field. The VAT gradient is turned on during imaging read-out in the slice selection direction. To further increase the acquisition efficiency, we developed a blipped version of the VAT gradient and applied simultaneous multi-slice imaging, based on blipped-CAIPI. The result is distortion reduction in EPI or acceleration in DIADEM and the increased volume coverage without increasing TR. |
| 4371 | Automated feature extraction across scanners for harmonization of diffusion MRI datasets | |
| Samuel St-Jean1, Max A. Viergever1, and Alexander Leemans1 | ||
1Image sciences institute, University Medical Center Utrecht, Utrecht, Netherlands |
||
Small variations in diffusion MRI metrics between subjects are ubiquitous due to differences in scanner hardware and are entangled in the genuine biological variability between subjects, including abnormality due to disease. In this work, we propose a new harmonization algorithm based on adaptive dictionary learning to mitigate the unwanted variability caused by different scanner hardware while preserving the biological variability of the data. Results show that unpaired datasets from multiple scanners can be mapped to a scanner agnostic space while preserving genuine anatomical variability, reducing scanner effects and preserving simulated edema added to test datasets only. |
| 4372 | Concomitant Gradient Field Corrections for Asymmetric Diffusion Encoding Waveforms | |
| Matthew J. Middione1, Michael Loecher1, Kévin Moulin1,2, and Daniel B. Ennis1,2,3 | ||
1Department of Radiology, Stanford University, Palo Alto, CA, United States, 2Cardiovascular Institute, Stanford University, Palo Alto, CA, United States, 3Veterans Administration Health Care System, Division of Radiology, Palo Alto, CA, United States |
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In DWI, applied diffusion gradients are assumed to be linear in space, but in practice are accompanied by additional undesired concomitant gradient (CG) fields that arise as a consequence of Maxwell’s equations. These CG fields contribute a residual gradient moment for asymmetric diffusion encoding strategies, which may impact the quantitative accuracy of the measured ADC. In this work, a CG correction method that does not increase the minimum achievable TE was implemented for clinically relevant asymmetric diffusion encoding DWI protocols and the mean ADC error reduction was characterized. |
| 4373 | A Comparison of Image-based and Field-monitoring-based Correction for Eddy Current and Bo Field Distortions in Diffusion Imaging Data | |
| Yoojin Lee1, Klaas P Pruessmann2, and Zoltan Nagy1 | ||
1Laboratory for Social and Neural Systems Research (SNS Lab), University of Zurich, Zurich, Switzerland, 2Institute of Biomedical Engineering, ETH, Zurich, Switzerland |
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Diffusion MRI commonly proceeds with single-shot echo planar imaging (EPI) readout, which renders this modality sensitive to Eddy current and susceptibility-induced distortions. Both image-based and k-space-based correction methods have been suggested previously. The aim of this project was to use a standard dataset and compare output images of two image-based correction methods (topup/Eddy and Tortoise) and the extended signal model method. The latter relies on separate magnetic field monitoring data and a Bo field map. Qualitatively the output of three pipelines were similar. Future work will make the diffusion acquisition more challenging for a more complete systematic evaluation. |
| 4374 | Introduction of matrix analysis for hybrid multidimensional prostate diffusion-weighted and T2-weighted imaging | |
| Xiaobing Fan1, Aritrick Chatterjee1, Milica Medved1, Aytekin Oto1, and Gregory S. Karczmar1 | ||
1Radiology, The University of Chicago, Chicago, IL, United States |
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We present a new concept based on matrix analysis for analyzing hybrid multi-dimensional T2-weighted and diffusion-weighted MRI of the prostate. This study evaluates whether matrix analysis is useful in diagnosis of prostate cancer. The hybrid data were linearized first by taking natural logarithms. Then the hybrid symmetric matrix was formed by multiplying by its own transpose matrix for each pixel. The eigenvalues and eigenvectors are calculated for this symmetric matrix to generate color maps. The preliminary results suggest that the combined color eigenvalue map provides new information that could help to identify and stage prostate cancer. |
| 4375 | Automatic Segmentation in Ischemic Stroke Rodent Brain with Pattern-recognition of Directional Intravoxel Incoherent Motion MRI | |
| MinJung Jang1, Seokha Jin1, MungSoo Kang1, SoHyun Han2, and HyungJoon Cho1 | ||
1Biomedical Engineering, Ulsan national institute of science and technology, Ulsan, Republic of Korea, 2Center for Neuroscience Imaging Research, Institute of Basic Science, Suwon, Republic of Korea |
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The purpose of this study is to demonstrate automatic segmentation for reduced diffusion and perfusion areas in ischemic stroke brains with pattern-recognition (constrained non-negative matrix factorization (cNMF)) to directional intravoxel incoherent motion MRI (IVIM-MRI). The robustness of region segmentation with pattern-recognition was observed in both simulations and in vivo experiments. Using pattern-recognition analysis of IVIM signal, white matter in which flow may have been aligned, and lesion regions are automatically segmented in ischemic stroke brain. In this study, we successfully implemented pattern-recognition to directional IVIM signals. |
| 4376 | Free-Water Diffusion Tensor Imaging (DTI) improves the accuracy and sensitivity of white matter analysis in Alzheimer’s disease | |
| Maurizio Bergamino1, Ryan R Walsh2, and Ashley M Stokes1 | ||
1Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ, United States, 2The Muhammad Ali Parkinson Center, Barrow Neurological Institute, Phoenix, AZ, United States |
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The objective of this study is to investigate differences in white matter (WM) integrity between Alzheimer’s disease (AD) and healthy subjects (HC) using diffusion tensor imaging (DTI) metrics from standard DTI and free-water (FW)-DTI. Regional changes in DTI metrics were found with both standard and FW-DTI, while FW-DTI improves the reliability and inter-parameter consistency of DTI metrics in the presence of atrophy. We hypothesize that the implementation of FW correction algorithm for DTI may provide more sensitive and specific insight into AD-related pathological changes in WM. |
| 4377 | Joint Sparsity and Low Rankness-based Spectroscopy Reconstruction for Magnetic Resonance Diffusion-Ordered NMR | |
| Di Guo1, Zhangren Tu1,2, Zifei Zhang3, Tianyu Qiu3, Xiaofeng Du1, Min Xiao2, Zhong Chen3, and Xiaobo Qu3 | ||
1School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, China, 2School of Opto-Electronic and Communication Engineering, Xiamen University of Technology, Xiamen, China, 3Department of Electronic Science, Xiamen University, Xiamen, China |
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The magnetic resonance diffusion ordering spectrum has been widely used in the separation of mixture due to the mobility of molecular self-diffusion reaction molecules. We propose a hybrid time and exponential decay signal recovery method based on low rank Hankel matrix1 to accelerate the acquisition. The experimental results show that this method enables to reduce the error between the recovery diffusion spectrum and the fully sampled signal, and enhance the peak intensity. |
| 4378 | Characterizing intravoxel spatial distribution of diffusion based on texture analysis | |
| Suguru Yokosawa1,2, Toru Shirai1, Hisaaki Ochi1, and Yoshitaka Bito3 | ||
1Research & Development Group, Hitachi, Ltd., Tokyo, Japan, 2Graduate School of Engineering, Chiba University, Chiba, Japan, 3Healthcare Business Unit, Hitachi, Ltd., Tokyo, Japan |
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In this study, we proposed a method for characterizing intravoxel spatial distribution of diffusion by using texture analysis with GLCM (gray level cooccurrence matrix) from single-shell diffusion MRI data, which can be acquired in practical scan time. Since the method does not assume a diffusion distribution model, unstable calculation such as fitting process is not required. The method could provide novel diagnostic indices of diffusion MRI without additional acquisition. |
| 4379 | Exploring the reliability of ComBat for multi-site diffusion MRI harmonization | |
| Suheyla Cetin Karayumak1,2, Lily O’Sullivan2, Monica Gabriella Lyons2, Marek Kubicki1,2, and Yogesh Rathi1,2 | ||
1Harvard Medical School, Boston, MA, United States, 2Brigham and Women's Hospital, Boston, MA, United States |
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This study thoroughly explores the reliability of a statistical multi-site diffusion-MRI harmonization method, ComBat, using a large diffusion-MRI dataset involving 5 sites. Additionally, we demonstrate the effects of using different software packages to estimate the diffusion tensor on the harmonization performance of ComBat. Even when the processing steps (and software) were identical for all sites, ComBat altered the inter-group variability at each site and in some regions flipped the direction of effect-sizes. Finally, when different software packages were used to estimate the diffusion tensor at different sites, ComBat introduced much drastic effects, thereby reducing the reliability of the results. |
| 4380 | Reproducibility crisis in diffusion MRI: Contribution of software processing pipelines | |
| Suheyla Cetin Karayumak1,2, Lily O’Sullivan2, Monica Gabriella Lyons2, Tashrif Billah2, Ofer Pasternak1,2, Sylvain Bouix1,2, Marek Kubicki1,2, and Yogesh Rathi1,2 | ||
1Harvard Medical School, Boston, MA, United States, 2Brigham and Women's Hospital, Boston, MA, United States |
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This study attempts to highlight the reproducibility problem in clinical diffusion MRI studies by comparing different software in a large diffusion MRI data, collected from multiple sites with 291 schizophrenia patients and 251 healthy controls. We fit diffusion tensor using FSL, MRtrix and Slicer with ordinary-least-squares (OLS) and weighted-least-squares (WLS) methods. To assess biological differences (measured by FA) between controls and patients, we computed effect-sizes (Cohen’s d) at each site using each software. We observed significant software effects with each software package producing significantly different results, when either OLS or WLS, was used. |
| 4381 | Diffusion MRI response function estimates vary more across pathways than across subjects | |
| Kurt G Schilling1, Bennett A Landman1,2,3,4, Alexander Leemans5, Adam W Anderson1,2, and Chantal M.W. Tax6 | ||
1Vanderbilt University Institute of Imaging Science, Nashville, TN, United States, 2Biomedical Engineering, Vanderbilt University, Nashville, TN, United States, 3Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States, 4Electrical Engineering, Vanderbilt University, Nashville, TN, United States, 5Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands, 6CUBRIC, School of Physics, Cardiff University, Cardiff, United Kingdom |
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We investigated the diffusion fiber response function by characterizing the modelled diffusivity, the shape, and the size of the diffusion signal in regions of single fiber populations. We show that the various descriptors of the diffusion signal vary significantly across white matter pathways within a subject, and across subjects for a given pathway. Analysis of variance suggests that variability between pathways is greater than across subjects. Understanding the response function and its variation are necessary for accurate fiber orientation characterization, as well as characterizing microstructural effects from geometrical effects within a voxel. |
| 4382 | High-resolution microscopic diffusion anisotropy imaging in the human hippocampus using multidimensional diffusion encoding | |
| Jiyoon Yoo1, Leevi Kerkelä1, Patrick W. Hales1, Kiran K. Seunarine1, Noemi G. Gyori1,2, Enrico Kaden2, and Christopher A. Clark1 | ||
1UCL Great Ormond Street Institute of Child Health, London, United Kingdom, 2UCL Centre for Medical Image Computing, London, United Kingdom |
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Several neurological diseases are associated with microstructural changes in the hippocampus which can be observed using diffusion MRI. However, DTI derived microstructural metrics such as fractional anisotropy (FA) are not able to differentiate between orientation dispersion and microscopic anisotropy. In this study, we applied an optimised multidimensional diffusion encoding sequence to measure microscopic fractional anisotropy (µFA) and normalised size variance (CMD) in the human hippocampus of healthy subjects. We also defined a clinically feasible acquisition protocol by subsampling the full data set. |
| 4383 | Quantifying whole-brain microstructural changes in rat model of focal ischemia on unilateral motor cortex using diffusion MRI at 14T | |
| Zhaoqing Li1, Huan Gao2, Kedi Xu2, and Ruiliang Bai1,3 | ||
1Interdisciplinary Institute of Neuroscience and Technology (ZIINT), College of Biomedical Engineering and Instrument Science, Zhejiang University, HangZhou, China, 2Qiushi Academy for Advanced Studies (QAAS), Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, HangZhou, China, 3School of Medicine, Zhejiang Univerisity, HangZhou, China |
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Focal cortical ischemia animal model has been widely used to study neuroanatomical reorganization of cortex with intracortical microstimulation. However, the whole-brain structural changes following focal ischemia on motor cortex is unknown. In this study, high-resolution DTI is performed on focal unilateral motor cortex ischemia rat model at 14T. Voxel-wise based analysis (VBA) and VBA-guided connectivity analysis are performed to explore potential whole-brain microstructure and global structural connectivity changes. Our results show that large-scale white matter microstructural changes mainly distribute in corpus callosum, external capsule, cerebral peduncle. Significant reorganization of sensorimotor network associated with these regions were also found after ischemia. |
| 4384 | A Study on Time Dependency of the Fractional Order Calculus Diffusion Model | |
| Guangyu Dan1,2, Yuxin Zhang3,4, Zheng Zhong1,2, Kaibao Sun1, M. Muge Karaman1,2, Diego Hernando3,4, and Xiaohong Joe Zhou1,2,5 | ||
1Center for Magnetic Resonance Research, University of Illinois at Chicago, Chicago, IL, United States, 2Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, United States, 3Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States, 4Department of Radiology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States, 5Department of Radiology and Neurosurgery, University of Illinois at Chicago, Chicago, IL, United States |
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Parameters in many diffusion models depend on diffusion time. However, time-dependent diffusion behaviors in the long diffusion time regime have not been well studied because a longer diffusion time would lead to a longer TE, substantially reducing signal-to-noise ratio in conventional spin-echo diffusion pulse sequences. In this study, we employed a STEAM diffusion sequence to investigate the diffusion-time dependence of parameters in a fractional order calculus diffusion model. Our results showed substantial dependence of all diffusion parameters on diffusion times in the range of 100-1000 ms. |
| 4385 | Delineating the grey matter-white matter interface directly from diffusion MRI data | |
| Dmitri Shastin1,2, Maxime Chamberland1, Greg Parker1, Chantal M. W. Tax1, Kristin Koller1, Khalid Hamandi1,2, William Gray2,3, and Derek Jones1 | ||
1School of Psychology, Cardiff University Brain Research Imaging Centre, Cardiff, United Kingdom, 2School of Medicine, Cardiff University Brain Research Imaging Centre, Cardiff, United Kingdom, 3BRAIN Biomedical Research Unit, Cardiff, United Kingdom |
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Anatomically constrained tractography aims to reduce the number of false positive streamlines by applying anatomically realistic priors. Grey matter-white matter interface is currently extracted based on T1 information requiring the availability of a T1 volume and its accurate co-registration with diffusion MRI data. Here we describe an alternative method based on multi-shell multi-tissue constrained spherical deconvolution that produces the interface without the need for T1. We go ahead and compare our method with the existing one and show a potential application. |
| 4386 | Synthetic-DWI with T2-based Water Suppression | |
| Tokunori Kimura1, Kousuke Yamashita1, and Kouta Fukatsu1 | ||
1Department of Radiological Science, Shizuoka College of Medicare Science, Hamamatsu-Shi, Japan |
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We proposed a new Diffusion Weighted Imaging (DWI) with T2-based water suppression technique (Wsup-DWI) and additionally combined with synthetic-MRI technique. Our water suppression was achieved by subtracting heavy T2-weighted (long-TE) image from the standard DWI images after correcting signal intensities due to b-value. We demonstrated that hyperintense artifacts due to CSF partial volume effects (PVE) were dramatically suppressed even at lower b-values (b); and quantitative maps of ADC and FA became close to the tissue values due to CSF reduction. Furthermore, fiber tracts became longer for Wsup-DWI data than for standard-DWI data in a tractography with the same condition. |
| 4387 | Sparse Representation of DWI Images for Fully Automated Brain Tissue Segmentation | |
| Hu Cheng1, Jian Wang1,2, and Sharlene Newman1 | ||
1Psychological and Brain Sciences, Indiana University, Bloomington, IN, United States, 2School of Information Science and Engineering, Shandong Normal University, Jinan, China |
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We propose a fully automated brain tissue segmentation method based on sparse representation of diffusion weighted imaging (DWI) signal. Learning a dictionary from DWI signals, brain voxels are classified into gray matter, white matter, and CSF according to their sparse representation of clustered dictionary atoms. The proposed method was tested on three subjects of the HCP DWI datasets and achieved good agreement with the segmentation on T1-weighted images using SPM12. The method is very fast and robust for a wide range of sparse coding parameter selection and works well on DWI data with less number of shells or gradient directions. |
| 4388 | Improved parameter maps calculation in IVIM-diffusion-weighted MRI using a noise compensation fitting model | |
| Anna-Katinka Bracher1, Meinrad Beer1, Volker Rasche2, and Neubauer Henning1 | ||
1Department of Diagnostic and Interventional Radiology, Ulm University Medical Center, Ulm, Germany, 2Department of Internal Medicine II, Ulm University Medical Center, Ulm, Germany |
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In standard diffusion-weighted imaging, the parameter maps are calculated based on a set of magnitude images. The standard fitting model of the parameter maps does not take a noise-induced bias into account. A noise offset model for Intravoxel Incoherent Motion (IVIM) in Diffusion Weighted Imaging (DWI) is introduced and the impact on diffusion parameter maps is evaluated for muscle and synovia of the knee joint. Parameter fitting using the noise-offset model results in faster signal decay of the fitted curve and therefore in increased diffusion coefficients compared to standard IVIM mapping. |
| 4389 | Diffusion tensor residuals as a potential biomarker for brain tissue damage in memory clinic patients | |
| Anouk van Rijn1, Alexander Leemans1, Geert Jan Biessels2, and Alberto de Luca 1 | ||
1Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands, 2Department of Neurology, University Medical Center Utrecht Brain Center, Utrecht, Netherlands |
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DTI metrics are often used without assessing the goodness of fit of the estimation model. We investigated local changes in fit residuals induced by pathology. To this end, a template of expected normalized residuals was created with 10 healthy controls, then voxel-wise comparisons were performed against the residuals of subjects affected by dementia. Results show that the residuals of infarcted regions are significantly different as compared to healthy tissue, whereas no differences were observed in hyperintensities. The fit residuals of the DTI model can be used to complement the information of DTI metrics at detecting microstructural changes in brain lesions. |
| 4390 | The efficacy of ADC value of DWI in differentiating extrahepatic cholangiocarcinoma from mass-forming cholangitis | |
| Yaxin Niu1, Ailian Liu1, Ye Li1, and Lizhi Lizhi Xie2 | ||
1The First Affiliated Hospital of Dalian Medical University, Dalian Medical University, Da Lian, China, 2GE Healthcare, MR Research China, BeiJing, China, Beijing, China |
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Diffusion-weighted imaging reflects the micro-movements of water molecules. |
| 4391 | Quasi-Diffusion Magnetic Resonance Imaging (QDI): optimisation of acquisition protocol | |
| Catherine A Spilling1, Franklyn A Howe1, and Thomas R Barrick1 | ||
1Neurosciences Research Centre, Molecular and Clinical Sciences Research Institute, St George's University of London, London, United Kingdom |
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Quasi-diffusion image (QDI) is a new ultra-high b-value diffusion magnetic resonance imaging technique which provides standard and non-Gaussian diffusion images. We use permutation analysis to optimise a clinical QDI tensor acquisition from a gold standard multi b-value protocol (28 non-zero b-values in 6 diffusion directions) to identify a 2 minute acquisition protocol with excellent tissue contrast. We achieve this by comparing different b-value combinations (2 non-zero b-values) to the gold standard using χ2 difference in parameterised signal decay curves. We obtain an optimal acquisition protocol of b=0, 1080, 5000 s mm-2 that may be acquired in a clinically acceptable time. |
| 4392 | Diffusion tensor imaging in identificationof stageIendometrial carcinoma and endometrial poly | |
| Xuedong Wang1, Ailian Liu1, ShiFeng Tian1, Lizhi Xie2, and Qingwei Song1 | ||
1The first affiliated hospital of dalian medical university, DaLian, China, 2GE Healthcare, MR Research China, Beijing, Beijing, China |
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Diffusion tensor imaging (DTI), a type of MR functional imaging, can reflect the direction of the diffusion motion of water moleculesas well as describe the free diffusion rate of water molecules. The characteristic suggested the DTI were helpful in distinguishing endometrial carcinoma (EC) from endometrial polyp (EP). |
| 4393 | An analytical segmented approach for extracting TE independent perfusion fraction in intravoxel incoherent motion (IVIM) MRI | |
| Erick O Buko1, Afis Ajala1, Jiming Zhang2, Pei Herng Hor1, and Raja Muthupillai2 | ||
1Physics, Texas Center for Superconductivity at University of Houston, Houston, TX, United States, 2Diagnostic and Interventional Radiology, Baylor St. Luke's Medical Center, Houston, TX, United States |
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Determination of perfusion fraction (f) from IVIM-MRI data is challenging. Recent studies have shown that estimation of f is influenced by echo time (TE). Eliminating thisTE dependency on f requires acquiring data sets at multiple TEs. Here, we propose an analytical segmented approach to correct for the TE dependency on f arising from T2 differences between the tissue and fluid compartments (AS-T2). Numerical simulations predict, and phantom experiments confirm that, -compared to commonly used segmented approaches to estimate f, AS-T2 approach permits the determination of perfusion fraction without TE dependence, and with fewer measurements. |
| 4394 | A simple phantom for extracting Intravoxel Incoherent Motion (IVIM) model parameters | |
| Erick O Buko1, Afis Ajala1, Jiming Zhang2, and Pei Herng Hor1 | ||
1Physics, Texas Center for Superconductivity at University of Houston, Houston, TX, United States, 2Diagnostic and Interventional Radiology, Baylor St. Luke's Medical Center, Houston, TX, United States |
||
We present a simple phantom set-up to model diffusion weighted imaging signal arising from intra-voxel incoherent motion (IVIM). The model provides means to independently control both the perfusion fraction (f) as well as the pseudodiffusion coefficient (Df). |
| 4395 | Impact of brain and head and neck radiotherapy fixation and coil configuration on tensor-valued dMRI | |
| Patrik Brynolfsson1, Markus Nilsson2, Christian Jamtheim Gustafsson1,3, Tim Sprenger4, Pia C Sundgren5,6, Lars E Olsson1, and Filip Szczepankiewicz7,8 | ||
1Dept. of Translational Medicine, Division of Medical Radiation Physics, Lund University, Lund, Sweden, 2Dept. of Clinical Sciences, Division of Radiology, Lund University, Lund, Sweden, 3Dept. of Hematology, Oncology and Radiation Sciences, Lund University, Lund, Sweden, 4MR Applied Science Laboratory Europe, GE Healthcare, Stockholm, Sweden, 5Diagnostic Radiology, Clinical Sciences, Lund University, Lund, Sweden, 6Lund University Bioimaging Center, Lund University, Lund, Sweden, 7Lund University, Lund, Sweden, 8Brigham and Women's Hospital, Boston, MA, United States |
||
Brain and head and neck cancer patients need fixation while undergoing radiotherapy, which prevents the use of a dedicated head coil when imaging patients using MRI in radiotherapy setup. We investigate the impact of coil setup on the technical feasibility of tensor-valued diffusion MRI in a radiation therapy setting. Three coil configurations were evaluated with respect to SNR and parameter bias in the resulting parametric maps using Bland-Altman plots. As expected, the coils configured for radiation therapy imposed a penalty on the SNR, but accuracy was not negatively impacted. |
| 4396 | Improved estimation of diffusion tensors by noise-corrected curve fitting with adaptive neighborhood regularization | |
| Li Guo1,2,3, Xinyuan Zhang2,3, Changqing Wang4, Jian Lyu2,3, Yingjie Mei5, Ruiliang Lu1, Mingyong Gao1, and Yanqiu Feng2,3 | ||
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, 4School of Biomedical Engineering, Anhui Medical University, Hefei, China, 5Philips Healthcare, Guangzhou, China |
||
The noncentral Chi noise in magnitude image may significantly affect the reliability of quantitative analysis in diffusion-weighted (DW) magnetic resonance imaging (MRI), especially at high b-value and/or higher order modeling of diffusion signal such as diffusion kurtosis imaging (DKI). We developed a novel first-moment noise-corrected curve fitting model with adaptive neighborhood regularization (MN1CM-ANR) algorithm for DKI. By fitting the signal to its first-moment (i.e. the expectation of the signal), MN1CM-ANR can effectively compensate the bias due to the noncentral Chi noise. In addition, by exploiting the neighboring pixels to regularize the curve fitting, MN1CM-ANR can reduce the measurement variance. |
| 4397 | Generalized sensitivity functions for optimal b-value selection in diffusion-based MRI modeling | |
| Umberto Villani1,2, Simona Schiavi3, and Alessandra Bertoldo1,2 | ||
1Padova Neuroscience Center, University of Padova, Padova, Italy, 2Department of Information Engineering, University of Padova, Padova, Italy, 3Department of Computer Science, University of Verona, Verona, Italy |
||
Generalized sensitivity functions provide insights about which temporal observations are most informative for the estimation of biological model parameters. We formulate the same concept in the dMRI field to investigate how biophysical models/data representations react to HARDI acquisitions of different b-values. This approach handily shows how different parameters feature enhanced estimation precision at different b-values and exposes potential correlations between them, shedding light on possible a posteriori identifiability issues. Requiring only byproducts of standard optimization routines, generalized sensitivity functions can easily be integrated in standard analyses when proposing either a new model or a modification of existing ones. |
| 4398 | Anomalous Diffusion estimation through the solution of the Fractional Time order Bloch-Torrey equation | |
| Óscar Peña-Nogales1, Carlos Castillo2,3,4, Carlos Lizama5, Rodrigo de Luis-Garcia1, Santiago Aja-Fernández1, and Pablo Irarrazaval2,3,4,6 | ||
1Laboratorio de Procesado de Imagen, Universidad de Valladolid, Valladolid, Spain, 2Instituto de Ingeniería Biológica y Médica, Pontificia Universidad Catolica de Chile, Santiago, Chile, 3Millennium Nucleus for Cardiovascular Magnetic Resonance, Santiago, Chile, 4Biomedical Imaging Center, Pontificia Universidad Católica de Chile, Santiago, Chile, 5Departamento de Matemáticas y Ciencia de la Computación, Universidad de Santiago de Chile, Santiago, Chile, 6Electrical Engineering Department, Pontificia Universidad Católica de Chile, Santiago, Chile |
||
Diffusion-Weighted (DW) imaging has a monoexponential signal decay at low b-values related to the statistical mechanics of Brownian motion. However, at high b-values the DW signal is no longer monoexponential. Various models have been proposed to better fit the data; nevertheless, none of them assumes that the DW signal is governed by the fractional-time order dynamics of the generalized Brownian motion (a.k.a., anomalous diffusion). In this work, by assuming anomalous diffusion we solve the fractional-time order Bloch-Torrey equation for smooth diffusion-weighting gradients and compare the obtained model to existing ones. The proposed model outperforms state-of-the-art on synthetic anomalous phantom experiments. |
| 4399 | Using Diffusional Kurtosis Imaging to Quantify non-Gaussian Water Diffusion in Normal Human Liver | |
| Junying Wang1, Hansen Schie2, Weiqiang Dou3, and Xiaoyi He1 | ||
1Medical Imaging, Shandong First Medical University, Jinan, Shandong, China, China, 2Medical Imaging, Shandong Provincial Qianfoshan Hospital，the First Hospital Affiliated with Shandong First Medical University, Jinan City, Shandong Province, China, China, 3GE Healthcare, MR Research China,Bejing, Bejing,China, China |
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This study aimed to test the reproducibility of DKI technique in normal liver and to explore the microscopic and diffusion differences between the left and right hepatic lobes. 32 healthy volunteers were scanned in DKI twice and the interval time was two weeks. All DKI-derived parametrical maps were reconstructed and mean values in eight liver segments were calculated. We demonstrated that DKI in the liver showed excellent reproducibility between two measurements and found interesting regional distributions of the parameters in liver. Additionally, significant difference was found in DKI-derived parameters between the left and right hepatic lobes |
| 4400 | Quasi-Diffusion Magnetic Resonance Imaging (QDI): a fast, high b-value diffusion imaging technique | |
| Thomas R Barrick1, Catherine A Spilling1, Carson Ingo2, Jeremy Madigan3, Jeremy D Isaacs3, Philip Rich3, Timothy L Jones3, Richard L Magin4, Matt G Hall5,6, and Franklyn A Howe1 | ||
1Neurosciences, St George's, University of London, London, United Kingdom, 2Northwerstern University, Chicago, IL, United States, 3St George's University Hospitals NHS Foundation Trust, London, United Kingdom, 4University of Illinois at Chicago, Chicago, IL, United States, 5National Physical Laboratory, Teddington, United Kingdom, 6University College London, London, United Kingdom |
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We present a new ultra-high b-value diffusion magnetic resonance imaging (dMRI) methodology, Quasi-Diffusion Imaging (QDI). The QDI technique includes a tensor representation of the dMRI data. We show that high contrast to noise images representing standard and non-Gaussian diffusion measures are obtainable in 1 to 4 minutes. QDI entropy maps show pathological contrast similar to Diffusional Kurtosis Imaging (DKI) in stroke and brain tumours. In addition, QDI overcomes the b-value limitations of DKI. |
| 4401 | Lesion detection using Free-Water elimination DTI - is this technique really specific to free water? | |
| Marc Golub1, R. N. Henriques2, and R. G. Nunes1 | ||
1ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico – Universidade de Lisboa, Lisbon, Portugal, Lisbon, Portugal, 2Champalimaud Neuroscience Programme, Champalimaud Centre for the Unknown, Lisbon, Portugal, Lisbon, Portugal |
||
Free water elimination (FWE) for diffusion tensor imaging (DTI) aims to decouple the free water contribution from tissue's diffusion. Recent studies suggest that FWE-DTI is essential to characterize degenerative processes since it suppresses free water partial volume effects from DTI analysis and provides an index sensitive to edema and tissue degeneration. In this work, the state-of-the-art of FWE-DTI estimation is explored and several fitting procedures are tested on in vivo data to which simulated lesions were added. We found that, unlike the multi-shell approach, the single-shell implementation was unable to discriminate between changes in tissue diffusion and free water increases. |
| 4402 | Deep Learning Based Brain Tissue Segmentation from Novel Diffusion Kurtosis Imaging Features | |
| Fan Zhang1, Anna Breger2, Lipeng Ning1, Carl-Fredrik Westin1, Lauren J O'Donnell1, and Ofer Pasternak1 | ||
1Harvard Medical School, Boston, MA, United States, 2University of Vienna, Wien, Austria |
||
Brain tissue segmentation is important in many diffusion MRI (dMRI) visualization and quantification tasks. We propose a deep learning tissue segmentation method that relies only on dMRI data. We leverage diffusion kurtosis imaging (DKI) and a recently proposed mean-kurtosis-curve (MK-curve) method to create a feature set that is highly discriminative between different types of tissues. We train a Unet model with a recently developed augmented target loss function on dMRI data from the Human Connectome Project. We show improved segmentation performance compared to several other methods and reliable segmentation results when applied on data with a different acquisition. |
| 4403 | Self-validation for deep learning–based diffusion kurtosis imaging harmonization | |
| Qiqi Tong1, Ting Gong1, Hongjian He1, Yi-Cheng Hsu2, and Jianhui Zhong1,3 | ||
1Center for Brain Imaging Science and Technology, Department of Biomedical Engineering, Zhejiang University, Hangzhou, China, 2MR Collaboration, Siemens Healthcare, Shanghai, China, 3Department of Imaging Sciences, University of Rochester, Rochester, NY, United States |
||
Deep learning–based harmonization for diffusion imaging data with high efficiency and low cost is gaining popularity. However, the performance of the training-required network depends on the training data, which lack the diversity of the large sets of data in more substantial multicenter projects. We proposed a leave-one-tissue-out training strategy to evaluate the validity and reliability across scanners of a deep learning–based diffusion kurtosis imaging harmonization method. The results confirm that the deep learning–based network can still reconstruct the untrained tissue with validity, although the reliability would be higher when the tissue is trained. |
| 4404 | Test-retest reliability of Diffusion Kurtosis Imaging (DKI) of the brain in healthy volunteers. | |
| Ernst Christiaanse1,2, Alexander Leemans2, Patrik Wyss1, and Alberto de Luca2 | ||
1Department of Radiology, Swiss Paraplegic Centre, Nottwil, Switzerland, 2Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands |
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It is essential for longitudinal studies to validate the reproducibility of the applied methods. Therefore, we assessed the test-retest reliability of diffusion kurtosis imaging of the brain in 10 healthy participants and showed a good reproducibility with some variation in different white matter regions. |
| 4405 | DeepHIBRID: How to condense the sampling in the k-q joint space for microstructural diffusion metric estimation empowered by deep learning | |
| Qiuyun Fan1, Qiyuan Tian1, Chanon Ngamsombat1, and Susie Y. Huang1 | ||
1Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States |
||
Conventional diffusion imaging protocols may require tens or hundreds of samples in the q-space to generate reliable maps. Knowing that the k-q joint space is highly redundant and given the tradeoffs between k, q and SNR, we trained a deep convolutional neural network using a HIgh B-value and high Resolution Integrated Diffusion (HIBRID) sampling scheme, dubbed DeepHIBRID. We show DeepHIBRID outperforms conventional sampling schemes, and is capable of outputting 14 synthesized diffusion metric maps simultaneously with only 10 input images, without sacrificing the quality of the output maps, using 30x angular downsampling. |
| 4406 | A Theoretical Framework for Representing and Estimating a Normal Diffusion Tensor Distribution | |
| Magdoom Kulam Najmudeen1, Dario Gasbarra2, and Peter J Basser1 | ||
1SQITS/NICHD, National Institute of Health, Bethesda, MD, United States, 2University of Helsinki, Helsinki, Finland |
||
A new signal model is introduced for diffusion tensor distribution imaging which is monotonically decreasing for all b-values unlike the cumulant and kurtosis models. A constrained multi-normal distribution is used as the tensor distribution which is fully characterized by the 2nd order mean and 4th order covariance tensors. A theoretical framework is presented showing the richness of covariance tensor, using synthetic gray and white matter voxels, and the ability to estimate the mean and covariance tensor from noisy MR signal. |
| 4407 | Estimating distributions of diffusion tensors and longitudinal relaxation rates in the brain via Monte-Carlo inversion: a proof of principle | |
| Alexis Reymbaut1,2, Jeffrey Critchley3, Giuliana Durighel3, Tim Sprenger4,5, Michael Sughrue6, and Daniel Topgaard1,2 | ||
1Physical Chemistry, Lund University, Lund, Sweden, 2Random Walk Imaging AB, Lund, Sweden, 3Spectrum Medical Imaging, Sydney, Australia, 4Karolinska Institute, Stockholm, Sweden, 5GE Healthcare, Stockholm, Sweden, 6Charlie Teo Foundation, Sydney, Australia |
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Conventional $$$T_1$$$-mapping techniques are only sensitive to voxel-averaged $$$T_1$$$ values, which hinders the study of fiber-specific myelination changes in the developing, aging or diseased brain. While recent works have focused on combining diffusion- and $$$T_1$$$- weightings to access orientation-resolved $$$T_1$$$ values, they rely on assumptions regarding the voxel content. This work combines a prototype diffusion-relaxation MR acquisition and a Monte-Carlo inversion method to extract intra-voxel nonparametric 5D distributions of diffusion tensors and longitudinal relaxation rates $$$R_1=1/T_1$$$ without the use of limiting assumptions. Estimated $$$R_1$$$ values are then mapped onto nonparametric orientation distribution functions, thereby yielding fiber-specific longitudinal relaxation rates. |
| 4408 | General tools for diffusion tensor distributions, and matrix-variate Gamma approximation for multidimensional diffusion MRI data | |
| Alexis Reymbaut1,2 | ||
1Physical Chemistry, Lund University, Lund, Sweden, 2Random Walk Imaging AB, Lund, Sweden |
||
Either on the voxel scale or within sub-voxel diffusion compartments, tissue microstructure can be described using a diffusion tensor distribution $$$\mathcal{P}(\mathbf{D})$$$. One way to resolve microstructural heterogeneity relies on choosing a plausible parametric functional form to approximate $$$\mathcal{P}(\mathbf{D})$$$. However, such a high-dimensional mathematical object is usually intractable. Here, we define matrix moments enabling the computation of diffusion metrics for any arbitrary functional choice approximating $$$\mathcal{P}(\mathbf{D})$$$. Applying these general tools to the matrix-variate Gamma distribution on the voxel scale, we obtain a new signal representation, the matrix-variate Gamma approximation, that we validate in vivo and in silico. |
| 4409 | Resolving orientation-specific diffusivities and transverse relaxation rates in heterogenous brain tissue | |
| Alexis Reymbaut1,2, João Pedro de Almeida Martins1,2, Chantal M. W. Tax3, Filip Szczepankiewicz2,4,5, Derek K. Jones3, and Daniel Topgaard1,2 | ||
1Physical Chemistry, Lund University, Lund, Sweden, 2Random Walk Imaging AB, Lund, Sweden, 3Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom, 4Harvard Medical School, Boston, MA, United States, 5Radiology, Brigham and Women’s Hospital, Boston, MA, United States |
||
Due to their cubic-millimeter scale, white-matter diffusion MRI voxels are often heterogeneous, comprising not only multiple fibre bundles but also grey matter, cerebrospinal fluid, or pathological tissue. To tackle this problem, conventional approaches rely on assumptions regarding tissue properties. This work combines state-of-the-art diffusion-relaxation MR acquisition and processing methods to extract intra-voxel nonparametric 5D distributions of diffusion tensors and transverse relaxation rates $$$R_2$$$ without the use of limiting assumptions. Orientation-resolved (fibre-specific) means of isotropic diffusivities, diffusion anisotropies and $$$R_2$$$ values are then obtained via clustering within the orientation subspace of these 5D distributions. |
| 4410 | Trueness and precision of statistical descriptors obtained from multidimensional diffusion signal inversion algorithms | |
| Alexis Reymbaut1,2, Paolo Mezzani1,3, João Pedro de Almeida Martins1,2, and Daniel Topgaard1,2 | ||
1Physical Chemistry, Lund University, Lund, Sweden, 2Random Walk Imaging AB, Lund, Sweden, 3Physics, Università degli Studi di Milano, Milan, Italy |
||
In first approximation, the diffusion signal writes as the Laplace transform of an intra-voxel diffusion tensor distribution (DTD). Several algorithms have been introduced to estimate the DTD’s statistical descriptors (mean diffusivity, variance of isotropic diffusivities, mean squared diffusion anisotropy, etc.) by inverting data obtained from tensor-valued diffusion encoding schemes. However, the trueness and precision of these estimations have not been systematically assessed and compared across methods. Here, we compare such estimations in silico for a 1D Gamma fit, a generalized two-term cumulant approach, and 2D and 4D Monte-Carlo inversion techniques, using a common and clinically feasible tensor-valued acquisition scheme. |
| 4411 | Spatiotemporal evolution of ischemic lesions in stroke animal models using free-water elimination and mapping with explicit T2 modelling | |
| Ezequiel Farrher1, Chia-Wen Chiang2, Kuan-Hung Cho2, Richard Buschbeck1, Ming-Jye Chen2, Zaheer Abbas1, Kuo-Jen Wu3, Yun Wang3, Farida Grinberg1, Chang-Hoon Choi1, N. Jon Shah1,4,5,6, and Li-Wei Kuo2,7 | ||
1INM-4, Forschungszentrum Jülich, Jülich, Germany, 2Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Miaoli, Taiwan, 3Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli, Taiwan, 4Department of Neurology, RWTH Aachen University, Aachen, Germany, 5JARA – BRAIN – Translational Medicine, RWTH Aachen University, Aachen, Germany, 6Institute of Neuroscience and Medicine 11, JARA, Forschungszentrum Jülich, Jülich, Germany, 7Institute of Medical Device and Imaging, National Taiwan University College of Medicine, Taipei, Taiwan |
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It is known that excess fluid as a result of vasogenic oedema formation following stroke onset obscures the microstructural characterisation of ischemic tissue by diffusion MRI. DTI-based free water elimination and mapping (FWE) has been proposed as a technique to potentially reduce the partial-volume effect. However, FWE estimation is ill-conditioned, leading to inaccurate results. More recently, it has been shown that the addition of a second dimension spanned by transverse relaxation weighting, mitigates the ill-conditioned problem. We aim here to investigate the latter model in a longitudinal study of MCAo stroke animal models. |
| 4412 | Impact of gradient non-linearities on B-tensor diffusion encoding | |
| Michael Paquette1, Chantal M.W. Tax2, Cornelius Eichner1, and Alfred Anwander1 | ||
1Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 2CUBRIC, School of Physics, Cardiff University, Cardiff, United Kingdom |
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We investigate the effect of gradient non-linearities (GNL) on free gradient waveform used for B-tensor diffusion encoding. We show the magnitude of the GNL-bias for strong gradients of $$$300 m\text{T}/\text{m}$$$. We derive a closed-form formula of the voxelwise B-tensor under GNL, independent of the choice of gradient waveform used to encode the B-tensor. |
| 4413 | Multi-dimensional Moment Imaging (MMI) for probing tissue microstructure | |
| Lipeng Ning1,2, Filip Szczepankiewicz1,2, Borjan Gagoski2,3, Carl-Fredrik Westin1,2, and Yogesh Rathi1,2 | ||
1Brigham and Women's Hospital, Boston, MA, United States, 2Harvard Medical School, Boston, MA, United States, 3Boston Children's Hospital, Boston, MA, United States |
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Multi-dimensional imaging techniques can provide complementary information to investigate the microscopic organizations of biological tissue. Deriving meaningful indices from these multi-dimensional imaging data is important to make these techniques relevant to clinical research. In this work, we introduce a general framework to estimate the moments of the joint probability distribution of T1, T2 relaxation and diffusion coefficients. This framework is an extension of our previously introduced REDIM approach which only focused on joint moments of T2 relaxation and diffusion. We show the cross coupling between different parameters using three datasets acquired using different protocols. |
| 4414 | Anomalous diffusion MRI model parameters vary in the human corpus callosum sub-regions with age | |
| Qianqian Yang1 and Viktor Vegh2 | ||
1School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia, 2Centre for Advanced Imaging, University of Queensland, Brisbane, Australia |
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Diffusion MRI measures of the human brain provide key insight into microstructural variations across individuals and into the impact of central nervous system diseases and disorders. One approach to extract information from diffusion signals has been to use biologically relevant analytical models to link millimetre scale diffusion MRI measures with microscale influences. The other approach has been to represent diffusion as an anomalous process, and infer information from the different anomalous diffusion equation parameters. Here, we show how parameters of three established anomalous diffusion equations change with age, in a microstructurally complex tissue, the human corpus callosum. |
| 4415 | Weighted linear least squares in multi-shell diffusion MRI: Should high b-shells always be weighted less? | |
| Jordan A. Chad1,2 and Ofer Pasternak3 | ||
1Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada, 2Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada, 3Departments of Psychiatry and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States |
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Fitting diffusion MRI signal models with the standard weighted linear least squares (WLLS) approach necessarily places lower weight on data with lower SNR, therefore placing lower weight on shells with higher b-values. This can be non-optimal for fitting signal models that rely on information from high b-shells. In this work, we propose a “nested” WLLS approach where each shell is assigned a relative weight, with standard WLLS applied within each shell. We demonstrate that weighting shells equally may be beneficial for fitting signal models dependent on multiple shells. |
| 4416 | Exploring effects of membrane permeability on dMRI metrics with Analytical solutions and Monte Carlo simulations | |
| Zihan Zhou1, Qiuping Ding1, Hongjian He1, and Jianhui Zhong1,2 | ||
1Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, China, 2School of Medicine and Dentistry, University of Rochester Medical Center, New York, NY, United States |
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White Matter Tract Integrity (WMTI) is a biophysical model with specificity to underlying tissue microstructures. However, recent work has suggested that inter-compartmental water exchange may affect outcomes of the model metrics. In this work, we analytically relate the WMTI-derived dMRI metrics to membrane permeability, and validate our predictions using Monte Carlo simulations. Our results show that the water exchange has a non-trivial effect on the metrics and needs to be carefully considered in WMTI. |
| 4417 | Application of MAP diffusion modelin differential diagnosis between high-grade glioma and single brain metastatic tumor | |
| BO LI1, YANG GAO1, SHAOYU WANG2, YAN XU2, GUANG YANG3, and HUAPENG ZHANG2 | ||
1Department of Radiology, The Affiliated Hospital of Inner Mongolia Medical University, Hohhot, China, 2MR Sicentific Marketing, Siemens Healthineers, Shanghai, China, 3Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China |
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This study aimed at using mean-apparent-propagator (MAP) diffusion model in differential diagnosis of high-grade glioma and single brain metastatic tumor.the findings show that multiple parameters quantified by DSI quantitative model MAP MRI, especially MSD and QIV has high applicatical value and provides more information for preoperative diagnosis of patients. |
| 4418 | A New Method for Reconstructing the Orientation Distribution Function in HARDI | |
| Diwei Shi1, Xuesong Li2, Ziyi Pan2, Hua Guo2, and Quanshui Zheng1 | ||
1Center for Nano & Micro Mechanics, Tsinghua University, Beijing, China, 2Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China |
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We propose a novel definition of orientation distribution function (ODF), which also represents diffusion coefficients for non-Gaussian situations, thus ODF has physical meaning. Then an expression is derived to calculate ODF values through diffusion-weighted signals. Next a new HARDI (high angular resolution diffusion imaging) method called “g-OPDT” (grids orientation probability density transform) is designed for practical use. Numerical simulations are performed to verify its accuracy. ISMRM-2015-Tracto-challenge data are used to quantitatively compare g-OPDT with other methods. Results show that g-OPDT has superior performance on most indicators. In-vivo experiments are conducted to show that its glyph representations have less redundant lobes. |
| 4517 | Quantification of uncertainty in parameterisations of cardiac myofibre orientations from diffusion-weighted imaging | |
| Bianca Freytag1, Vicky Y Wang2, Alistair A Young3, and Martyn P Nash1 | ||
1Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand, 2Veterans Affairs Medical Center, San Francisco, CA, United States, 3Biomedical Engineering Department, King's College London, London, United Kingdom |
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Electro-mechanical models of heart function rely upon accurate representation of microstructural orientations in the myocardium. We assessed the sensitivity of a finite element parameterisation of the myofibre orientation field derived from high-resolution DWI data of a canine heart. Eigenanalysis of the indifference region in the neighbourhood of the optimal fit of the myofibre field enabled quantification of helix angle uncertainty consistent with the DWI data. This method can be used to propagate the uncertainty in myofibre parameterisation to electro-mechanics simulation results. |
| 4419 | Quantifying Intra-Soma Diffusion Properties via Spherical Mean Spectrum Imaging | |
| Khoi Minh Huynh1,2, Ye Wu2, Kim-Han Thung2, Sahar Ahmad2, Hoyt Patrick Taylor IV2, Weili Lin2, and Pew-Thian Yap2 | ||
1Department of Biomedical Engineering, UNC-Chapel Hill, Chapel Hill, NC, United States, 2Department of Radiology and BRIC, UNC-Chapel Hill, Chapel Hill, NC, United States |
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We propose a novel model to quantify intra-soma diffusion properties, including volume fractions and kurtosis. The model is flexible, allowing simultaneous modeling of multiple tissue compartments without the need for assumptions on the number of compartments and their diffusivities. We demonstrate that our method provides biologically meaningful contrasts that agree well with histological data. |
| 4420 | Characterisation of microvascular blood velocity, exchange and structure using multi-diffusion time DWI | |
| Lauren Scott1, Ben Dickie1, Damien McHugh2, John McFadden1, Andrew N Priest3, and Laura M Parkes1 | ||
1Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, United Kingdom, 2Quantitative Biomedical Imaging Laboratory, University of Manchester, Manchester, United Kingdom, 3Radiology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom |
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Diffusion-time (∆) dependence in the bi-exponential intra-voxel incoherent motion model of diffusion-weighted imaging (DWI) signal decay is generally not considered. However, by using multi-∆ signal acquisitions, blood flow dynamics across different flow regimes can be accessed. In this study, we use multi-∆ DWI and an adapted velocity autocorrelation model to estimate blood velocity (v), capillary segment length (l) and transvascular water exchange. Human cerebral cortex and white matter (WM) estimates of v (cortex: 1.85 ± 0.21 mms-1; WM: 2.67 ± 1.01 mms-1) and l (cortex: 43.4 ± 19.5 µm; WM: 93.3 ± 51.1 µm) are consistent with literature values. |
| 4421 | Data-Driven Multi-Contrast Spectral Microstructure Imaging with InSpect: INtegrated SPECTral Component Estimation and Mapping | |
| Paddy J. Slator1, Jana Hutter2,3, Razvan V. Marinescu1, Marco Palombo1, Laurence Jackson2,3, Alison Ho4, Lucy C. Chappell4, Mary A. Rutherford2, Joseph V. Hajnal2,3, and Daniel C. Alexander1 | ||
1Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom, 2Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, 3Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, 4Women's Health Department, King's College London, London, United Kingdom |
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We introduce a novel spectroscopic imaging technique - termed InSpect - for analysing multi-contrast microstructural MRI experiments. Such data potentially supports estimation of multidimensional correlation spectra via a regularised inverse Laplace transform, but this is an ill-posed calculation. InSpect addresses these limitations in a data-driven way. The algorithm simultaneously estimates a canonical basis of spectral components for the whole data set, and maps their spatial distribution across images. Unlike standard approaches, InSpect shares information across voxels, implementing data-driven regularisation of the inverse Laplace transform. We demonstrate the method on combined diffusion-relaxometry placental MRI scans, revealing anatomically-relevant substructures, and identifying dysfunctional placentas. |
| 4422 | TE-dependence of NODDI-derived parameters and its modelling with compartmental T2 relaxation times | |
| Ting Gong1,2, Qiqi Tong1, Hongjian He1, Jianhui Zhong1,3, and Hui Zhang2 | ||
1Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, China, 2Department of Computer Science & Centre for Medical Image Computing, University College London, London, United Kingdom, 3Department of Imaging Sciences, University of Rochester, Rochester, NY, United States |
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Compartment-based models of diffusion MRI signals have become popular for probing tissue microstructure. However, the standard models do not explicitly model compartment-specific T2 relaxation. This has been shown to cause a TE-dependence of DTI-derived measures in white matter, which can confound the interpretation and quantification of results. Here we explored the TE-dependence of the widely used NODDI model and proposed a technique to determine parameter estimates that are TE-independent. This could be useful in investgateing diseases where changes of T2 and signal fraction interact. |
| 4423 | Optimisation of Temporal Diffusion Ratio (TDR) to maximise its potential to map large axons: Insight from simulations | |
| William Richard Warner1, Marco Palombo1, Flavio Dell'Acqua2, and Ivana Drobnjak1 | ||
1CMIC, Computer Science Department, University College London, London, United Kingdom, 2NatBrainLab, King's College London, London, United Kingdom |
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Temporal Diffusion Ratio (TDR) is a novel technique introduced by Dell’Acqua et al. at ISMRM 2019, with potential for mapping areas with large diameter axons in the human brain. We aim to maximise TDR signal in practical applications by optimizing the sequence parameters used. Working in simulation, it is found that the highest TDR signal for a given axon diameter is produced by contrasting signal from sequences with as disparate as possible shapes: a tall/narrow gradient shape should be contrasted with a short/wide gradient to produce the best contrast. |
| 4424 | Single-shell derived tissue signal fraction maps show increased contrast between hippocampal subfields compared to multi-shell analysis. | |
| Benjamin T Newman1,2, Thijs Dhollander3,4, and T. Jason Druzgal1,2 | ||
1Department of Radiology & Medical Imaging, Division of Neuroradiology, University of Virginia Health System, University of Virginia, Charlottesville, VA, United States, 2Brain Institute, University of Virginia, Charlottesville, VA, United States, 3The Florey Department of Neuroscience, University of Melbourne, Melbourne, Australia, 4The Florey Institute of Neuroscience and Mental Health, Melbourne, Australia |
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Recent advances in the analysis of diffusion MRI have allowed for the estimation of 3 tissue compartments in the brain from data with only a single non b=0 shell. There is currently no published quantitative comparison between signal fractions derived from either single- or multi-shell methods. Applying both single-shell analysis and multi-shell analysis to the same dataset shows high b-value single-shell analysis may increase contrast between different hippocampal subfields. While this effect may occur due to differences in microstructure between ROIs it should be a noted factor when applying either model and deserving of further study. |
| 4425 | Skeletal Muscle Diffusion Modeling to Identify Age Related Remodeling of Muscle Microstructure | |
| Vadim Malis1, Shantanu Sinha2, Edward Smitaman2, and Usha Sinha3 | ||
1Physics, UC San Diego, La Jolla, CA, United States, 2Radiology, UC San Diego, La Jolla, CA, United States, 3Physics, San Diego State University, San Diego, CA, United States |
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Diffusion modelling of the time dependence of the skeletal muscle diffusion eigenvalues derived from DTI allows one to probe tissue microstructure. We applied the Random Permeable Barrier Model to the time dependent diffusion data to identify age related remodeling in skeletal muscle microstructure. Model derived volume fraction (measure of the membrane’s ability to hinder diffusion) decreased with age while diffusion time and residence time in a cell increased with age while other model parameters such as the free diffusion coefficient, the fiber size, and membrane permeability did not. |
| 4426 | Improving neural soma imaging using the power spectrum of the free gradient waveforms | |
| Maryam Afzali1, Marco Palombo2, Lars Mueller 1, Hui Zhang2, Daniel C Alexander2, Markus Nilsson3, and Derek K Jones1,4 | ||
1Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom, 2Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom, 3Clinical Sciences Lund, Radiology, Lund University, Lund, Sweden, 4Mary MacKillop Institute for Health Research, Faculty of Health Sciences, Australian Catholic University, Melbourne, Victoria, 3065, Australia |
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Diffusion magnetic resonance imaging is a non-invasive technique to probe the microstructural features of tissue. Conventional diffusion encoding is unable to disentangle different microstructural features; therefore, multidimensional diffusion encoding has been proposed previously to solve this problem. Here we investigate different combinations of b-tensor encoding in a three-compartment model called SANDI. To estimate the size of soma in this model, we use frequency domain analysis because optimized b-tensor encoding waveforms do not provide a well-defined diffusion-time. The results show that different combinations of linear, planar, and spherical tensor encoding can improve the estimation of a specific parameter. |
| 4427 | Accuracy of axon diameter estimation using diffusion MRI in fiber space | |
| Mohammad Ashtarayeh1, Tobias Streubel1,2, Francisco Javier Fritz1, Joao Periquito3, Andreas Pohlmann3, Thoralf Niendorf3, Henriette Rusch4, Markus Morawski4, Carsten Jäger2, Stefan Geyer2, Bibek Dhital5, Muhamed Barakovic6,7, Simona Schiavi 8, Alessandro Daducci8, 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, 3Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany, 4Paul Flechsig Institute of Brain Research, University of Leipzig, Leipzig, Germany, 5Department of Radiology, University Medical Center Freiburg, Freiburg, Germany, 6Signal Processing Lab (LTS5), Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland, 7Translational Imaging in Neurology (ThINk) Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland, 8Department of computer science, University of Verona, Verona, Italy |
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We investigated the effect of different diffusion MRI acquisition protocols (incl. varying gradient-strength and signal-to-noise ratio) on the accuracy of axon diameter index (ADI) estimation in fiber space for human specimens. We used the Bland-Altman plot to estimate the error in the MRI-based ADI measurement. We found that gradient strengths above 900mT/m and b-values larger than b=50k s/mm2 provided accurate estimation of ADI (error smaller than 0.13 µm). The error for the best protocol was about 0.04 µm, allowing to distinguish white matter tracts with varying effective axon diameters (e.g. corpus callosum, genu, 1.5 µm and posterior body, 1.93 µm). |
| 4428 | Using stimulated echo diffusion MRI to elucidate cellular changes during cell death | |
| Daniel Djayakarsana1,2, Gregory J Czarnota1,2,3, and Colleen Bailey1,2 | ||
1Medical Biophysics, University of Toronto, Toronto, ON, Canada, 2Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada, 3Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada |
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Morphological changes caused by cellular death alter the movement of water, which diffusion MRI has the potential to detect. Cellular death can be easily isolated with an in vitro model. I find that the ADC, kurtosis and the ball-sphere model showed significant changes between the control and the treated groups. Likely sources of parameter changes are the increased membrane permeability, organelle/macromolecule breakdown and differences in cellular size. |
| 4429 | Indetermination-free cytoarchitecture measurements in brain gray matter via a forward diffusion MRI signal separation method | |
| Maëliss Jallais1 and Demian Wassermann1 | ||
1Université Paris-Saclay, Inria, CEA, Palaiseau, France |
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Non-invasive imaging at the cellular level could lead us to quantify grey matter tissue cytoarchitecture, which has so far been accessible only through histology, or by indeterminate-prone approaches. We propose a new dMRI-based index to study modulated by the size of the somas. This index can be extracted without indeterminations from any acquisition including three b-values superior to 3 ms/μm2. Simulations were experimentally confirmed by tests on the HCP MGH data set. |
| 4430 | Discrepancy between In-vivo Measurements and Monte-Carlo Simulations with Spherical Structures in B-tensor Encoding | |
| Noemi G Gyori1,2, Matt G Hall2, Christopher A Clark2, Daniel C Alexander1, and Enrico Kaden1 | ||
1Centre for Medical Image Computing, University College London, London, United Kingdom, 2Great Ormond Street Institute of Child Health, University College London, London, United Kingdom |
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In in-vivo B-tensor encoding measurements, linear tensor encoding (LTE) and spherical tensor encoding (STE) waveforms estimate the same mean diffusivity in brain white and grey matter. Contrary to this, we show that in Monte-Carlo simulations of quasi-spherical restrictions, LTE and STE signal decay curves are markedly different and lead to different mean diffusivity estimates. We investigate this discrepancy in the presence of variable compartment sizes, geometric distortions in cell shapes, permeable cell membranes, and water exchange between connected cellular geometries. Our results suggest that a strict model of restricted diffusion may not be suitable for brain tissue. |
| 4431 | Varying the frequency-content of high b-value spherical diffusion encoding improves the characterisation of isotropic restricted compartment | |
| Malwina Molendowska1, Mark Drakesmith1, Derek K. Jones1, and Chantal M. W. Tax1 | ||
1Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom |
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The use of ultra-strong diffusion gradient systems facilitates high b-values to suppress the signal from biological compartments with significant mobility, and as such the complexity of the model fit can be reduced. Here, we adopt isotropic encoding at high b-values to isolate spherical restricted compartments, and explore whether adding waveforms with different frequency-characteristics give an improvement in parameter-estimation of the spherical compartment. |
| 4432 | Decreased axon water fraction can result from either axonal loss and/or demyelination, reflecting different ex-vivo and in-vivo conditions | |
| Zihan Zhou1, Qiqi Tong1, Qiuping Ding1, Junye Yao1, Hongjian He1, and Jianhui Zhong1,2 | ||
1Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, China, 2School of Medicine and Dentistry, University of Rochester Medical Center, New York, NY, United States |
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White Matter Tract Integrity (WMTI) is specific to tissue microstructure. However, answers to a question of what a decreased axon water fraction (AWF), a metric of WMTI, reflects seem contradictory among previous in-vivo and ex-vivo studies. To our knowledge, there have been no studies that compare the difference in AWF decline under both ex-vivo and in-vivo conditions. Here we use Monte Carlo (MC) simulation to investigate such question and results show that AWF decline indicated demyelination under ex-vivo conditions while it also related to axonal loss in-vivo besides demyelination. Results highlighted the non-negligible effect of membrane permeability on the difference. |
| 4433 | A simulation study of the robustness of cell size and volume mapping for tissue with two underlying cell populations using diffusion weighted MRI | |
| Shu Xing1,2 and Ives R. Levesque1,2,3,4 | ||
1Department of Physics, McGill University, Montreal, QC, Canada, 2Medical Physics Unit, McGill University, Montreal, QC, Canada, 3McGill University Health Center Research Institute, Montreal, QC, Canada, 4Department of Oncology, McGill University, Montreal, QC, Canada |
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Advanced diffusion-weighted MRI allows non-invasive cell size and volume mapping in cancerous tumours. Existing methods assume that a given voxel contains one cell population. This work investigates the feasibility of estimating the radii and volume fractions of 2 cell populations co-existing in the same voxel and introduces techniques to improve the robustness and stability of fitting. The influence of noise on the fitted parameters is also examined for a range of SNR values. Reliable estimation of cell size and volume for tissue with 2 cell populations opens exciting avenue of potential applications in both tumor diagnosis and treatment monitoring. |
| 4434 | On the bias introduced by assuming different intravoxel incoherent motion regimes | |
| Oscar Jalnefjord1,2, Nicolas Geades3, and Maria Ljungberg1,2 | ||
1Department of Radiation Physics, University of Gothenburg, Gothenburg, Sweden, 2Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden, 3Philips Clinical Science, Gothenburg, Sweden |
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Intravoxel incoherent motion (IVIM) analysis typically assumes that the motion of blood caused by microcirculation mimics a random walk with several steps taken during the diffusion encoding (diffusive regime). Some studies have suggested use of the other extreme regime where no direction changes occur during diffusion encoding (ballistic regime). However, data available suggest that an intermediate regime is more likely. In this study, we explore the impact of assuming different IVIM regimes on modeling and parameter estimation. Results on healthy liver indicate that substantial bias may be introduced unless proper modeling is used. |
| 4435 | Power-Law Behaviour of the Diffusion-Weighted Signal Under Different B-Tensor Encoding Schemes | |
| Maryam Afzali1, Santiago Aja-Fernandez1,2, and Derek K Jones1,3 | ||
1Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom, 2Laboratorio de Procesado de Imagen, ETSI Telecomunicacion Edificio de las Nuevas Tecnologias, Campus Miguel Delibes s/n, Universidad de Valladolid, Valladolid, Spain, 3Mary MacKillop Institute for Health Research, Faculty of Health Sciences, Australian Catholic University, Melbourne, Victoria, Australia |
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It has been shown previously that for the linear (LTE), as well as planar tensor encoding (PTE) and in tissue with 'stick-like' geometry, the diffusion-weighted signal at high b-values follows a power-law. Specifically, the signal decays as $$$1/\sqrt{b}$$$ in LTE and $$$1/b$$$ in PTE. Here, we investigate whether power-law behaviors occur with other encodings and geometries. The results show that using an axisymmetric b-tensor a power-law only exists for stick-like geometries, using LTE and PTE. Finally, using ultra-strong gradients, we confirm –for the first time in vivo– that a power-law exists for PTE in white matter of the human brain. |
| 4436 | Tackling Degeneracy in Linear Tensor Encoding Diffusion MRI | |
| Khoi Minh Huynh1, Ye Wu2, Hoyt Patrick Taylor IV2, Weili Lin2, and Pew-Thian Yap2 | ||
1Biomedical Engineering, UNC-Chapel Hill, Chapel Hill, NC, United States, 2Department of Radiology and BRIC, UNC-Chapel Hill, Chapel Hill, NC, United States |
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Model degeneracy in diffusion MRI could lead to misestimation of microstructural properties. This work presents a metric to characterize the degree of degeneracy and proposes a strategy to break degeneracy by utilizing both diffusion-weighted signal and its spherical mean. We will demonstrate that breaking the degeneracy results in more accurate quantification of microstructure. |
| 4437 | Toolbox for spin-level MRI simulations: an application to cardiac diffusion | |
| Carlos Castillo-Passi1,2,3, Gabriel della Maggiora1,2,4, and Pablo Irarrazaval1,2,3,4 | ||
1Millennium Nucleus for Cardiovascular Magnetic Resonance, Santiago, Chile, 2Biomedical Imaging Center, Pontificia Universidad Católica de Chile, Santiago, Chile, 3Institute for Biological and Medical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile, 4Electrical Engineering Department, Pontificia Universidad Católica de Chile, Santiago, Chile |
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Cardiac diffusion imaging is a field with multiple challenges to overcome. The main challenge, compared to other techniques, is that the diffusion encoding sequence is prone to artifacts1. In this work, we show the first version of an MRI simulator that includes the most relevant effects for this type of contrast. And could be a useful tool for the development and testing of new pulse sequences. It is programmed in Julia2, which provides an intuitive object-oriented framework for the pulse sequences and creation of digital phantoms. We show two examples with results that correspond well with the theory. |
| 4438 | Using free waveform diffusion MRI to investigate time-dependence of water movement in an isotropic in vitro system | |
| Daniel Djayakarsana1,2, Gregory J Czarnota1,2,3, and Colleen Bailey1,2 | ||
1Medical Biophysics, University of Toronto, Toronto, ON, Canada, 2Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada, 3Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada |
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Signal attenuation due to diffusion is affected by several different acquisition parameters, such as gradient duration, spacing, strength and shape. In this study, I used free waveforms to investigate the effect of non-rectangular pulses. I chose an isotropic in vitro system such that the signal represents time and spatial scales relevant to human imaging and is independent of orientation. By varying only the gradient shape to target certain q-space frequencies, the signal measured could represent different combinations of diffusion time. |
| 4439 | Quantification of soma compartment in cerebral cortical mean kurtosis with diffusion MRI | |
| Tianjia Zhu1,2 and Hao Huang1,3 | ||
1Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, United States, 2Bioengineering, University of Pennsylvania, Philadelphia, PA, United States, 3Radiology, University of Pennsylvania, PHILADELPHIA, PA, United States |
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Unlike white matter composed mostly of neurites, cerebral cortex includes a significant amount of somas from neurons or glial cells besides neurites. Mean kurtosis (MK) of diffusion kurtosis imaging characterizes cortical microstructural complexity contributed by both neurites and somas, but the exact contribution of somas to cortical MK is unknown. Neuronal density plays a vital role in neurodegenerative disorders. Quantitative delineation of the soma compartment is critical for assessment and therapeutic monitoring of soma compartment with noninvasive diffusion MRI. We for the first time proved and quantified soma and neurite compartmental contributions to cerebral cortical MK. |
| 4440 | Behaviors of high b-value direction-averaged DWI signal decay in human gray matter | |
| Chu-Yu Lee1, In-Young Choi1,2,3, and Phil Lee1,4 | ||
1Hoglund Brain Imaging Center, University of Kansas Medical Center, Kansas City, KS, United States, 2Department of Neurology, University of Kansas Medical Center, Kansas City, KS, United States, 3Department of Molecular & Integrative Physiology, University of Kansas Medical Center, Kansas City, KS, United States, 4Department of Radiology, University of Kansas Medical Center, Kansas City, KS, United States |
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Neurite microenvironment has been approximated as impermeable, thin cylindrical tubes. This assumption has been validated in human white matter by a power law with the exponent of around 0.5 at b-values above 4000 s/mm2. However, the decay exponent in gray matter deviates from 0.5, suggesting that the cylindrical tube approximation does not apply in gray matter. This study aimed to study the whole-brain gray matter distribution of the decay exponent, and demonstrated an apparent contrast in the decay exponent between cortical gray matter and deep gray matter. This suggests that inherent microstructural differences may exist between these gray matter regions. |
| 4441 | Detecting the evolving tumor microenvironment with diffusion microstructure modeling: a simulation study | |
| Shu Xing1,2 and Ives R. Levesque1,2,3,4 | ||
1Department of Physics, McGill University, Montreal, QC, Canada, 2Medical Physics Unit, McGill University, Montreal, QC, Canada, 3McGill University Health Center Research Institute, Montreal, QC, Canada, 4Department of Oncology, McGill University, Montreal, QC, Canada |
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Diffusion MRI with microstructure modeling can nominally map voxelwised cell radii and relative cell volume fractions for the entire tumour. This work proposes a model selection method that chooses the most suitable diffusion model among the two microstructural models and the monoexponential ADC model. This technique can potentially distinguish tissue microstructure featuring one or two underlying cell populations, and acellular necrosis. Microstructural parameters were also reliably estimated. These observations suggest the possible differentiation of three tumour microenvironments resulting from cancer therapy. |
| 4442 | Compartment-specific diffusivity: A new dimension in multidimensional diffusion MRI? | |
| Deneb Boito1,2, Cem Yolçu1, and Evren Özarslan1,2 | ||
1Department of Biomedical Engineering, Linköping University, Linköping, Sweden, 2Center for Medical Image Science and Visualization CMIV, Linköping, Sweden |
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We extend the diffusion tensor distribution imaging framework so that each subdomain making up the tissue is represented by an effective confinement (rather than diffusion) tensor. The confinement tensor is determined by the subdomain’s shape as well as the acquisition parameters and is the physical quantity that leads to microscopic diffusion anisotropy. In this approach, the scalar-valued diffusivity remains as an independent parameter, which could be different in different subdomains. We demonstrate the difficulties in estimating compartment-specific diffusivity alongside the confinement tensor distribution when typical free gradient waveforms are employed. |
| 4443 | Mapping diffusion in aging white matter: A comparison of two free-water modeling approaches | |
| Jordan A. Chad1,2, Ofer Pasternak3, and J. Jean Chen1,2 | ||
1Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada, 2Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada, 3Departments of Psychiatry and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States |
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To gain more insight into age-effects on white matter diffusivity, advanced diffusion MRI models attempt to separate the effect of cellular diffusion from extracellular isotropic water movement by modeling the latter as free water (FW). Using these models, increased diffusivity with age is typically attributed to an enlargement of the FW compartment with age. The current study compares the sensitivity of FW to age using two common modeling approaches: single-shell fwDTI and multi-shell NODDI. |
| 4444 | What’s the FWAF? A Finite Width Adjustment Factor for the effect of finite pulse duration on the diffusion signal in impermeable cylinders | |
| Nadia A S Smith1, Jessica E Talbott1, Chris A Clark2, and Matt G Hall1,2 | ||
1National Physical Laboratory, Teddington, United Kingdom, 2UCL Great Ormond Street Institute of Child Health, University College London, London, United Kingdom |
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A common approach to microstructure imaging in diffusion MRI is to fit the signal with a weighted sum of geometric compartments. This approach is widespread but the need for analytical closed-form solutions necessitates highly restrictive assumptions about the underlying physics which are rarely met in practice. In particular, violation of the narrow-pulse approximation is a significant potential source of bias. This abstract investigates the effect of violating the narrow pulse approximation numerically and proposes a simple effect correction factor to reduce apparent bias as a scale factor on q as a function of δ. |
| 4445
|
Apparent exchange rate (AXR) mapping: Influence of extracellular volume fraction and membrane permeability | |
| Julian Rauch1,2, Tristan Anselm Kuder1, Frederik Bernd Laun3, Karel D. Klika4, Peter Bachert1,2, and Dominik Ludwig1,2 | ||
1Department 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, 4Molecular Structure Analysis, German Cancer Research Center (DKFZ), Heidelberg, 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. However, the measured AXR is also significantly influenced by intra- and extracellular water fractions. In this study, using simulations and experiments with yeast cells, we show that – for low cell concentrations – the AXR exhibits only a moderate dependence on the cell concentration, while for high concentrations, a stronger influence of the packing density on AXR occurs so that it becomes more difficult to disentangle these two influencing parameters. |
| 4446 | Estimation of the vascular fraction in brain tumors by VERDICT correlated with Perfusion MRI | |
| Matteo Figini1, Antonella Castellano2, Valentina Pieri2, Samira Bouyagoub3, Andrea Falini2, Daniel C Alexander1, Mara Cercignani3, and Eleftheria Panagiotaki1 | ||
1Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom, 2Neuroradiology Unit and CERMAC, Vita-Salute San Raffaele University and IRCCS San Raffaele Scientific Institute, Milano, Italy, 3Clinical Imaging Sciences Centre, Brighton and Sussex Medical School, Brighton, United Kingdom |
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We used the VERDICT framework to find clinically useful microstructural models to characterize vasculature in brain tumors. We correlated the vascular fractions, estimated by all possible three-compartment models, with perfusion MRI metrics (plasma volume and cerebral blood volume) derived from independent measurements on the same patients. The models with the strongest correlation with the perfusion MRI and clinical data incorporate spherical restriction for the intracellular compartment, isotropic diffusion for the extracellular compartment, and isotropically hindered or restricted pseudo-diffusion for the vascular compartment. |
| 4447 | Microstructural brain abnormalities and reorganization of early-blind adolescents: a voxel-based diffusion kurtosis imaging study | |
| Zhifeng Zhou1, Xia Liu2, Long Qian3, Gangqiang Hou2, Wentao Jiang2, and Hengguo Li4 | ||
1Radiology, Shenzhen Mental Health Center/Shenzhen Kangning Hospital, Shenzhen, China, 2Shenzhen Mental Health Center/Shenzhen Kangning Hospital, Shenzhen, China, 3GE Healthcare, Beijing, China, 4The First Affiliated Hospital of Jinan University, Guangzhou, China |
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An important focus of blind brain research, especially the early-blind brain, is how to identify the specific neural plasticity patterns. Neuroimaging studies, particularly the diffusion MRI, are powerful probes for characterizing the microstructural changes in human brain. Additionally, previous study indicated that the Diffusion Kurtosis Imaging (DKI) is an advanced diffusion model without the assumption of Gaussian distribution. Taken together, it is feasible to utilize the DKI to investigate the structural neuroplasticity in early-blind brain. Our results demonstrated that the neural reorganization and compensatory development process induced by visual deprivation are coexisted in early-blind adolescents. Furthermore, the diffusion kurtosis metrics are more sensitive to detect the pathology and development related brain regions than diffusion tensor metrics. |
| 4448 | Comprehensive analysis of full-spectrum diffusion weighted MR images with Multimodal Anomalous Diffusion Method (MAD) | |
| Frederick C. Damen1, Mirko Vukelich1, Nitu Saran1, and Kejia Cai1 | ||
1Radiology, University of Illinois at Chicago, CHICAGO, IL, United States |
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In physiological and pathological conditions in which multiple underlying tissue properties are expected to vary the diffusion weighted signal, the diagnostic value of conventional apparent diffusion coefficient (ADC) notably decreases. By fully dissecting the whole spectrum of diffusion weighted imaging (DWI) data from low to high b‑values, we developed a method to extract the anomalous diffusion parameters for four water milieus: flow, and, unrestricted, restricted, and highly restricted diffusion, thus, expounding upon the diverse diffusivity within a voxel. |
| 4449 | Diffusion Tensor Distribution (DTD) MRI Reimagined | |
| Magdoom Kulam Najmudeen1, Michal E Komlosh1,2, Dario Gasbarra3, and Peter J Basser1 | ||
1SQITS/NICHD, National Institute of Health, Bethesda, MD, United States, 2The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, United States, 3University of Helsinki, Helsinki, Finland |
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A new DTD imaging method is presented with novel data acquisition schemes for higher rank b-matrices, and analysis pipeline to estimate the mean and covariance of diffusion tensor. The developed pulse sequence is simple, easy to implement with well defined diffusion, mixing and pulsed gradient dwell times and immune to concomitant fields. The method is validated using PDMS phantom and excised rat brain tissue. Estimated DTD was used to compute the microscopic FA and AD. The phantom results agreed as expected with zero FA and uFA and accurate AD. The approach was able to capture the heterogeneity in the brain. |
| 4450 | Automated segmentation of human axon and myelin from electron microscopy data using deep learning for microstructural validation and simulation | |
| Qiyuan Tian1,2, Chanon Ngamsombat1, Hong-Hsi Lee3,4, Daniel R. Berger5, Yuelong Wu5, Qiuyun Fan1,2, Berkin Bilgic1,2, Dmitry S. Novikov3,4, Els Fieremans3,4, Bruce R. Rosen1,2, Jeff W. Lichtman5, and Susie Y. Huang1,2 | ||
1Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States, 2Department of Radiology, Harvard Medical School, Boston, MA, United States, 3Department of Radiology, Center for Biomedical Imaging, New York University School of Medicine, New York, NY, United States, 4Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, NY, United States, 5Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, United States |
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Diffusion microstructural metrics represent inferences of axonal size and morphology rather than directly imaged quantities, validation of these metrics is essential. With novelty of multibeam-serial electron microscopy, high-resolution images of human white matter can be acquired at nanometer resolution over volumes of tissue large enough to capture the diffusion-MRI dynamics extending over length scales comparable to MRI voxel size. This work presents automated segmentation of serial EM of a sub-volume of human white matter using a 3D convolutional neural network studying variations in axonal diameter over the longest axons within the volume of tissue. |
| 4451 | Time-dependent diffusion in healthy human calf muscle in a clinically feasible acquisition time | |
| Amy R McDowell1, Matthew G Hall1,2, Thorsten Feiweier3, and Chris A Clark1 | ||
1GOS UCL Institute of Child Health, London, United Kingdom, 2Medical Radiation Physics, National Physical Laboratory, London, United Kingdom, 3Siemens Healthcare GmbH, Erlangen, Germany |
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Muscle fibres have a complex hierarchical internal structure which leads to a marked decrease in the observed MR diffusion coefficient with diffusion time. We expect the form of this diffusion time dependence to be highly sensitive to changes in this internal structure. However, characterising the diffusion time dependence in tissue can be highly demanding of total acquisition time. We examine the time-dependence of diffusion indices in human calf muscle in healthy volunteers in a clinically feasible scan time. We find significant time dependence and diffusion restriction in all directions, including longitudinally, due to the internal structure of muscle fibres. |
| 4452 | Brodmann atlas based non-Gaussion water diffusion analysis of normal tension glaucoma: A diffusion kurtosis imaging study | |
| Xiaoxia Qu1, Lizhi Xie2, Qian Wang1, Ting Li1, Jian Guo1, and JunFang Xian1 | ||
1Radiology Department, Beijing Tongren Hospital, Capital Medical University, Beijing, China, 2GE Healthcare, MR Research China, Beijing, Beijing, China |
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To access the non-Gaussion water diffusion characteristic of normal tension glaucoma (NTG), we analyzed the diffusion parameters generated from diffusion kurtosis imaging (DKI). The parameters derived from DKI within changed brain regions of NTG group were reduced and involved the occipital lobe. The visual cortex in NTG group had lower degree of diffusional heterogeneity and microstructural complexity compared to normal control (NC) group. |
| 4453 | Imaging meningioma tumor microstructure: a comparison between quantitative histopathology and high-resolution diffusion tensor imaging | |
| Jan Brabec1, Filip Szczepankiewicz2,3,4, Elisabet Englund5, Johan Bengzon6, Linda Knutsson1,7, Carl-Fredrik Westin2,3, Pia Sundgren4,8, and Markus Nilsson4 | ||
1Clinical Sciences Lund, Medical Radiation Physics, Lund University, Lund, Sweden, 2Department of Radiology, Brigham and Women's Hospital, Boston, MA, United States, 3Harvard Medical School, Boston, MA, United States, 4Clinical Sciences Lund, Diagnostic Radiology, Lund University, Lund, Sweden, 5Clinical Sciences, Oncology and Pathology, Lund University, Lund, Sweden, 6Clinical Sciences, Neurosurgery, Lund University, Lund, Sweden, 7Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States, 8Lund University Bioimaging Center, Lund University, Lund, Sweden |
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We explore anisotropy of meningioma tumors by using structure tensor analysis of histological images and high-resolution diffusion MRI scans. We observed a good visual agreement between the structure- and diffusion-based anisotropy measures, but a more modest quantitative agreement. The results highlight the need to image microscopic rather than voxel-level fractional anisotropy in meningioma tumors. |
| 4454 | In search of the right solution for Ex-Vivo Diffusion Weighted Imaging | |
| Shijia Teo1, Jochen Leupold1, Juergen Hennig1, Marco Reisert1, and Valerij G. Kiselev1 | ||
1Dept. of Radiology, Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany |
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Utilising the right solution in immersing an ex-vivo sample is the first and yet important step in optimising dWI, while preserving the biological and structural integrity of the sample for effective and meaningful repeated scans. In so doing, using 1%PFA, while toxic in preparation, has many other benefits in optimizing diffusion-weighted imaging (dWI). For a safer handling option, PBS + 0.005%NaN3 is also a viable alternative. |
| 4455 | Parcellation of the human brain cortex using a model free, sparse acquisition diffusion MRI approach («S-index») | |
| Tetsuya Yamamoto1, Masaki Fukunaga1, Norihiro Sadato1, and Denis Le Bihan1,2,3 | ||
1Department of System Neuroscience, National Institute for Physiological Sciences, Okazaki, Japan, 2Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan, 3NeuroSpin/Joliot, CEA-Saclay Center, Paris-Saclay University, Gif-sur-Yvette, France |
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We have used a model free diffusion MRI approach (S-index) to classify brain tissue types from the “proximity” or resemblance of their diffusion MRI signal profile at a sparse set of key b values (maximizing sensitivity to tissue microstructure) to a library of “signature” signal profiles (e.g. typical brain grey and white matter). 3D S-index maps have been generated and overlaid on a brain parcellation atlas from the Human Connectome Project showing differences among cortical brain areas. |
| 4456 | Scan-Rescan Reliability of Microstructural Imaging Metrics Derived from High-Gradient Diffusion MRI | |
| Maya Polackal1, Qiyuan Tian1,2, Chanon Ngamsombat1,2,3, Aapo Nummenmaa1,2, Thomas Witzel1,2, Eric C. Klawiter2,4, Susie Y. Huang1,2,5, and Qiuyun Fan1,2 | ||
1Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States, 2Harvard Medical School, Boston, MA, United States, 3Department of Radiology, Faculty of Medicine, Siriraj Hospital, Mahidol University, Thailand, 4Department of Neurology, Massachusetts General Hospital, Boston, MA, United States, 5Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States |
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Scan-rescan reliability of axon diameter index, restricted volume fraction, and DTI metrics derived from high-gradient diffusion MRI was assessed in seven healthy volunteers. Maps of all three metrics were visually comparable from scan/rescan sessions, and moderate to high voxel-wise correlation coefficients were obtained for all metrics. Intraclass correlation coefficients were high for well-defined white matter tracts across all subjects. Our preliminary findings support the robustness and reliability of high-gradient diffusion MR metrics for use in clinical research studies. |
| 4457 | Neuroanatomical underpinning of cerebral cortical mean kurtosis from diffusion MRI | |
| Tianjia Zhu1,2 and Hao Huang1,3 | ||
1Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, United States, 2Bioengineering, University of Pennsylvania, Philadelphia, PA, United States, 3Radiology, University of Pennsylvania, Philadelphia, PA, United States |
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Cortical mean kurtosis (MK) of diffusion MRI characterizes microstructural complexity in the cerebral cortex. In this study, we tested a linear model that soma and neurite densities jointly contributed to MK with different weights. The actual soma and neurite densities were quantified from digitization of macaque brain histological images of Nissl and neurofilament staining. DKI was acquired from 6 postmortem macaque brains. We found actual MK measurement was accurately predicted by a weighted linear combination of soma and neurite densities from histological images with higher neurite density weight. |
| 4458 | Evaluation of Denoising Deep Convolutional Neural Network for Double Diffusion Encoding Technique | |
| Hiroshi Kusahara1, Masanori Ozaki2, Masahiro Abe1, Koji Kamagata3, Masaaki Hori4, and Shigeki Aoki3 | ||
1Advanced MRI development PJ Team, Canon Medical Systems Corporation, Kanagawa, Japan, 2Research&Development Center, Canon Medical Systems Corporation, Kanagawa, Japan, 3Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan, 4Department of Radiology, Toho University Omori Medical Center, Tokyo, Japan |
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Double Diffusion Encoding (DDE) is a diffusion measurement technique that applies two directions of diffusion encoding in parallel and orthogonal directions and can calculate μFA that can evaluate detailed information of anisotropy in voxels. However, since the diffusion encoding method generally acquired many directions, the acquisition time becomes long. In this study, we evaluated DDE technique applying denoising DLR recently developing. It was demonstrated that the dDLR techniques are capable of generating DDE with higher SNR compared to normal DDE, with the additional benefit of being able to optimize the acquisition time and number of acquisitions without affecting μFA. |
| 4459 | Exploring the vascular and neurodegenerative origin of increased interstitial fluid diffusion in intravoxel incoherent motion | |
| Merel M. van der Thiel1,2,3, Whitney M. Freeze2,3,4, Alida A. Postma1, Inge I.C.M. Verheggen1,2,3, Sau M. Wong1, Joost J.A. de Jong1, Frans R.J. Verhey2,3, Inez H.G.B. Ramakers2,3, Walter H. Backes1,3, and Jacobus F.A. Jansen1,3 | ||
1Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, Netherlands, 2Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, Netherlands, 3School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht, Netherlands, 4Department of Radiology, Leiden University Medical Center, Leiden, Netherlands |
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Spectral analysis using non-negative least squares in intravoxel incoherent motion enables estimation of an intermediate component in the diffusion spectrum between parenchymal diffusion and microvascular pseudodiffusion. However, the precise source of the intermediate component remains unknown. By studying the relation of the intermediate component with vascular (i.e. WMH volume) and neurodegenerative (i.e. hippocampal atrophy) biomarkers, the current study aimed to gain more knowledge about the interpretation of the intermediate peak in relation to cognitive status and its underlying pathology. The intermediate peak seems to be a promising imaging biomarker for microvascular and neurodegenerative pathology in Alzheimer’s disease and its prestages. |
| 4460 | Influence of WM fibre orientation on gradient-echo derived tissue parameters | |
| Tonima S Ali1, Elisabeth C van der Voort1,2, and Markus Barth3,4 | ||
1University of Queensland, Brisbane, Australia, 2Eindhoven University of Technology, Eindhoven, Netherlands, 3The University of Queensland, University of Queensland, Brisbane, Australia, 4The ARC Training Centre for Innovation in Biomedical Imaging Technology, University of Queensland, Brisbane, Australia |
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This study investigates the effect of white matter fibre orientation with respect to main magnetic field on gradient-echo (GRE) derived tissue phase, susceptibility, magnetization transfer ratio, R2* and water fraction of myelin water compartments. Spherical deconvolution is used to identify multiple fibre bundles within each imaging voxel. We observed that these GRE derived parameters show moderate sensitivity towards the changes in fibre orientations. Using bi- instead of mono-exponential fitting, it additionally showed that myelin R2* seems more sensitive to the fibre orientation than previously anticipated. |
| 4461 | Preliminary study of diffusion encoding scheme for double diffusion encoding in clinical application on 3T. | |
| Masanori Ozaki1, Hiroshi Kusahara2, Masahiro Abe2, Masaaki Hori3, Koji Kamagata4, and Shigeki Aoki4 | ||
1Research and Development Center, Canon Medical Systems Corporation, Kanagawa, Japan, 2Advanced MRI development PJ Team, Canon Medical Systems Corporation, Kanagawa, Japan, 3Department of Radiology, Toho University Omori Medical Center, Tokyo, Japan, 4Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan |
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Double diffusion encoding (DDE) can measure the microscopic anisotropy (μFA), however one of problems for clinical application is that the acquisition time is prolonged due to the many diffusion encoding patterns necessary. Recently, DDE with a reduced number of acquisitions has been proposed as a solution and been validated as a solution at 9.4T. The aim of this study is to validate the proposed solution for clinical application on 3T clinical scanners. Our results show that our proposed solution can obtain more accurate μFA than previous reported solutions on 3T clinical scanners. |
| 4462 | Precision and goodness of fit of diffusion-based microstructure models in brain tumours: an integrated information theory approach | |
| Umberto Villani1,2, Erica Silvestri1,2, Marco Castellaro1,2, Simona Schiavi3, Mariagiulia Anglani4, Silvia Facchini1,5, Elena Monai1,5, Domenico Davella1,5, Alessandro Della Puppa6, Diego Cecchin7, Maurizio Corbetta1,5,8, and Alessandra Bertoldo1,2 | ||
1Padova Neuroscience Center, University of Padova, Padova, Italy, 2Department of Information Engineering, University of Padova, Padova, Italy, 3Department of Computer Science, University of Verona, Verona, Italy, 4Neuroradiology Unit, University of Padova, Padova, Italy, 5Department of Neuroscience, University of Padova, Padova, Italy, 6Departments of Neurosurgery, Neuroscience, Psychology, Pharmacology, and Child Health, University of Firenze, Firenze, Italy, 7Department of Medicine, Unit of Nuclear Medicine, University of Padova, Padova, Italy, 8Departments of Neurology, Radiology, Neuroscience, Washington University School of Medicine, St.Louis, MO, United States |
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Diffusion-based microstructure modeling techniques potentially provide significant biomarkers to characterize the tumoral architecture in the human brain. While clinical studies focus on the application of these technique, not enough care is being devoted to understand whether the employed models provide precise and reliable parameter estimates when fitted on the cancerous tissues. The present works tackles these issues on a cohorts of 11 patients diagnosed with different types of brain tumours by quantifying the variance of parameter estimates and the goodness-of-fit in an integrated view borrowing concepts from information theory. |
| 4463 | Diffusion MRI with tensor-valued diffusion encoding as a marker of axonal content within malformations of cortical development | |
| Björn Lampinen1, Ariadne Zampeli2, Filip Szczepankiewicz3,4, Kristina Källén5, Maria Compagno Strandberg2, Isabella Björkman-Burtscher6, and Markus Nilsson3 | ||
1Clinical Sciences Lund, Medical Radiation Physics, Lund University, Lund, Sweden, 2Clinical Sciences Lund, Neurology, Lund University, Lund, Sweden, 3Clinical Sciences Lund, Diagnostic Radiology, Lund University, Lund, Sweden, 4Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States, 5Clinical Sciences Lund, AKVH-Neurology Helsingborg, Lund University, Lund, Sweden, 6Radiology, Sahlgrenska university hospital, Gothenburg, Sweden |
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MRI is central to presurgical workup for malformations of cortical development (MCD) but findings are ambiguous on morphological imaging. For example, assessments on cortical thickness may disagree with histology. We investigated whether this gap may be bridged by diffusion MRI (dMRI) with the novel ‘tensor-valued diffusion encoding’ technique. Results from thirteen patients showed WM-like content with high microscopic anisotropy within lesions that were uniform and GM-like in T1- and T2-weighted images and on conventional dMRI. As a marker of axonal content less confounded by myelination and orientation dispersion, tensor-valued diffusion encoding may improve MCD characterization and evaluation of cortical thickness. |
| 4464 | Diffusion Tensor Tractography of Tendons as a Tool for Assessing MRgFUS Ablation | |
| William Chu Kwan1, Warren Foltz2, Ben Keunen1, Matt Walker3, Karolina Piorkowska1, Adam Waspe1, and James Drake4 | ||
1Center for Image Guided Innovation and Therapeutic Intervention, Hospital for Sick Children, Toronto, ON, Canada, 2Radiation Oncology, University Health Network, Toronto, ON, Canada, 3Krembil Research Institute, University Health Network, Toronto, ON, Canada, 4Department of Surgery, Center for Image Guided Innovation and Therapeutic Intervention, Hospital for Sick Children, Toronto, ON, Canada |
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MRgFUS ablation of tendons is a promising treatment to disrupt tendons in conditions such as musculotendinous contractures. In this study, DTI and tractography were proposed as tools to assess tendons before and after MRgFUS ablation, providing a quantitative, directional, and visual assessment of tendon tract architecture and integrity. Diffusivity parameters (FA and ADC) changed in accordance to the tendon fascicle integrity. Fiber tractography visually delineated healthy tendon fascicles and confirmed tract disruptions at the same location as registered with b0 and T1-weighted images. This study demonstrates the potential for DTI and tractography as assessment tools for MRgFUS ablation treatments. |
| 4465 | A novel ex vivo structural connectome atlas of the C57Bl6 mouse brain using ultra-high field diffusion MRI at 17.2T | |
| Ivy Uszynski1, Roxane Golgolab1, David A. Barrière1, Tomokazu Tsurugizawa1, Michel Simonneau2,3,4,5, Luisa Ciobanu1, and Cyril Poupon1 | ||
1NeuroSpin, CEA, Gif-sur-Yvette, France, 2Centre Psychiatrie & Neurosciences, INSERM U894, Paris, France, 3Ecole Normale Supérieure Paris-Saclay & LAC-CNRS, Institut d’Alembert, Cachan, France, 4LBPA, Institut d’Alembert, Ecole Normale Supérieure Paris-Saclay, Université Paris-Saclay, Cachan, France, 5Département de Biologie, Ecole Normale Supérieure Paris-Saclay, Université Paris-Saclay, Cachan, France |
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Diffusion MRI is a powerful tool to investigate the structural connectivity of the brain. Ultra-high field preclinical MRI systems are equipped with strong gradients that allow to reach higher spatial and angular resolutions in animal models, enabling to segment white matter bundles in a similar way to what was achieved in humans. In this study, we propose to adapt the clustering approach of Guevara to rodents to establish a novel atlas of the connectivity of C57BI6 mice brains. 3D Hybrid diffusion imaging was performed ex-vivo allowing the reconstruction of a novel white matter atlas including 25 well-described fiber bundles. |
| 4466 | Investigating SLFI anatomy using multi-resolution dMRI | |
| Chiara Maffei1, Robert Jones1, Connor Johnson2, Hui Wang1, and Anastasia Yendiki1 | ||
1Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States, 2Brown University, Providence, RI, United States |
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The ability of tractography methods to discern between different fiber populations in the presence of challenging anatomical architectures remains limited, and it is hampered by the low spatial resolution achievable by diffusion MRI (dMRI). As a result, tractography often fails to reliably reconstruct some major white matter connections of the human brain. Here we incorporate high-resolution ex-vivo dMRI into the tractography process to understand whether this additional information can improve tractography results. |
| 4467 | Cortical projections of the superoanterior fasciculus (SAF) | |
| Szabolcs David1, Michel Thiebaut de Schotten2, Fenghua Guo1, Flavio Dell’Acqua3, Alexander Leemans1, and Alberto de Luca1 | ||
1Image Sciences Institute, UMC Utrecht, Utrecht, Netherlands, 2Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France, 3NatBrainLab, Department of Forensics and Neurodevelopmental Sciences, Sackler Institute for Translational Neurodevelopment, King's College London, London, United Kingdom |
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The superoanterior fasciculus (SAF) is defined as a bilateral tract in the frontal lobe that resembles the structure of the anterior cingulum, but is located superior, anterior and lateral. In this work, we investigated the cortical projections of the structure utilizing the latest multi-shell multi tissue (MSMT) constrained spherical deconvolution (CSD) method to analyze diffusion MRI data from the Human Connectome Project (HCP). Our results show that the paracentral lobular, mid cingulate cortex and the orbital- and polar frontal cortex show high SAF termination prevalence, suggesting a novel connection in the frontal lobe. |
| 4468 | Diffusion MRI analysis of complex fiber configurations in human brain white matter and cortex | |
| Szabolcs David1, Hamed Y Mesri1, Fenghua Guo1, Alexander Leemans1, and Alberto de Luca1 | ||
1Image Sciences Institute, UMC Utrecht, Utrecht, Netherlands |
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Fiber configurations in the human brain white matter and cortex are dominant with multiple orientations. In this work, we investigated the prevalence of crossing fibers in the brain, utilizing the latest multi-shell multi tissue (MSMT) constrained spherical deconvolution (CSD) method to analyze diffusion MRI data from the Human Connectome Project (HCP). Voxel-wise number of fiber orientation (NuFO) was calculated from 56 subjects, using the Generalized Richardson Lucy (GRL) framework, which offers robust fiber orientation distribution (FOD) estimation. Our results suggest that 83% of the voxels have at least one and 37% of the voxels have at least two fiber orientations. |
| 4469 | Does the intensity inhomogeneity field in diffusion MRI data affect constrained spherical deconvolution results? | |
| Alberto De Luca1, Hamed Yousefi Mesri1, Szabolcs David1, Martijn Froeling2, and Alexander Leemans1 | ||
1Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands, 2Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands |
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The correction for the intensity inhomogeneity field (IIF) is becoming de-facto a pre-processing step in diffusion MRI, but its effect on CSD remains unclear. In this study, we investigated the fundamental effects of the IIF on CSD and the effectiveness of corrections based on a tool commonly applied to structural MRI (N4ITK). We show that the IIF modulates the amplitude of the fiber orientation distribution (FOD), influencing not only the estimation of the response function, but also subsequent uses of the FOD amplitude, as tractography termination criteria or the estimation of the number of fibers (NuFO). |
| 4470 | RIPPLE: A new framework for estimating rotationally-invariant with paired-ODF spatial correlations in fiber tracking using MRI | |
| Ying-Chia Lin 1,2, Steven Baete1,2, Xiuyuan Wang1,2, and Fernando Boada1,2 | ||
1Center for Biomedical Imaging, Department of Radiology, NYU School of Medicine, New York, NY, United States, 2Center for Advanced Imaging Innovation and Research (CAI2R), NYU School of Medicine, New York, NY, United States |
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Quantification of internal structure (i.e., microstructure) is central to for the modeling of diffusion signals. In recent years, rotationally-invariant measures have generated significant attention because of their tremendous potential for characterizing the underlying structural information contained in the orientation-distribution-function (ODF). We demonstrate the use of a new approach for the analysis of long-range structural connectivity based on the use of pairwise correlations between ODF’s. This approach is shown to better capture differences between the underlying morphological features present within a fiber bundle. |
| 4471 | The investigation of topological contributions: A novel approach for modelling brain networks | |
| Xiaoyun Liang1,2, Chun-Hung Yeh2, Govinda Poudel1, Juan F Domínguez D1, and Karen Caeyenberghs1 | ||
1Mary Mackillop Institute for Health Research, Australian Catholic University, Melbourne, Australia, 2Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia |
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Diffusion MRI streamline tractography offers a unique approach to probe into such mechanisms underlying structural brain network. In this study, we propose modelling network strength based on both fibre length and topological profile of brain network. The proposed model leads to more robust fitting outcomes. Meanwhile, our results show that network thresholding could dramatically alter the relationship between the connection strength and physical length; this would inevitably compromise further network analyses. Further results demonstrate that within- and between-hemisphere connections bear distinct patterns in terms of the relationship between network strength and topological correlation matrix. |
| 4472 | Redundancy of arousal brainstem structural connectivity pathways in humans by 7 Tesla HARDI | |
| María Guadalupe García-Gomar1, Kavita Singh1, and Marta Bianciardi1 | ||
1Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States |
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Arousal plays a crucial role in wakefulness/sleep, autonomic function, affect and attention. Recent meta-analysis of rat neuroanatomical macroconnectome based on pathway-tracing studies showed redundancy of arousal mechanism through the presence of multiple connectivity pathways and of high interconnectivity among arousal brainstem nuclei. Using 7 Tesla HARDI MRI and a recently developed brainstem nuclei atlas, we build the structural connectome of brainstem arousal nuclei in living humans. In line with rat studies, this connectome showed high redundancy through the presence of multiple interconnected pathways. This connectome might be used to better understand arousal and its impairment. |
| 4473 | What factor influences most the reproducibility of MRI-based white matter tract estimation using probabilistic tractography? | |
| Irène Brumer1,2,3, Enrico De Vita1, Jonathan Ashmore2,4, Jozef Jarosz2, and Marco Borri2 | ||
1Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King’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 |
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MRI-based white matter tract estimation using probabilistic tractography is valuable for presurgical planning. In this work, we investigate three factors influencing the reproducibility of probabilistic tractography: the tract threshold used to visualise the analysis results in the final tractography image, the manually drawn seed region, and the end region of the tracts. A compromise between low risk and high reproducibility has to be found for the tract threshold. The end region definition was found to be the most important parameter for the inter-user reproducibility of restricted tracts. Good inter-user reproducibility for the unrestricted tracts is achievable for similar seed regions. |
| 4474 | Mapping white matter specificity captured by diffusion tractography through deep learning on structural MRI | |
| Qi Yang1, Colin Hansen1, Francois Rheault2, Bramsh Qamar3, Owen Williams4, Susan Resnick4, Eleftherios Garyfallidis3, Adam W Anderson5,6, Maxime Descoteaux2, Bennett A Landman5,6,7,8, and Kurt G Schilling5 | ||
1Computer Science, Vanderbilt University, Nashville, TN, United States, 2Sherbrooke Connectivity Imaging Laboratory (SCIL), Universite de Sherbrooke, Sherbrooke, QC, Canada, 3Intelligent Systems Engineering, Indiana University Bloomington, Bloomington, IN, United States, 4Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, United States, 5Vanderbilt University Institute of Imaging Science, Nashville, TN, United States, 6Biomedical Engineering, Vanderbilt University, Nashville, TN, United States, 7Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States, 8Electrical Engineering, Vanderbilt University, Nashville, TN, United States |
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We investigate the value added by diffusion fiber tractography dissection of white matter pathways over standard T1w images in which WM is largely homogenous. We analyze structural differences in pathway segmentations between a deep learning network trained to label WM directly on T1w images and the same pathways dissected using tractography, and find that although the core of the stem of many fiber bundles is accurately delineated, the value of tractography is in delineating terminal connections and determining fine-scale stem geometrical properties. Thus, while localizing regions-of-interest is possible in structural images, tractography is needed for increased pathway and connection information. |
| 4475 | Clinical Recovery of intracellular volume fraction and fiberODF for a patient with asymptomatic temporal-occipital lesion using Deep Learning | |
| Sudhir Kumar Pathak1, Vishwesh Nath2, Sandip Panesar3, Kurt G. Schilling4, Juan Carlos Fernandez-Miranda3, Bennett A. Landman2,5, and Walter Schneider1 | ||
1Learning Research and Development Center, University of Pittsburgh, Pittsburgh, PA, United States, 2Electrical Engineering & Computer Science, Vanderbilt University, Nashville, TN, United States, 3Department of Neurosurgery, Stanford University, Palo Alto, CA, United States, 4Radiology, Vanderbilt University Medical Center, Nashville, TN, United States, 5Biomedical Engineering, Vanderbilt University, Nashville, TN, United States |
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Diffusion-weighted magnetic resonance imaging (DW-MRI) offers a unique insight on microarchitecture of the in-vivo human brain. Multiple well-known reconstruction methods that model geometrical and micro-structural properties of the tissue such as multi-tissue constrained spherical deconvolution (MT-CSD) and spherical mean technique (SMT) rely on high quality acquisitions (more than 2 shells and 45 gradient directions) which is a constraint. We propose recovery of fiber-ODFs, compartment diffusivities and volume-fractions using a two-stage deep learning framework by training on human-connectome-project dataset. The proposed approach can predict fiber-ODFs using single shell DW-MRI on a tumor patient and assess the diseased region of interest. |
| 4476 | Longitudinal white matter changes in the callosal subsections in Parkinson’s Disease using connectivity-based parcellation. | |
| Jingjing Wu1, Xiaoujun Guan1, Tao Guo1, Cheng Zhou1, Ting Gao2, Peiyu Huang1, Xiaojun Xu1, and Minming Zhang1 | ||
1Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China, 2Department of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China |
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Corpus callosum (CC) is the most important association fiber intrinsically connecting with different cortical regions. Studies reported the CC and its subsections could be used to differentiate different phenotypes in PD, PD and PDS. In this study, 39 PD patients with a mean time interval of 21m and 82 NC were recruited. We segmented the whole CC into five subsections according to their functional connectivity with predefined cortices. As a result, we observed that the microstructure and structure were fairly preserved in PD at baseline, but widespread changes occur in the corpus callosum during PD evolvement. |
| 4477 | Gender differences in brain white matter discovered by whole brain suprathreshold fiber cluster statistics | |
| Fan Zhang1, Suheyla Cetin-Karayumak1, Yang Song2, Weidong Cai3, James J Levitt1, Nikos Makris1, Carl-Fredrik Westin1, and Lauren J O'Donnell1 | ||
1Harvard Medical School, Boston, MA, United States, 2The University of New South Wales, Sydney, Australia, 3The University of Sydney, Sydney, Australia |
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We propose to study whole-brain white matter connectivity differences between females and males using diffusion MRI (dMRI) tractography. We leverage a well-established data-driven fiber clustering pipeline and a novel suprathreshold fiber cluster statistical method. We study a large cohort of 707 healthy adult subjects from the Human Connectome Project. We find multiple fiber tracts that are significantly different between the female and male groups in terms of the fractional anisotropy and/or the trace measures of the fiber tracts. These tracts include the corticospinal tract, the arcuate fasciculus, and the corpus callosum tract. |
| 4478 | MODELLING NEURAL EXCITABILITY OF REALISTIC DTI-DERIVED AXON TRAJECTORIES | |
| Sulagna Sahu1, Munish Chauhan1, Saurav Zaman Khan Sajib1, Stephen Helms Tillery1, Vikram D. Kodibagkar1, and Rosalind J. Sadleir1 | ||
1Arizona State University, Tempe, AZ, United States |
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Studying neural activation patterns is critical in the understanding of neuromodulation in transcranial electrical stimulation methods (TES). This research focuses on simulations of neural excitability of a realistic axon model obtained from DTI tractography of the trigeminal nerve, in comparison to a linear axon model obtained from literature, in presence of induced electric fields found from realistic FEM (finite element method) modelling of TES. The differences observed highlight the need for use of realistic trajectories in neural simulations and provide means for patient specific personalized studies. |
| 4479 | Comparison of interconnected basal ganglia probabilistic tractography between 3T and 7T MRI Images | |
| Jae-Hyuk Shim1 and Hyeon-Man Baek1 | ||
1Gachon University, Incheon, Republic of Korea |
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Basal ganglia structures, globus pallidus internal, globus pallidus external, subthalamic nucleus, substantia nigra, red nucleus and striatum were automatically segmented on 3T and 7T HCP preprocessed diffusion weighted images. Connectivity between each basal ganglia structure was observed using probabilistic tractography generated with FSL's diffusion tools such as BEDPOSTX and PROBTRACKX. Tractography between basal ganglia was compared between 3T and 7T to observe differences that arise from tradeoffs of each acquisition. |
| 4480 | Investigating age-related differences in fractional anisotropy in relation to complex fibre architecture | |
| Jordan A. Chad1,2, Ofer Pasternak3, and J. Jean Chen1,2 | ||
1Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada, 2Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada, 3Departments of Psychiatry and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States |
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It is well established that white matter diffusion fractional anisotropy (FA) is sensitive to age, but interpreting this effect in terms of cellular microstructure has posed a challenge. Here we investigate how age-related differences in FA relate to measures of crossing and dispersing fibres derived from advanced diffusion MRI models. We find that, in aging, decreased FA is associated with increased fibre dispersion, and increased FA is associated with selective degeneration of crossing fibres. Importantly, we show that age-related differences in FA more closely reflect age-related differences in fibre architecture when applying free water elimination. |
| 4481 | Comparison of Basal Ganglia-based Structural Connectome between 6-OHDA-induced Parkinson Mouse Model and Normal Mouse Model | |
| Ayoon Kim1 and Hyeon-Man Baek1 | ||
1Department of Health Science and Technology, GAIHST, Gachon University, gachon university, Incheon, Republic of Korea, Republic of Korea |
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The study on probabilistic connectivity of basal ganglia have not reported in mouse model. However, we have quantified fiber connectivity and visualized specific tractography pathway. The basal ganglia is a complex system of a subcortical nuclei network which plays a fundamental role in a wide range of processes related to motor and limbic functions. Altered neural connectivity of basal ganglia may contribute to a number of neurologic and psychiatric disease such as Parkinson’s disease. This study shows that probabilistic diffusion tractography allows for detailed 3D reconstruction of the projections of basal ganglia in ex vivo control and PD mouse brain. |
| 4482 | Detecting neuronal connectivity using diffusion tensor imaging in a Parkinson`s disease mouse basal ganglia using 9.4T MRI | |
| Sang-Jin Im1 and Hyeon-Man Baek1 | ||
1Gachon university, Incheon, Korea, Republic of |
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Parkinson's disease (PD) is a neurodegenerative disorder that affects motor and cognition, resulting from dopaminergic cell death in substantia nigra (SN). Basal ganglia, a neural circuit involved in executive functions such as motor control and have been studied extensively in PD mouse models. Mouse brain tractography using MRI have seen increasing use to study neural networks but more comprehensive analysis is needed to establish a stronger consensus. The purpose of this study is to provide a comprehensive analysis of basal ganglia neuronal connectivity in control and PD mouse models. |
| 4483 | Quantitative assessment of multi-scale tractography: bridging the resolution gap with 3D-Polarized Light Imaging | |
| Abib Alimi1, Matteo Frigo1, Samuel Deslauriers-Gauthier1, and Rachid Deriche1 | ||
1Athena Project-Team, Inria Sophia Antipolis Méditerranée, Université Côte d'Azur, Sophia Antipolis, France |
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Three-dimensional Polarized Light Imaging (3D-PLI) is an optical technique presented as a good candidate for validation of diffusion Magnetic Resonance Imaging (dMRI) results such as orientation estimates and tractography. We previously demonstrated a multi-scale tractography approach using 3D-PLI. Here, we show how tractograms obtained at different spatial scales from 3D-PLI human brain datasets can be inspected using homology theory in order to perform a quantitative comparison between them. This paves the way for the validation of tractography obtained from dMRI using multi-scale fiber tracking based on 3D-PLI. |
| 4484 | Aligning Shapes of Along-tract Diffusion Profiles across Populations | |
| David Soobin Lee1, Antoni Kubicki1, Ashish Kaul Sahib1, Katherine L Narr1, and Shantanu H Joshi1 | ||
1UCLA, Los Angeles, CA, United States |
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Various tools exist to extract diffusion measures from tract profiles. However, they lack the precision in terms of statistical analysis since the tract shapes are registered to a common template. Although this analysis leads to meaningful results, we postulate that there is a significant geometric information in the along-tract diffusion profiles that is unaccounted for. Here we propose a novel method for aligning shapes of diffusion profiles across populations. This method offers improved matching and statistical analysis of along-tract diffusion profiles. Furthermore, this method could be used to perform multivariate statistical analysis of along-tract diffusion profiles in an invariant manner. |
| 4485 | Application of Diffusion MRI ODF-Fingerprinting for Neurosurgical Tractography | |
| Genevieve Barroll1,2, Dimitris Placantonakis, M.D., Ph.D.3, Fernando E. Boada, Ph.D. 1, Timothy Sheperd, M.D., Ph.D.1,2, and Steven Baete, Ph.D.1,2 | ||
1Center for Biomedical Imaging, Dept. of Radiology, NYU School of Medicinie, New York, NY, United States, 2Center for Advanced Imaging Innovation and Research (CAI2R), NYU School of Medicine, New York, NY, United States, 3Department of Neurosurgery, Perlmutter Cancer Center, Neuroscience Institute, Kimmel Center for Stem Cell Biology, NYU School of Medicinie, New York, NY, United States |
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The ODF-Fingerprinting method has proven to be successful in improving detection of fiber pairs with small crossing fibers [1]. We evaluated the performance of ODF-Fingerprinting and other algorithms used to detect fiber directions, to determine whether the clinical application contains the same success that was experienced in a healthy control. The performance of these competing algorithms was examined in a healthy control and post-operative scan of a tumor patient. With the success of ODF-Fingerprinting in comparison to other algorithms, we hope that the application of this algorithm will lead to improved neurosurgical precision. |
| 4486 | Advantage of readout-segmented EPI in simultaneous multi-slice diffusion MRI measurements for identifying uncinate fasciculus | |
| Hiromasa Takemura1,2, Wei Liu3, Hideto Kuribayashi4, and Ikuhiro Kida1,2 | ||
1Center for Information and Neural Networks, National Institute of Information and Communications Technology, Suita, Japan, 2Graduate School of Frontier Biosciences, Osaka University, Suita, Japan, 3Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China, 4Siemens Healthcare K.K., Tokyo, Japan |
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We evaluated the performance of diffusion MRI (dMRI) acquisition with simultaneous multi-slice (SMS) readout-segmented echo-planar imaging (rs-EPI) in measuring the uncinate fasciculus, which is typically affected by susceptibility-induced distortion or signal dropout. We found that SMS rs-EPI data provides a larger number of streamlines supported by dMRI data and larger fractional anisotropy in uncinate, as compared to conventional SMS single-shot EPI data. However, such an advantage was not consistent across subjects in the forceps major. Taken together, our results demonstrate that dMRI acquisition with SMS rs-EPI has advantages in measuring specific white matter tracts affected by susceptibility-induced artifacts. |
| 4487 | Does introduction of priors improve reliability to segment hyperdirect connections using tractography for Deep Brain Stimulation ? | |
| Tristan MOREAU1, Maxime PERALTA1, John BAXTER1, and Pierre JANNIN1 | ||
1UMR 1099 LTSI, RENNES, France |
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A better knowledge of subthalamic nucleus connections could help predict the clinical outcome of deep brain stimulation in the context of Parkinson’s disease. However, diffusion weighted images used in clinical context are generally of poor resolution. In this study, we compared a whole brain versus an a-priori-based tractography method in order to segment hyperdirect connections linking subthalamic nucleus to cortex on normal controls acquired in clinical context. In systematically comparing our hyperdirect connections segmentation results with high resolution data set, we showed better reliability when using the a-priori-based tractography compared to the whole-brain method. |
| 4488 | Assessing scan-rescan reproducibility of surgically relevant white matter tractography reconstructions | |
| Kan Yan Chloe Li1,2, Leevi Kerkelä1, Jonathan D Clayden1, Kiran K Seunarine1, Matt G Hall1,2, and Chris A Clark1 | ||
1UCL Great Ormond Street Institute of Child Health, London, United Kingdom, 2National Physical Laboratory, Teddington, United Kingdom |
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Tractography is regularly used in neuroscientific research and neurosurgical planning for its ability to delineate fibre bundles non-invasively. The construction and analysis of tractograms often requires user-defined parameter choices such as streamline density thresholding for estimating tract volume. In this study, we assessed the reproducibility of a manual tractography pipeline that is applied in neurosurgical planning for oncology and epilepsy operations, and quantified the effect of streamline density thresholding on reproducibility. The pipeline was found to be robust in terms of reproducibility over the range of investigated thresholding levels with some variability between tracts. |
| 4489 | SlicerDMRI: a suite of clinician-accessible tools for neurosurgical planning research using diffusion MRI and tractography | |
| Fan Zhang1, Thomas Noh1, Parikshit Juvekar1, Sarah F Frisken1, Laura Rigolo1, Isaiah Norton1, Tina Kapur1, Sonia Pujol1, William Wells III1,2, Alex Yarmarkovich3, Gordon Kindlmann4, Demian Wassermann5, Raul San Jose Estepar1, Yogesh Rathi1, Ron Kikinis1,6, Hans J Johnson7, Carl-Fredrik Westin1, Steve Pieper3, Alexandra J Golby1, and Lauren J O'Donnell1 | ||
1Harvard Medical School, Boston, MA, United States, 2Massachusetts Institute of Technology, Boston, MA, United States, 3Isomics, Inc., Cambridge, MA, United States, 4University of Chicago, Chicago, IL, United States, 5Université Paris-Saclay, Palaiseau, France, 6University of Bremen and Fraunhofer MEVIS, Bremen, Germany, 7University of Iowa, Iowa City, IA, United States |
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We present an open-source software suite, SlicerDMRI (dmri.slicer.org), that enables neurosurgical planning research using diffusion magnetic resonance imaging (dMRI). SlicerDMRI is built upon and deeply integrated with 3D Slicer, an NIH-supported open-source platform for medical image informatics, image processing, and three-dimensional visualization. In this work, we give a demonstration of SlicerDMRI to enable end-to-end dMRI analyses in two retrospective imaging datasets from patients with high-grade glioma. Analyses demonstrated here include conventional diffusion tensor imaging (DTI) analysis, advanced multi-fiber tractography, automated identification of critical fiber tracts, and integration of multimodal imagery with dMRI. |
| 4490 | Assessing brain wiring patterns using tractography fiber clustering to study sex differences of the frontostriatal white matter connections | |
| Fan Zhang1, Mark Vangel1, Marek Kubicki 1, Martha E Shenton1, Lauren J O'Donnell1, and James J Levitt1 | ||
1Harvard Medical School, Boston, MA, United States |
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We studied structural connectivity differences between females and males in frontostriatal white matter connections. We proposed a novel method to measure the topographical organization of the frontostriatal circuits, leveraging a data-driven fiber clustering of whole-brain dMRI tractography. The proposed topographical measure provides important information to assess the segregated and integrative brain wiring patterns in the human brain. We applied this technique to test for sex differences in a cohort of 100 healthy subjects. We identified significant group differences in the frontostriatal white matter connections, potentially related to the sex-specific brain wiring patterns. |
| 4491 | Diffusion MRI simulation of realistic neurons with SpinDoctor and the Neuron Module | |
| Van-Dang Nguyen1, Chengran Fang2,3, Demian Wassermann3, and Jing-Rebecca Li2 | ||
1Department of Computational Science and Technology, KTH Royal Institute of Technology, Stockholm, Sweden, 2INRIA-Saclay, Equipe DEFI, Palaiseau, France, 3INRIA Saclay, Equipe Parietal, Palaiseau, France |
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The dMRI simulation arising from realistic neurons can help investigate the cellular microstructure. Ensuring correct connectivity between distinct cellular compartments while minimizing the computational burden is one of the main challenges. The design of simulation algorithm and the construction of high-quality neuron meshes are crucial. The NeuronModule can perform HARDI simulation of realistic neurons at various b-values and diffusion sequences with high accuracy. The computational time per gradient-direction is around 30 seconds which is faster than some Monte-Carlo simulators. The linearity between the diffusion-direction-averaged signal and one over square root of b for tubular structures is validated by our simulations. |
| 4492 | Structural connectivity analysis of anterior nuclei of the thalamus in Papez circuit based on DW-MRI fiber tractography for ANT-DBS in epilepsy | |
| Ruhunur Özdemir1,2, Kai Lehtimäki3, Jukka Peltola1,3, and Hannu Eskola1,2 | ||
1Department of Medicine and Health Technology, Tampere University, Tampere, Finland, 2Department of Radiology, Tampere University Hospital, Tampere, Finland, 3Department of Neuroscience and Rehabilitation, Tampere University Hospital, Tampere, Finland |
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The white matter organization of anterior nuclei of thalamus (ANT) has not been comprehensively examined before. We visualized white matter tracks in Papez circuit determining different ROIs in ANT, cingulate gyrus, mammillothalamic body, hippocampus and parahippocampal region for ANT-DBS in epilepsy. We employed constrained spherical deconvolution (CSD), multi-shell multi-tissue (MSMT) CSD, and DTI model to characterize white matter tissue organization in healthy controls and one patient diagnosed with refractory epilepsy in DW-MRI. We demonstrate a connectivity pattern of ANT. CSD model tractography may provide consistent insights on the alteration of the connections in patients with refractory epilepsy for performing ANT-DBS. |
| 4493 | Diffusion MRI-based Connectivity Enriched with Microstructure Information Predicts the Propagation of Cortico-Cortical Evoked Potentials | |
| Patryk Filipiak1, Fabien Almairac2, Théodore Papadopoulo1, Denys Fontaine2, Lydiane Mondot3, Stéphane Chanalet3, Rachid Deriche1, Maureen Clerc1, and Demian Wassermann4 | ||
1INRIA Sophia Antipolis - Méditerranée, Valbonne, France, 2Service de Neurochirurgie, Centre Hospitalier Universitaire de Nice, Université Côte d’Azur, Nice, France, Nice, France, 3Service de Radiologie, Centre Hospitalier Universitaire de Nice, Université Côte d’Azur, Nice, France, Nice, France, 4INRIA, CEA, Université Paris-Saclay, Paris, France, Paris, France |
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The propagation of Cortico-Cortical Evoked Potentials (CCEPs) varies depending on numerous structural features of brain tissue. In this work, we show that combined dMRI-based connectivity enriched with microstructure data has the potential to measure cortico-cortical communication as it predicts CCEP-based effective connectivity. Our multiple linear regression model incorporates q-space indices like Q-space Inverse Variance, Non-Gaussianity and Return to Plane Probability with minimum streamline lengths obtained from tractography to predict delays and amplitudes of the P1 peaks in CCEPs. In our experiment, we use presurgical dMRI and intrasurgical ECoG recordings of 9 patients operated on brain tumor in the awake condition. |
| 4494 | Structural connectome of autonomic and sensory brainstem nuclei in humans based on 7 Tesla high spatial and angular resolution diffusion imaging | |
| KAVITA SINGH1, María Guadalupe García-Gomar1, Jeffery P Staab2,3, Simone Cauzzo4, Iole Indovina5,6, and Marta Bianciardi1 | ||
1Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States, 2Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States, 3Department of Otolaryngology, Head and neck Surgery, Mayo clinic, Rochester, MN, United States, 4Institute of Life Sciences, Sant'Anna School of Advanced Studies, Pisa, Italy, 5Laboratory of neuromotor physiology, IRCCS, Santa Lucia Foundation, Rome, Italy, 6Centre of SpaceBiomedicine, University of Rome for Vergata, Rome, Italy |
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With the advancement of imaging technologies and signal processing tools, ample progress has been made in cortical and sub-cortical brain structural connectivity mapping; however, this is still missing in living humans for brainstem nuclei. Through high spatial-resolution 7 Tesla HARDI MRI and a recently developed probabilistic brainstem nuclei atlas, we built a structural connectome of autonomic and sensory brainstem nuclei in living humans. Interestingly, our connectome corresponded well with established non-human connectivity data. We foresee this connectome as basis for structural and functional studies of autonomic and sensory circuits in health and disease. |
| 4495 | 3D-printed phantom for validating diffusion MRI models | |
| Michael Woletz1, Franziska Gantner2,3, Benedikt Hager4, Peter Gruber2,3, Siawoosh Mohammadi5,6, Zoltan Nagy7, Aleksandr Ovsianikov2,3, and Christian Windischberger1 | ||
1Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria, 2Institute of Materials Science and Technology, Technical University Vienna, Vienna, Austria, 3Austrian Cluster for Tissue Regeneration, Vienna, Austria, 4Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria, 5Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany, 6Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 7Laboratory for Social and Neural Systems Research (SNS Lab), University of Zurich, Zurich, Switzerland |
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Here we show the first DTI phantom manufactured by advanced high-resolution 3D-printing methods. The phantom consists of hollow, 12μm thin, liquid filled channels, that can be constructed in arbitrary configurations, ideally suited for validating diffusion sequences and analysis models. A simple configuration with orthogonal channel directions is presented. Diffusion weighted images were acquired and a diffusion tensor model employed. The main direction of the resulting tensors is accurately able to capture the directions of the channels with an average fractional anisotropy of 0.46. This method for creating diffusion phantoms will help to test and validate different models in the future. |
| 4496 | Water diffusion pore imaging on a 14.1 T spectrometer using glass capillary phantoms in the presence of extraporal fluid | |
| Dominik Ludwig1,2, Frederik Bernd Laun3, Karel D. Klika4, Mark Edward Ladd1,2,5, Peter Bachert1,2, and Tristan Anselm 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 and matching the magnetic susceptibility, it was possible to acquire diffraction patterns of glass capillaries that were placed orthogonal to the main magnetic field. Furthermore, the feasibility of doing DPI in the presence of water outside the pores was demonstrated for the first time. |
| 4497 | Validation of NMR transient subdiffusion in controlled samples | |
| Silvia Capuani1, Fabio Micalizzi2, Simona Sennato3, Giulio Costantini3, Roberto Matassa4, Dante Rotili5, Lorenzo Correale2, Francesca Giuffrida2, Annalisa Caligiuri2, Giovanni Familiari4, and Andrea Gabrielli3 | ||
1Physics Dpt. Sapienza, CNR ISC, Rome, Italy, 2Physics Dpt., Sapienza University of Rome, Rome, Italy, 3Physics Dpt. Sapienza Roma, CNR ISC, Rome, Italy, 4Anatomical, Histological, Forensic Medicine and Orthopedics Sciences, Sapienza University of Rome, Rome, Italy, 5Drug chemistry and technology department, Sapienza University of Rome, Rome, Italy |
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The quantification of transient anomalous diffusion (tAD) parameters by NMR could provide higher sensitivity, resolution and complementary detailed information for detecting early changes due to pathological conditions than the conventional metric does. However, there are some questions and controversial issues which prevent the take-off of tAD NMR investigations in soft condensed matter and medical diagnostic field. To overcome these obstacles, we planned to investigate the potential and limits of NMR subdiffusion in calibration standards characterized by porous structured materials and diffusing probes matching or not characteristics length-scales of the porous matrix.
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| 4498 | Phantom validation of diffusion weighted T2- and T2*-relaxometry EPI sequences | |
| Yu Zidan1,2, Jelle Veraart1,2, Gregory Lemberskiy1,2, Ying-Chia Lin1,2, Tiejun E. Zhao3, Martijn Cloos1,2, Dan Iosifescu4,5, and Steven H. Baete1,2 | ||
1Center for Biomedical Imaging, Dept. of Radiology, NYU School of Medicine, New York, NY, United States, 2Center for Advanced Imaging Innovation and Research (CAI2R), NYU School of Medicine, New York, NY, United States, 3Siemens Medical Solutions, New York, NY, United States, 4Dept. of Psychiatry, NYU School of Medicine, New York, NY, United States, 5Clinical Research Division, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, United States |
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Combination of diffusion weighted MRI with orthogonal measures such as T2- or T2*-weighting has been proposed to overcome the fit degeneracy found in microstructure modeling of diffusion signals. However, the repetition of diffusion measurements at different TE leads to unacceptably long acquisition times, hindering clinical applicability of this approach. Here, we propose accelerated acquisitions using diffusion weighted multi-spin and multi-gradient echo trains which sample the signal at several TEs after a standard diffusion encoding spin echo. In the current configurations these sequences speed up the acquisitions by 2.6x or 3.6x respectively. We validate these approaches on a phantom. |
| 4499 | Sensitivity Gain from Multi-Echo Acquisitions in Ex-Vivo Diffusion Imaging: Numerical Simulations and Experimental Verification | |
| Cornelius Eichner1, Michael Paquette1, Toralf Mildner2, Torsten Schlumm2, Catherine Crockford3, Roman Wittig3, Carsten Jäger4, Markus Morawski4, Harald E. Möller2, Angela D. Friederici1, and Alfred Anwander1 | ||
1Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 2NMR Unit, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 3Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany, 4Paul Flechsig Institute of Brain Research, University Leipzig, Leipzig, Germany |
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Ex-vivo dMRI acquisitions achieve very high resolutions from increased SNR at the cost of prolonged scan times. Due to highly-segmented acquisition strategies, the ex-vivo dMRI signal is often not fully decayed when signal encoding progresses. Using numerical simulations and real-dMRI data from a wild chimpanzee, we show that this circumstance can be effectively employed using an optimized noise informed combination of multi-echo acquisitions from segmented EPI trains. The additional sampling comes at a small price and leads to increased SNR and a general reduction of signal bias. |
| 4500 | Characterization of orientation dispersion’s impact on diffusion kurtosis and NODDI using an axon-mimetic 3D printed phantom | |
| Tristan K. Kuehn1,2, Farah N. Mushtaha2, Omar El-Deeb3, Amanda Moehring3, Corey A. Baron1,2,4, and Ali R. Khan1,2,4,5 | ||
1School of Biomedical Engineering, Western University, London, ON, Canada, 2Centre for Functional and Metabolic Mapping, Robarts Research Institute, Western University, London, ON, Canada, 3Department of Biology, Western University, London, ON, Canada, 4Department of Medical Biophysics, Western University, London, ON, Canada, 5The Brain and Mind Institute, Western University, London, ON, Canada |
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Existing phantoms used to validate diffusion MRI models of white matter microstructure struggle to represent the complex fibre configurations found in vivo. Here we demonstrate a 3D printed phantom that realizes several complex fibre configurations inexpensively. We prepare a set of phantoms and use them to characterize the change in diffusion MRI model parameters with fibre curvature and crossing fibres. Most parameters computed by DTI, kurtosis, and NODDI had relationships with fibre crossing angle. These phantoms are a promising tool for evaluating the effect of orientation dispersion on diffusion MRI models of white matter. |
| 4501 | Geometric Distortion Evaluation of Integrated Slice Dependent Shimming (iShim) Using ACR MRI Phantom | |
| Cindy Xue1, Gladys Lo1, Raymond Lee1, Chi Wai Michael Liu1, Oi Lei Wong1, and Jing Yuan1 | ||
1Hong Kong Sanatorium and Hospital, Hong Kong, Hong Kong |
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Integrated slice dependent shimming (iShim) has been found to be able to reduce the magnetic field inhomogeneity and geometric distortion. In this study, we aim to evaluate, optimize and quantify the performance of the in-plane and through-plane geometric distortion in EPI-DWI using iShim. ACR large MRI phantom was scanned in two positions (a: along the bore, b: perpendicular to the bore) to evaluate the in-plane and through-plane geometric distortion. The phantom was separately scanned at 5 GRAPPA acceleration factors (iPAT 1-5) twice. In-plane geometric distortion along phase encoding direction with iShim may be minimized by increasing the acceleration factor. |
| 4502 | Double-Diffusion-Encoding MRI: phantom evaluation of concomitant gradient effects with single- and twice-refocused sequences | |
| Lisa Novello1, Stefano Tambalo1, Thorsten Feiweier2, and Jorge Jovicich1 | ||
1CIMeC, Center for Mind/Brain Sciences, University of Trento, Rovereto, Italy, 2Siemens Healthcare GmbH, Erlangen, Germany |
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In Double-Diffusion-Encoding sequences, concomitant gradients may introduce spatial bias in the measured MRI signal. It is important to characterize such biases since they can affect the accuracy of quantitative microstructural metrics in brain studies. In this work, we assess the signal deviations at different positions along the scanner z-axis in an isotropic phantom for both single- and twice-refocused spin-echo sequences. |
| 4503 | NODDInet: Diffusion parameter mapping using deep neural network trained by computer simulation data | |
| Juhyung Park1, Woojin Jung1, Eun-jung Choi1, and Jongho Lee1 | ||
1Seoul National University, Korea, Republic of Korea |
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A deep neural network, NODDInet, was developed to generate NODDI parameters (ICVF, ISOVF, OD, and FA) in 1 min. This network was trained using a computer simulation-generated training dataset only, and, therefore, is unbiased to experimental data and covers a wide range of the parameters. For the network input, the diffusion measurements of each shell were projected onto three 2D plains to reduce the input data size while preserving the geometric information of the diffusion measurements. The results demonstrate higher accuracy and faster processing time (x14) than a previous method (AMICO). |
| 4504 | Intravoxel Tissue Heterogeneity: One-to-one Correspondence between Non-Gaussian Diffusion MRI Parameters and Histologic Features | |
| Muge Karaman1,2, Lingdao Sha3, Tingqi Shi1, Dan Schonfeld2,3,4, Tibor Valyi-Nagy5, and X Joe Zhou1,2,6 | ||
1Center for Magnetic Resonance Research, University of Illinois at Chicago, Chicago, IL, United States, 2Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, United States, 3Department of Electrical and Computer Engineering, University of Illinois at Chicago, Chicago, IL, United States, 4Department of Computer Science, University of Illinois at Chicago, Chicago, IL, United States, 5Department of Pathology, University of Illinois at Chicago, Chicago, IL, United States, 6Departments of Radiology and Neurosurgery, University of Illinois at Chicago, Chicago, IL, United States |
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The parameters of the continuous-time random-walk (CTRW) model have been shown to be related to the underlying tissue heterogeneity. However, it has been challenging to establish a rigorous correlation between the CTRW parameters and the gold-standard histology. This is primarily because the histopathological evaluation of tissue heterogeneity is a labor-intensive task. We develop a machine-learning algorithm that quantifies the microscopic tissue heterogeneity revealed by histology as probability maps; and demonstrate a one-to-one correspondence between the CTRW parameters and tissue structural heterogeneity. Our results have provided evidence towards establishing a correlation between the CTRW parameter values and tissue heterogeneity. |
| 4505 | Validation of Diffusion Propagator Imaging measures in White Matter using Histology | |
| Madhura Baxi1,2, Lipeng Ning2, Suheyla Cetin-Karayumak2, Marek Kubicki2,3, and Yogesh Rathi2,3 | ||
1Graduate Program for Neuroscience, Boston University, Boston, MA, United States, 2Psychiatry Neuroimaging Lab, HMS, BWH, Boston, MA, United States, 3Department of Psychiatry, MGH, Boston, MA, United States |
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This study is the first attempt towards histological validation of three advanced diffusion MRI measures derived from the 3D diffusion propagator in white matter tissue: i) return-to-origin-probability (RTOP), ii) return-to-axis-probability (RTAP) and iii) mean squared displacement (MSD), using ex-vivo cat spinal cord tissue. We compared these dMRI measures voxel-wise with the underlying histological properties of the tissue. RTOP and RTAP were found to be significantly correlated with the following biological characteristics: i) Number of axons, ii) Myelin volume fraction and iii) Restricted water fraction, showing that the diffusion propagator imaging measures are sensitive to the underlying white matter microstructural properties. |
| 4506 | Fundamental Cell Biology Properties Underlying In Vivo DWI | |
| Brendan Moloney1, Eric M. Baker1, Xin Li1, Erin W. Gilbert2, and Charles S. Springer, Jr.1 | ||
1Advanced Imaging Research Center, Oregon Health & Science University, Portland, OR, United States, 2Surgery, Oregon Health & Science University, Portland, OR, United States |
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With cellular ensembles featuring stochastic [“Voronoi”] geometries, Monte Carlo random walk simulated DWI b-space decays exhibit sensitivity to cell biology parameters measuring membrane Na+,K+‑ATPase [NKA] activity, cell density, ρ, and voxel average cell volume, <V>. Furthermore, the simulations matching disparate in vivo tissue [murine xenograft colorectal cancer, human cerebral cortex, and human bladder] experimental b‑space decays have parameters [cellular water efflux rate constant <kio>, ρ, and <V>] in near absolute agreement with the most pertinent literature. Inspecting the common, empirical early decay measure, ADC, of these simulations provides insights into acute and chronic tissue property changes in vivo. |
| 4507 | Co-electrospun spinal cord phantom for diffusion MRI | |
| Fenglei Zhou1,2, Francesco Grussu1,3, Zhanxiong Li4, and Geoff Parker1,5 | ||
1Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom, 2School of Pharmacy, University College London, London, United Kingdom, 3Queen Square MS Centre, Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom, 4College of Textile and Clothing Engineering, Soochow University, Suzhou, China, 5Bioxydyn Limited, Manchester, United Kingdom |
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A spinal cord-mimicking fibre phantom was developed to evaluate its potential for validating dMRI. Microfibres were co-electrospun with two polymer solutions and characterized by SEM. The phantom comprised two material samples designed with 0o and 90o crossings. SEM revealed that fibres were uniaxially aligned and hollow, having similar sizes to spinal cord axons. Diffusion tensor analysis of a ZOOM dMRI acquisition demonstrated the difference in alignment of the two samples. Diffusion kurtosis analysis demonstrated differences in axial and radial diffusion restriction, with parameter values consistent with published spinal cord data. Relaxation time constants were similar in two samples. |
| 4508 | Validating pore size estimates in a biomimetic microfibre architecture with a stochastic distribution of pore-sizes and cross-sectional shapes | |
| Chih-Chin Heather Hsu1, Chun-Chung Huang2,3, Slawomir Kusmia4, Mark Drakesmith4, Feng-Lei Zhou5, Geoff Parker5, Ching-Po Lin2,3,6, and Derek Jones4 | ||
1Department of Biomedical Imaging and Radiological Science, National Yang Ming University, Taipei, Taiwan, 2Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China, 3Aging and Health Research Center, National Yang-Ming University, Taipei, Taiwan, 4Cardiff University Brain Research Imaging Center (CUBRIC), Cardiff University, Cardiff, United Kingdom, 5Centre for Medical Image Computing, University College London, London, United Kingdom, 6Institute of Neuroscience, National Yang-Ming University, Taipei, Taiwan |
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Previous studies showed that AxCaliber-like frameworks produce reliable orientation and inner diameter estimates in idealised phantoms (i.e., highly parallel hollow cylinders with uniform circular cross-section). We extend this work to ‘biomimetic’ phantoms, having stochastic pore-size distributions, non-circular cross sections and complex (i.e., crossing) fibre configurations. Using a Connectom scanner, and assuming a Poisson pore-size distribution, inner diameter and crossing angle estimates were in excellent agreement with electron-microscopy measurements in the same sample. To our knowledge, this is the first validation of pore-size estimates in complex geometries on a human scanner, lending support to the promise of mapping these parameters in-vivo. |
| 4509 | Comparison of Cylindrical and Spherical Geometric Models to Infer Cell Sizes in a Garlic Stem | |
| Melissa Sarah Lillian Anderson1, Henri Sanness Salmon1, Guneet Uppal1,2, Jarrad Perron3, Lisa Bako4, Gong Zhang5, Sheryl Lyn Herrera1,6, and Melanie Martin1 | ||
1Physics, University of Winnipeg, Winnipeg, MB, Canada, 2University of Manitoba, Winnipeg, MB, Canada, 3Physics, University of Manitoba, Winnipeg, MB, Canada, 4Cubresa, Inc., Winnipeg, MB, Canada, 5Brain Engineering Centre, Anhui University, China Physics, University of Winnipeg, Winnipeg, MB, Canada, 6Cubresa, Winnipeg, MB, Canada |
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Temporal diffusion spectroscopy (TDS) can be used to infer sizes of cells in samples. It relies on a geometric model to relate the MRI signal to the cell sizes. Garlic stem collenchyma tissue has long cells which might be modelled as cylinders. We compared a cylindrical and spherical geometric model in temporal diffusion spectroscopy to determine how important the geometrical model was for garlic stems. The inferred diameters of cells in the garlic stem (4μm-6μm) were not statistically different when using the two different geometric models. This is the first step toward understanding the importance of geometric models for TDS. |
| 4510 | Radiological Qualitative Assessment of IVIM Parameters for Total Variation Penalty Function Approach: A Pilot Study in Osteosarcoma | |
| Amit Mehndiratta1, Esha Badiya Kayal1, Kedar Khare 2, Sameer Bakhshi3, Raju Sharma4, and Devasenathipathy Kandasamy4 | ||
1Centre for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India, 2Department of Physics, Indian Institute of Technology Delhi, New Delhi, India, 3Dr. BRA Institute-Rotary Cancer Hospital, All India Institute of Medical Sciences, New Delhi, India, 4Department of RadioDiagnosis, All India Institute of Medical Sciences, New Delhi, India |
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Radiological based qualitative assessment of evaluated IVIM parametric maps using state-of-the-art IVIM analysis methods Bi-exponential (BE) model with adaptive Total Variation Penalty function (BE+TV) and BE with adaptive Huber Penalty function (BE+HPF) has been performed in comparison to the commonly used IVIM analysis methodologies like BE model, and segmented BE methods. BE+TV/BE+HPF preserve spatial homogeneity in the parametric images by updating them iteratively during data fitting. Experimental results showed all IVIM analysis methods showed BE+TV and BE+HPF produced comparative better noise suppression and diagnostic quality and interpretability for D* and f than other methods. |
| 4511 | Utility of DWI with quantitative ADC in diagnosing residual or recurrent HCCs after TACE: A systematic review and meta-analysis | |
| Hai-Feng Liu1 and Wei Xing1 | ||
1Department of Radiology, Third Affiliated Hospital of Soochow University, changzhou, China |
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This meta-analysis was to investigate the accuracy of DWI and ADC value in diagnosing residual or recurrent HCCs after TACE. This study suggested DW have high diagnostic efficacy, and ADC value can be used to differentiate residual or recurrent HCCs after TACE. |
| 4512 | Impact of processing pipelines on biological findings of large scale multicenter DTI studies | |
| Chung-Man Moon1, Amritha Nayak1,2, M. Okan Irfanoglu1, and Carlo Pierpaoli 1 | ||
1National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, United States, 2Henry M. Jackson Foundation for the Advancement of Military Medicine, Rockville, MD, United States |
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Different post-processing pipelines might influence the research or even clinical conclusions obtained from diffusion MRI. Our study investigated the impact of alternative pre-processing techniques and spatial normalization approaches on the outcome of a large multicenter study in schizophrenia that was originally analyzed using the ENIGMA pipeline. Our main finding is the discovery of profound effects of the spatial normalization approach used, on both biological conclusions and inter-site harmonization of the results. |
| 4513 | Rigorous Prospective Reduction of Inter-scanner Variance of Diffusion Imaging: Initial Experience | |
| Vincent Kyu Lee1, Benjamin Meyers1, William T Reynolds2, Rafael Ceschin1, Vincent Schmithorst1, Jeffrey Berman3, Thomas Chenevert4, Borjan Gagoski5, Peter LaViolette6, Deqiang Qiu7, Sudhir Pathak1, Ashok Panigrahy1, and Walter Schneider8 | ||
1Radiology, University of Pittsburgh, Pittsburgh, PA, United States, 2Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, United States, 3Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, United States, 4Radiology, University of Michigan, Ann Arbor, MI, United States, 5Radiology, Harvard Medical School, Boston, MA, United States, 6Radiology, Medical College of Wisconsin, Milwaukee, WI, United States, 7Radiology, Emory University, Atlanta, GA, United States, 8Psychology, University of Pittsburgh, Pittsburgh, PA, United States |
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Our study shows for the first time that synthetic phantoms that simulate fiber anatomical characteristics can provide in vitro corrections factors for reducing in-vivo inter-scanner variance specific to discrete segments of cortical association fiber tracts. The overall goal of our evolving rigorous harmonization approach is to reduce inter-scanner variance that can confound biological variance derived from multi-center discovery and neuroprotection clinical trials in the developing human brain. |
| 4514 | Evaluation of longitudinal changes in white matter structural integrity and grey matter volume in Parkinson’s disease | |
| Maurizio Bergamino1, Elizabeth Keeling1,2, Ryan R Walsh3, and Ashley M Stokes1 | ||
1Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ, United States, 2Neuroscience Department, Arizona State University, Phoenix, AZ, United States, 3The Muhammad Ali Parkinson Center, Barrow Neurological Institute, Phoenix, AZ, United States |
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In this study, we investigated longitudinal changes in white matter (WM) structural integrity and gray matter (GM) volume in Parkinson’s disease (PD). More specifically, free-water diffusion tensor imaging (FW-DTI), generalized q-sampling imaging (GQI), and voxel-based morphometry (VBM) were assessed in data obtained from the Parkinson Progression Markers Initiative (PPMI) database. We hypothesize that the use of advanced DTI metrics and VBM analysis will improve the sensitivity and specificity for the detection of WM alterations and GM volumetric changes in PD over time. |
| 4515 | Are DKI Measures Relatively More Sensitive In Identifying HIV Infection Related Pathologies Than DTI Measures? | |
| Sameer Vyas1, Teddy Salan2, Paramjeet Singh1, Sulaiman Sheriff2, Mahendra Kumar2, and Varan Govind2 | ||
1Postgraduate Institute of Medical Education and Research,, Chandigarh, India, 2University of Miami, Miami, FL, United States |
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DTI has shown evidence of alterations to the micro-structural integrity of the brain due to infection from HIV. However this finding is not consistent across all studies. In this work, we compare metrics obtained from DTI and diffusion kurtosis imaging (DKI) to determine if DKI can provide a more reliable and sensitive measurement of structural integrity. |
| 4516 | Application Study of DWI Radiomics Features with Transurethral Resection on Assessing the Muscular Infiltrating of Bladder Carcinoma | |
| guiqin Liu1, shuaishuai XU1, yongming Dai2, Guangyu WU1, and jianrong XU1 | ||
1Radiology, Renji Hospital，Shanghai Jiaotong University School of Medicine, Shanghai, China, 2United Imaing Healthcare, Shanghai, China |
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To investigate the value of radiomics features from diffusion-weighted imaging (DWI) in differentiating muscle-invasive bladder cancer (MIBC) from non-muscle-invasive bladder cancer (NMIBC). Combining DWI radiomics features with TUR could improve the sensitivity and accuracy in discriminating the presence of muscle invasion in bladder cancer for clinical practice. Multi-center, prospective studies are needed to confirm our results. |
| 4518 | Evaluation of simultaneous multislice acquisition with advanced processing vs. conventional sequence in free-breathing DWI for liver patients | |
| Mihaela Rata1, Katja De Paepe1, Matthew R Orton1, Erica Scurr1, Julie Hughes1, Alto Stemmer2, Marcel Dominik Nickel2, and Dow-Mu Koh1 | ||
1Royal Marsden Hospital and Institute of Cancer Research, London, United Kingdom, 2Siemens Healthcare, Erlangen, Germany |
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Diffusion Weighted Imaging (DWI) in combination with simultaneous multislice (SMS) acquisition has the potential to decrease acquisition time and improve image quality in abdominal MRI. In this study, we evaluated the image quality of free-breathing DWI acquired from 25 patients with liver metastases and compared SMS (with/without an advanced processing option) DWI with conventional bipolar echo planar DWI. We found that free-breathing liver DWI based on a SMS-accelerated protocol with advanced processing methods was faster and demonstrated better image quality when compared with a conventional bipolar DWI protocol. |
| 4519 | Fourier analysis of dynamic diffusion changes during cardiac cycle in idiopathic normal pressure hydrocephalus | |
| Yuya Yasuda1, Tosiaki Miyati1, Naoki Ohno1, Mitsuhito Mase2, Ryo Yagawa1, Rika Saito1, Masatomo Uehara1, Harumasa Kasai2, Yuta Shibamoto2, and Satoshi Kobayashi1 | ||
1Graduate School of Medical Sciences, Kanazawa University, Kanazawa, Japan, 2Nagoya City University Hospital, Nagoya, Japan |
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In this study, we evaluated the frequency characteristics of the apparent diffusion coefficient (ADC) wave form in the cardiac cycle of the brain in idiopathic normal pressure hydrocephalus (iNPH). iNPH is associated with higher ADC amplitude with a wide frequency range. The Fourier analysis of ADC change in the cardiac cycle in iNPH makes it possible to noninvasively obtain a more detailed information regarding the intracranial state in iNPH. |
| 4520 | Which frontal white matter pathways mediate executive decline in healthy ageing? | |
| Anoushka Leslie1, Ahmad Beyh1,2, Marco Catani3, Flavio Dell'Acqua3, Ceriesse Gunasinghe4, Henrietta Howells5, Richard Parker6, Andy Simmons1, Michel Thiebaut de Schotten7,8, Steve Williams1, and Mitul Mehta1 | ||
1Department of Neuroimaging, King's College London, London, United Kingdom, 2NatBrainLab, King's College London, London, United Kingdom, 3Natbrainlab, Department of Neuroimaging, King's College London, London, United Kingdom, 4Department of Psychological Medicine, King's College London, London, United Kingdom, 5Dipartimento di Biotecnologie Mediche e Medicina Traslazionale, Universita degli studi di Milano, Milano, Italy, 6IXICO plc, London, United Kingdom, 7Groupe d’Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives-UMR 5293, Universite de Bordeaux, Bordeaux, France, 8Brain Connectivity and Behaviour Laboratory, BCBlab, Sorbonne Universities, Paris, France |
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This study aimed to expand our understanding of how changes to frontal white matter pathways might influence executive decline in healthy ageing. We selected three cognitive components of executive function, attention, spatial working memory and planning and predicted that changes to microstructure of the cingulum, IFOF and SLFI -III would play a mediatory role in age related cognitive decline of 86 healthy adults. Contrary to our predictions, no mediation effects were found within the proposed tract - task groupings. Instead, during exploratory analysis, HMOA of the left uncinate demonstrated a small to medium indirect effect on age-related decline in planning performance. |
| 4521 | Increased non-Gaussian subdiffusion in white matter is associated with increased longitudinal blood pressure exposure in adults at midlife | |
| Carson Ingo1,2, Shawn Kurian3, James Higgins4, Lisanne Jenkins5, Donald Lloyd-Jones6, and Farzaneh Sorond1 | ||
1Department of Neurology, Northwestern University, Chicago, IL, United States, 2Department of Physical Therapy and Human Movement Sciences, Northwestern University, Chicago, IL, United States, 3Department of Neurology, Chicago, IL, United States, 4Department of Radiology, Northwestern University, Chicago, IL, United States, 5Department of Psychiatry and Behavioral Sciences, Northwestern University, Chicago, IL, United States, 6Department of Preventative Medicine, Northwestern University, Chicago, IL, United States |
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The increased presence of non-Gaussian subdiffusive dynamics, possibly reflecting the presence of increased neuronal and glial microstructural heterogeneity, is sensitive increased vascular risk exposure, which was not observed with traditional DTI metrics such as FA. |
| 4522 | Along-tract correlation analysis of diffusion metrics and white matter lesions in a 70-year old birth cohort | |
| Carole Hélène Sudre1,2, Chiara Maffei3, Josephine Barnes2, David Thomas2, David Cash2, Tom Parker2, Chris Lane2, Marcus Richards2, Hui Zhang2, Sebastien Ourselin1, Jonathan Schott2, Anastasia Yendiki3, and M. Jorge Cardoso1 | ||
1King's College London, London, United Kingdom, 2University College London, London, United Kingdom, 3Massachusetts General Hospital, Boston, MA, United States |
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In a population of 260 elderly individuals presenting white matter hyperintensities of presumed vascular origin, lesion profile along reconstructed tracts correlated strongly with diffusion metrics obtained from multishell acquisition (notably intracellular volume fraction, orientation dispersion index, axial radial and mean kurtosis). Results appeared stronger when the tractography was performed using data from the highest b-value. Furthermore, changes to the diffusion signal was observed consistently on the reconstructed tracts at the vicinity of the lesions potentially indicative of tissue vulnerability beyond the lesion border identified from FLAIR images. |
| 4523 | Microstructural and structural connectivity alterations in dexmedetomidine-induced loss of consciousness | |
| Timo Roine1,2, Oskari Kantonen3, Jaakko Langsjö3,4, Kimmo Kaskinoro5, Roosa Kallionpää2,5,6, Annalotta Scheinin3,5, Katja Valli2,5,6,7, Timo Laitio5, Antti Revonsuo2,6,7, and Harry Scheinin3,5,8 | ||
1Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland, 2Turku Brain and Mind Center, University of Turku, Turku, Finland, 3Turku PET Centre, University of Turku and the Hospital District of Southwest Finland, Turku, Finland, 4Department of Intensive Care, Tampere University Hospital, Tampere, Finland, 5Division of Perioperative Services, Intensive Care and Pain Medicine, Turku University Hospital, University of Turku, Turku, Finland, 6Department of Psychology and Speech-Language Pathology, University of Turku, Turku, Finland, 7Department of Cognitive Neuroscience and Philosophy, School of Bioscience, University of Skövde, Skövde, Sweden, 8Department of Pharmacology, Drug Development and Therapeutics, University of Turku, Turku, Finland |
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We used diffusion MRI to investigate brain microstructure and structural connectivity in 10 healthy subjects before and during dexmedetomidine-induced loss of consciousness. We found rapid local changes both in the microstructural properties and in the structural brain connectivity networks, most prominently in the left angular gyrus and its connections indicating possible involvement of the area in consciousness. Moreover, our results indicate that conventional high b-value diffusion MRI acquisitions, in addition to sequences specifically designed to capture functional changes, are sensitive to at least major brain state changes. |
| 4524 | Presurgical planning of MRgFUS for Essential Tremor (ET) with protocol for high quality DTI | |
| Amritha Nayak1,2, Angela Bissoli3, Okan M Irfanoglu2, Guiseppe Ricciardi3, Elisa Ciceri3, and Carlo Pierpaoli Pierpaoli2 | ||
1Henry Jackson Foundation for advancement in Military Medicine Inc, Rockville, MD, United States, 2National Insitutes of Health, Bethesda, MD, United States, 3Azienda Ospedaliera Universitaria Integrata, Verona, Italy |
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This study evaluates the role of a high quality DTI in presurgical planning of MRgFUS for initial target localization. |
| 4525 | Abnormal insula white matter tracts in smokers | |
| Chao Wang1, Shuyue Wang1, Peiyu Huang1, and Minming Zhang1 | ||
1Department of Radiology, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China |
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The insula, a cortical region that is thought to play a central role in this reward circuitry, has been implicated as an important role in the maintenance of nicotine addiction. However, it remains largely unclear about the alterations in white-matter tracts of insula circuits in nicotine addiction. Here, we further investigated the differences of insula white-matter tracts between smokers and nonsmokers. We found abnormal white matter tracts of insula subregions in smokers. These altered insula microstructural connectivity could interfere with the normal neural circuitry of reward processing, which might be the underlying neurobiology of nicotine addiction. |
| 4526 | Rich-Club Organizational Changes Over the Course of Motor Recovery after First-Time Acute Stroke | |
| Lu Wang1, Hing-Chiu Chang1, Peng Cao1, and Edward.S Hui1 | ||
1Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, China |
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In this study we acquired diffusion data and motor functions from stroke patients at within 1 week, 1, 3 and 6 months and found rich-club organization remerged one month after stroke and high order regions were found at 6 months when patients functionally recovered. Feeder connections showed middle cost and high capacity while rich-club connections showed high cost and middle capacity at 6 months after stroke. Together these results suggest that there could be a potential relation between reemergence of rich-club organization and brain motor recovery. |
| 4527 | Tractography based organization of the hyperdirect pathway to the subthalamic area in HCP subjects and parkinsonian patients | |
| Gizem Temiz1, Sophie Sébille1, Chantal François1, Eric Bardinet1, and Carine Karachi1,2 | ||
1CENIR, Institut du Cerveau et de la Moelle Epinière, Paris, France, 2AP-HP, Hôpital de la Pitié-Salpêtrière, Department of Neurosurgery, Paris, France, Paris, France |
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The aim of this study is to analyze differences in the hyperdirect cortical connectivity between the subthalamic nucleus and its medial region, and the anatomo-functional organization of these regions using tractography. These analyzes were performed in healthy subjects and parkinsonian patients. Our results show that a dominant motor cluster was located in the posterolateral STN, a limbic cluster located medially in the MSR, and an intermediate motor-limbic cluster located in between for both cohorts. In conclusion, tractography based sub-parcellisation of subthalamic regions could be helpful to refine individual targeting for functional neurosurgery. |
| 4528 | Differentiating Low- and High-Grade Adult glioma Using Multi-diffusion Models | |
| Junqi Xu1, He Wang1,2, Xueying Zhao1, Hui Zhang1, Xiaoyuan Feng3, and Ren Yan3 | ||
1Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China, 2Human Phenome Institute, Fudan University, Shanghai, China, 3Radiology, Huashan Hospital, Fudan University, Shanghai, China |
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To offer a potential multiparameter-mapping platform for clinical pathological diagnosis using multi-diffusion models including mono-exponentional model, IVIM, SEM, FROC, CTRW, SM and DKI. The U-test and ROC analysis show the superiority of FROC, CTRW and DKI models in diagnostic accuracy for grading brain tumors (at 0.770, 0.780 and 0.817 respectively). |
| 4529 | Evaluating advanced multi-shell diffusion MRI microstructural biomarkers of Alzheimer’s disease | |
| Julio Ernesto Villalon Reina1, Talia Miriam Nir2, Sophia Thomopoulos2, Lauren E Salminen3, Neda M Jahanshad2, Rutger Fick4, Matteo Frigo5, Rachid Deriche5, and Paul M Thompson2 | ||
1USC Imaging Genetics Center, University of Southern California, Los Angeles, CA, United States, 2USC Stevens Neuroimaging and Informatics Institute, University of Southern California, Marina del Rey, CA, United States, 3USC Imaging Genetics Center, University of Southern California, Marina del Rey, CA, United States, 4Therapanacea, Paris, France, 5Athena Project Team, Inria Sophia-Antipolis Méditerranée, Université Côte d'Azur, Nice, France |
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To identify microstructure-based biomarkers sensitive to cognitive impairment, we used ADNI-3 multi-shell dMRI data to estimate 18 measures from seven dMRI models and assessed their ability to predict mild cognitive impairment (MCI). For each measure, we used TV-L1 regularized logistic regression to find cohesive clusters of brain tissue that contribute to correct classification. We found that tensor-based (DTI) diffusivity and multi-compartment spherical mean technique (MC-SMT) measures showed the highest prediction accuracy, but differential anatomical distributions of classifying voxels. MC-SMT may offer greater sensitivity and specificity to MCI than DTI as MC-SMT resulted in the highest recall and fewest classifying voxels. |
| 4530 | Topological alterations in structural brain connectivity networks are associated with survival after out-of-hospital cardiac arrest | |
| Timo Roine1,2, Oskari Kantonen3, Ulrika Roine1, Sami Virtanen4, Jani Saunavaara4,5, Riitta Parkkola4, Ruut Laitio6, Olli Arola6, Marja Hynninen7, Juha Martola8, Heli M Silvennoinen8, Marjaana Tiainen9, Risto O. Roine10, Harry Scheinin6, and Timo Laitio6 | ||
1Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland, 2Turku Brain and Mind Center, University of Turku, Turku, Finland, 3Turku PET Centre, University of Turku and the Hospital District of Southwest Finland, Turku, Finland, 4Department of Radiology, Turku University Hospital, University of Turku, Turku, Finland, 5Department of Medical Physics, Turku University Hospital, University of Turku, Turku, Finland, 6Division of Perioperative Services, Intensive Care and Pain Medicine, Turku University Hospital, University of Turku, Turku, Finland, 7Division of Intensive Care Medicine, University of Helsinki and Helsinki University Hospital, Helsinki, Finland, 8Department of Radiology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland, 9Department of Neurology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland, 10Division of Clinical Neurosciences, Turku University Hospital, University of Turku, Turku, Finland |
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Mortality after out-of-hospital cardiac arrest is high, and there is a substantial need for new biomarkers to improve the identification of patients with poor outcome. Therefore, we investigated structural brain connectivity networks in patients after out-of-hospital cardiac arrest in order to detect differences related to survival. We found decreased global efficiency and strength from MRI scans acquired in a median of 53 hours (IQR 47-64) after OHCA to be related to mortality at 6 months after OHCA. In addition, several regions with decreased strength and local efficiency were found, most significantly in the pallidum, and superior frontal and supramarginal cortices. |
| 4531 | Diffusion MRI reveals macro- and microstructural changes in cosmonauts' brains after long-duration spaceflight | |
| Steven Jillings1, Angelique Van Ombergen2, Elena Tomilovskaya3, Alena Rumshiskaya4, Liudmila Litvinova4, Inna Nosikova3, Ekaterina Pechenkova5, Ilya Rukavishnikov3, Inessa Kozlovskaya3, Stefan Sunaert6, Paul M Parizel7, Valentin Sinitsyn8, Victor Petrovichev4, Steven Laureys9, Peter zu Eulenburg10, Jan Sijbers11, Floris Wuyts1, and Ben Jeurissen11 | ||
1Lab for Equilibrium Investigations and Aerospace, Dept. of Physics, University of Antwerp, Antwerp, Belgium, 2Translations Neuroscience, Dept. of Medicine, University of Antwerp, Antwerp, Belgium, 3Institute of Biomedical Problems, Russian Academy of Sciences, Moscow, Russian Federation, 4Dept. of Radiology, Federal Center of Treatment and Rehabilitation, Moscow, Russian Federation, 5Laboratory for Cognitive Research, National Research University Higher School of Economics, Moscow, Russian Federation, 6Dept. of Imaging and Pathology, KU Leuven, Leuven, Belgium, 7Dept. of Radiology, Royal Perth Hospital and University of Western Australia, Perth, Australia, 8Faculty of Fundamental Medicine, Lomonosov Moscow State University, Moscow, Russian Federation, 9Coma Science Group, Dept. of Neurology, University (Hospital) of Liège, Liège, Belgium, 10German Center for Vertigo and Balance Disorders, Dept. of Neurology, Ludwig-Maximilians-University Munich, Munich, Germany, 11imec - Vision Lab, Dept. of Physics, University of Antwerp, Antwerp, Belgium |
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There is currently limited information on the effects of spaceflight on the human brain. Therefore, we investigated longitudinal changes in gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) density and mass using diffusion MRI data acquired pre-flight, post-flight and at follow-up. Our results show redistributed CSF and concomitant GM morphological changes post-flight, which reverse at follow-up. At the same time, our results show no evidence of neurodegeneration. Moreover, GM and WM mass increased in sensorimotor brain regions post-flight, which largely persisted at follow-up. These results indicate, for the first time, sensorimotor neuroplasticity after spaceflight. |
| 4532 | High-resolution Distortion-free DWI of Pituitary Adenomas and Rathke Cleft Cysts Using Point-spread-function Encoded EPI | |
| Jieying Zhang1, Chunjie Guo2, Xinrui Liu3, Yishi Wang1,4, Huimao Zhang2, and Hua Guo1 | ||
1Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China, 2Department of Radiology, the First Hospital of Jilin University, Changchun, China, 3Department of Neurosurgery, the First Hospital of Jilin University, Changchun, China, 4Philips Healthcare, Beijing, China |
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Differentiation between pituitary adenomas (PAs) and Rathke cleft cysts (RCCs) is important for treatment planning. Diffusion weighted imaging (DWI) has been reported for the differentiation. However, traditional single-shot echo planar imaging (EPI) DWI has limited resolution and suffers from image distortion near the skull base. High-resolution distortion-free DWI should be more suitable. We apply a recently developed fast point-spread-function encoded EPI on pituitary imaging. It generates high-resolution distortion-free DWI, in which the signals of the microadenoma and the RCCs are hyperintense and hypointense, respectively. This study shows the potential of this technique to distinguish between PAs and RCCs. |
| 4533 | Can mapping cortical diffusivity provide unique microstructural insight into aging? | |
| Graham A. D. Archibald1, Jordan A. Chad1,2, David H. Salat3,4, and J. Jean Chen1,2 | ||
1Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada, 2Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada, 3MGH/HST Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States, 4Neuroimaging Research for Veterans Center, VA Boston Healthcare System, Boston, MA, United States |
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The aging process in the cerebral cortex is typically measured in-vivo via MRI-based cortical thickness. Here we show that mean diffusivity (MD), a parameter derived from diffusion MRI, serves as a more sensitive measure of aging than thickness across the cortex. MD shows distinct age-related differences than thickness, suggesting that MD can provide insight into microscopic degeneration that cannot be detected with macroscopic structural MRI measures. While diffusion MRI microstructural analyses are typically limited to the white matter, this work suggests that additionally assessing age-related differences in cortical gray matter diffusivity can offer potentially valuable information on early cortical degeneration. |
| 4534 | Hemodialysis can contribute to acute changes in cerebral volume and white matter structure | |
| Madeleine T Dacey1,2,3, Stefan E Poirier1,3, Janice Gomes2,4, Udunna C Anazodo1,3, and Christopher W McIntyre1,2 | ||
1Medical Biophysics, Western University, London, ON, Canada, 2Kidney Clinical Research Unit, Lawson Health Sciences Center, London, ON, Canada, 3Imaging, Lawson Health Research Insitute, London, ON, Canada, 4Pathology and Laboratory Medicine, Western University, London, ON, Canada |
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Cognitive impairment and white matter degeneration are common in hemodialysis patients. Hemodialysis can severely impede blood flow and create osmotic imbalances in the brain. This may cause brain injury by a mechanism similar to that of stroke. To investigate the acute effects of hemodialysis on the brain, we used a novel system to perform diffusion and T1 weighted MRI scans during hemodialysis. Several tracts exhibit diffusion tensor imaging markers for cytotoxic and ionic edema. Increased white and grey matter volume during hemodialysis further support the presence of ionic edema. Ionic and cytotoxic edema are evidence of acute brain injury. |
| 4535 | Clinical monitoring of axonal loss in multiple sclerosis using advanced diffusion MRI | |
| Scott Kolbe1, Meaghan Clough1, Frederique Boonstra1, Myrte Strik2, Anneke van der Walt1, Helmut Butzkueven1, Owen White1, Joanne Fielding1, and Meng Law1 | ||
1Monash University, Prahran, Australia, 2University of Melbourne, Parkville, Australia |
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Brain atrophy is currently the accepted method for measuring neurodegeneration in multiple sclerosis (MS) but is insensitive over short times and ignores changes in cellular density. Recent advances in diffusion weighted imaging provide markers of axonal fibre density and atrophy. This study aimed to study the longitudinal sensitivity of these markers in comparison to brain atrophy based on data acquired in a standard clinical MS study. Annualised within-patient change in fibre density was around seven times more sensitive than brain volume change. This supports the development of fibre density based methods for clinical monitoring of axonal loss in MS. |
| 4536 | White matter fiber density and cross-section alterations in neuropathic pain after spinal cord injury | |
| Shana Black1,2, Andrew Janson1,2, and Christopher R Butson1,2,3 | ||
1Biomedical Engineering, University of Utah, Salt Lake City, UT, United States, 2Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, United States, 3Neurology, Neurosurgery, and Psychiatry, University of Utah, Salt Lake City, UT, United States |
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Fiber-specific white matter changes were compared using fixel-based analysis between spinal cord injured subjects with chronic neuropathic pain (n=17) and spinal cord injured subjects without any pain symptoms (n=15). Fiber density, fiber cross-section (FC), and a combined measurement of fiber density and cross section (FDC) were calculated and compared between groups using multi-shell, 3-tissue constrained spherical deconvolution and connectivity-based fixel enhancement. Statistically significant increases (FWE-corrected p<0.1) in FC and FDC were identified in a posterior-inferior commissural white matter pathway, corresponding to the splenium and major forceps of the corpus callosum and regions of the retrosplenial complex. |
| 4537 | Brain white matter abnormalities and correlation with severity in amyotrophic lateral sclerosis: An atlas-based diffusion tensor imaging study | |
| XiaoQiang Du1, YunJing Xue1, HuaJun Chen1, and ZhongShuai Zhang2 | ||
1Fujian Medical University Union Hospital, Fuzhou, China, 2SIEMENS Healthcare, Shanghai, China |
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This study used atlas-based region of interest analysis to assess WM microstructure in ALS by combining intra-voxel metrics, which included FA and MD, and an inter-voxel metric, i.e., LDH. We found WM abnormalities extending from the motor to the extra-motor regions in ALS and observed a correlation between distinct diffusion metrics and various clinical variables, supporting DTI metrics may be utilized as the diagnostic biomarker of ALS. Meanwhile, the extent of WM abnormalities in several tracts (e.g. ATR and LIFOF) were better revealed by LDH measurement, suggesting the supplementary role in reflecting ALS-related pathological process. |
| 4538 | Diffusion Tensor Imaging Detects Cross-Sectional and Longitudinal Brain Changes in Type 2 Diabetes Mellitus | |
| Bhaswati Roy1, Sarah E Choi2, Milena Lai3, Luke Ehlert3, Rashmi Mullur4, Matthew J. Freeby4, and Rajesh Kumar3,5,6,7 | ||
1University of California at Los Angeles, LOS ANGELES, CA, United States, 2UCLA School of Nursing, University of California at Los Angeles, Los Angeles, CA, United States, 3Anesthesiology, University of California at Los Angeles, Los Angeles, CA, United States, 4Medicine, University of California at Los Angeles, Los Angeles, CA, United States, 5Radiology, University of California at Los Angeles, Los Angeles, CA, United States, 6Bioengineering, University of California at Los Angeles, Los Angeles, CA, United States, 7Brain Research Institute, University of California at Los Angeles, Los Angeles, CA, United States |
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Patients with Type 2 diabetes mellitus (T2DM) show brain tissue changes in mood and cognitive control sites, functions that are deficient in the condition. However, the nature and extent of brain injury in T2DM, and their progression with time along with functional deficits are unclear. Using diffusion tensor imaging based MD procedures, we showed wide-spread chronic tissue changes in T2DM subjects and their continued progression after 6 months follow-up in areas involve in mood and cognitive regulatory functions. These findings may have resulted from underlying metabolic dysfunction associated with the condition. |
| 4539 | Preliminary Assessment of Intravoxel Incoherent Motion Diffusion-Weighted MRI (IVIM-DWI) Metrics in Alzheimer’s Disease | |
| Maurizio Bergamino1, Ashley Nespodzany1, Leslie C Baxter1,2, Anna Burke3, Richard Caselli2, Marwan N Sabbagh4, Ryan R Walsh5, and Ashley M Stokes1 | ||
1Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ, United States, 2Mayo Clinic Arizona, Phoenix, AZ, United States, 3Department of Neuropsychiatry, Barrow Neurological Institute, Phoenix, AZ, United States, 4Lou Ruvo Center for Brain Health, Cleveland Clinic, Las Vegas, NV, United States, 5The Muhammad Ali Parkinson Center, Barrow Neurological Institute, Phoenix, AZ, United States |
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The objective of this study was to assess complementary metrics from voxel-based morphometry (VBM) and intravoxel incoherent motion diffusion-weighted images (IVIM-DWI) MRI methods in aging populations. Using voxel-based analysis, grey matter (GM) and white matter (WM) differences were analyzed across Alzheimer’s disease (AD), mild cognitive impairment (MCI), and cognitively normal (HC) individuals. IVIM-DWI demonstrated early significant differences between MCI and HC groups, while VBM did not. In addition, voxel-based correlations between neuroimaging metrics and cognitive assessments were assessed in the cognitively impaired groups (AD and MCI). |
| 4540 | A comparison of RESOLVE DWI with delayed gadolinium-enhanced T1-weighted MRI in detecting cholesteatoma based on 531 patients’ data | |
| Yaru Sheng1, Yan Sha1, Rujian Hong1, Zhongshuai Zhang2, and Wenhu Huang1 | ||
1Radiology, EENT Hospital of Fudan University, Shanghai, China, 2Siemens Healthcare, Shanghai, China |
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This study aimed to compare the performance of readout-segmented echo-planar imaging (RESOLVE) DWI and delayed gadolinium-enhanced T1-weighted MRI to diagnose cholesteatoma on 531 patients. The results showed that RESOLVE DWI can be an excellent tool for the detection of primary cholesteatoma. |
| 4541 | A novel diffusion registration method with the NTU-DSI-122 template to transform free water signal fraction maps to stereotaxic space. | |
| Benjamin T Newman1,2, Ana Untaroiu1, and T. Jason Druzgal1,2 | ||
1Department of Radiology & Medical Imaging, Division of Neuroradiology, University of Virginia Health System, University of Virginia, Charlottesville, VA, United States, 2Brain Institute, University of Virginia, Charlottesville, VA, United States |
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We propose the use of the NTU-DSI-122 template as a flexible, diffusion specific, means of registering subject images to stereotaxic MNI-space for further analysis. This allows for registration to be performed based on matching white matter fiber orientation distributions, which create within tissue contrasts, unlike voxel intensity metrics. This advantage is demonstrated by observing the increased consistency of registration versus a leading intensity-based algorithm. The range of b-values present in the NTU-DSI-122 allows for tailoring to selectively register at b-values matching those acquired in an experimental cohort, providing flexibility for both single- and multi-shell acquisitions. |
| 4542 | Diffusion-Ordered NMR Spectroscopy Reconstruction Based on Low-rank and Sparse Inverse Laplace Transform | |
| Enping Lin1, Yu Yang1, Yuqing Huang1, and Zhong Chen1 | ||
1Department of Electronic Science, Xiamen University, Xiamen, China |
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DOSY (Diffusion-ordered NMR spectroscopy) presents an essential tool for the analysis of compound mixtures. However, existing DOSY reconstruction methods is limited by its relatively low resolution. Here, based on constraints on low rank and sparsity of DOSY data, we propose a reconstruction method to achieve high-resolution DOSY spectrum for measurements on complex mixtures, even when component signals are congested and mixed together along the spectral dimension. Experiment results indicate that our method is robust and possesses high-resolution reconstruction performance. |
| 4543 | Diffusion MRI revealed mild optic nerve fiber degeneration during Chimpanzee aging | |
| Chun-Xia Li1, Yumei Yan1, Longchuan Li2, Todd Preuss3, James G Herndon3, Xiaoping Hu4, and Xiaodong Zhang1,3 | ||
1Yerkes Imaging Center, Yerkes National Primate Research Center, Emory University, Atlanta, GA, United States, 2Department of Pediatric, Emory University School of Medicine, Atlanta, GA, United States, 3Division of Neuroscience and Neurological diseases, Emory University, Atlanta, GA, United States, 4Department of bioengineering, University of California, Riverside, Riverside, CA, United States |
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Aging effects on the optic nerve (ON) bundles of chimpanzees were investigated systematically with diffusion tensor imaging (DTI). Mean diffusivity (MD), axial diffusivity (AD or λll), radial diffusivity (RD or λτ) and fractional anisotropy (FA) showed mild and proportional changes from youth to elder adulthood, and significant increase of MD and RD were seen in elder chimpanzees. However, the changes are much milder than previous studies in the ON of monkey and human brain white matter. The unique evolution pattern in chimpanzee white mater aging may grant further investigations to unveil the neural substrate mechanism of the human brain aging. |
| 4544 | Diffusion Tractography at 0.5T: Comparison to 1.5T | |
| Jeff A Stainsby1, Chad T Harris1, Andrew T Curtis1, Philip J Beatty1, and Curtis N Wiens1 | ||
1Synaptive Medical, Toronto, ON, Canada |
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The feasibility of generating diffusion tractography from data obtained on a head-only 0.5T system is demonstrated and results are compared qualitatively to tractography generated from clinical 1.5T data. DTI data from 0.5T compares favorably in quantitative (FA, ADC) measures to literature values, and qualitative (segmented white matter tracts) measures to 1.5T. |
| 4545 | Diffusion-weighted imaging at ultra-low field MR for acute stroke detection: what can we see? | |
| Tiago Timoteo Fernandes1, Marc Golub1, Andreia Freitas1, Sairam Geethanath2,3, and Rita Gouveia Nunes1 | ||
1ISR, IST - University of Lisbon, Lisbon, Portugal, 2Medical Imaging Research Centre, Dayananda Sagar Institutions, Bangalore, India, 3Magnetic Resonance Research Center, Columbia University, NY, DC, United States |
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The primary goal of MR in acute stroke imaging is to determine the ischemic tissue at risk. Since a narrow time window is available for treatment, an accessible point-of-care system is desirable. Ultra-low field MR (ULF) shows promise but suffers from low signal-to-noise ratios (SNR). We performed a theoretical study of the SNR and contrast-to-noise (CNR) ratios for a range of B0 fields, with corresponding tissue relaxation times, considering different gradient performances. Illustrative simulated DWI brain images are provided. Results suggest that despite the challenges, ULF is promising for imaging acute stroke lesions. |
| 4546 | Ultra-high b-value Diffusion MRI for Evaluation of Single Amyloid Precursor Protein Knock-in Mouse Model of Alzheimer’s Disease | |
| Jin Gao1,2, Zachery Morrissey3, Alex Leow3, Orly Lazarov4, Danilo Erricolo1, Richard Magin5, and Weiguo Li2,5 | ||
1Electrical 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 Psychiatry, University of Illinois at Chicago, Chicago, IL, United States, 4Department of Anatomy and Cell Biology, University of Illinois at Chicago, Chicago, IL, United States, 5Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, United States |
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Alzheimer’s disease (AD) has a tremendous impact in terms of social and economic cost. White matter damage in the progression of AD and the associated cognitive symptoms and pathophysiology are of crucial interest. Diffusion MRI offers unique insights into the pathophysiology of AD in vivo. This feasibility study aims to assess and visualize the white matter changes using an ultrahigh b-value diffusion MRI. |
| 4547 | Cerebrospinal fluid pulsation does not affect on DWI-based thermometry: healthy volunteer study | |
| Koji Sakai1, Jun Tazoe1, Kentaro Akazawa1, Hiroyasu Ikeno2, Toshiaki Nakagawa2, and Kei Yamada1 | ||
1Kyoto Prefectural University of Medicine, Kyoto, Japan, 2Kyoto Prefectural University of Medicine Hospital, Kyoto, Japan |
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Diffusion-weighted imaging (DWI) based thermometry has the potential to be a non-invasive method of temperature measurement for the deep inside of human brain. Nevertheless, the DWI at lateral ventricle in brain might be influenced by the pulsation flow of cerebrospinal fluid (CSF), which is motivated by heartbeat. The purpose of this study was to investigate the influence of pulsation flow on brain DWI thermometry for healthy subjects. Comparisons were performed between magnetic resonance spectroscopy and DWI based thermometry (ΔT) at three CSF speed selections. There was no significant difference on ΔT among the CSF speed and volume on healthy subjects. |
| 4548 | T2w-FLAIR generation through deep-learning using distortion-free PSF-EPI DWI | |
| Zhangxuan Hu1, Zhe Zhang2, Yishi Wang3, Yajing Zhang4, and Hua Guo1 | ||
1Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China, 2China National Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China, 3Philips Healthcare, Beijing, China, 4MR Clinical Science, Philips Healthcare (Suzhou), Suzhou, China |
||
MRI examinations usually contain multi-contrast images, which may share redundant information. For example, T2w-FLAIR contrast relies on the property of T2 relaxation and water component of the tissue, which also present in T2- and diffusion-weighted images. T2w-FLAIR acquisition is usually lengthy due to the long inversion time. In this study, point-spread-function (PSF) encoded EPI (PSF-EPI) DWI and T2-weighted images were used to generate T2w-FLAIR images by taking the advantages of high-resolution and distortion-free of PSF-EPI. This method has the potential to improve the acquisition efficiency of MRI. |
| 4549 | AMURA with standard single-shell acquisition can detect changes beyond the Diffusion Tensor: a migraine clinical study | |
| Álvaro Planchuelo-Gómez1, Rodrigo de Luis-García1, Antonio Tristán-Vega1, David García-Azorín2, Ángel Luis Guerrero2, and Santiago Aja-Fernández1 | ||
1Imaging Processing Laboratory, Universidad de Valladolid, Valladolid, Spain, 2Headache Unit, Hospital Clínico Universitario de Valladolid, Valladolid, Spain |
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AMURA (Apparent Measures Using Reduced Acquisitions) is an alternative formulation to drastically reduce the number of samples needed for the estimation of diffusion properties related to the Ensemble Average diffusion Propagator (EAP). Although these measures were initially intended for medium-to-high b-values, in this work we evaluate their performance in DTI-like acquisitions. Fifty healthy controls, 54 episodic migraine (EM) and 56 chronic migraine (CM) patients were compared, using a single-shell diffusion scheme at b=1000 s/mm2. We compare AMURA measures (return-to-origin, return-to-axis and return-to-plane probabilities) to traditional DTI measures. Differences between EM and controls were only detectable using the return-to-origin probability. |
| 4550 | Fewer number of gradient directions in diffusion MRI can be counterbalanced with higher sample size: a migraine clinical study | |
| Álvaro Planchuelo-Gómez1, Santiago Aja-Fernández1, David García-Azorín2, Ángel Luis Guerrero2, and Rodrigo de Luis-García1 | ||
1Imaging Processing Laboratory, Universidad de Valladolid, Valladolid, Spain, 2Headache Unit, Hospital Clínico Universitario de Valladolid, Valladolid, Spain |
||
The effect of changes in the acquisition parameters on Diffusion Tensor Imaging (DTI) has been studied, but for very specific situations. A whole-brain comparison of 54 episodic migraine (EM) and 56 chronic migraine (CM) patients, using diffusion schemes of 61, 40 and 21 gradient orientations, was performed. Statistical comparisons were repeated reducing the sample size until no significant differences were found. Higher number of regions with significant lower axial diffusivity in CM compared to EM were found using 61 gradient directions. With a larger sample size, results with 40 and 21 directions were equivalent to results acquired with 61 directions. |
| 4551 | A DTI Comparative study – Is demyelination in AD resembling primary demyelinating disease (MS) or secondary demyelinating disease (NPSLE)? | |
| Huiqin Zhang1, Hui Zhang1, Franki Kai-Hei Tse 2, Edward Sai-Kam Hui1, Peng Cao1, Kannie Wai Yan Chan3, Queenie Chan4, Karl HERRUP5, and Henry Ka Fung Mak1 | ||
1Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, Hong Kong, 2Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, Hong Kong, 3Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, Hong Kong, 4Philips Healthcare, Hong Kong, Hong Kong, 5Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA, United States |
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Demyelination is a known pathology in AD, but it is unclear whether such myelin loss resembles primary or secondary demyelinating disease. Here, we retrospectively analysed the DTI data using voxel-wise TBSS analysis and made pair-wise comparisons between cohorts of AD, Relapsing-remitting MS(RRMS), NPSLE and normal controls (NC). In diffusion metrics analysis, widespread microstructural patterns were similarly found between AD and MS in terms of diffusion metrics, but not between AD and NPSLE. Our results indicate that the microstructural WM changes in AD may share similar pathological mechanisms in demyelinating disease of RRMS. |
| 4552 | A longitudinal study on heterogeneity of diffusional parameters of spontaneously-hypertensive rats. | |
| Jung-Sen Hsiao1, Hung-Yu Fu1, Pei-Lun Yu1, Sheng-Min Huang1, Kung-Chu Ho2, and Fu-Nien Wang1 | ||
1Biomedical Engineering and Envionmental Sciences, National Tsing-Hua University, Hsinchu City, Taiwan, 2Chang-Gung Memorial Hospital, Taoyuan City, Taiwan |
||
Diffusion MRI has been regarded as an assessment in characterizing brain tissue integrity. However, the information of tissue heterogeneity is often overlooked. To investigate the feasibility of diffusional heterogeneity in gray matter through DKI derived diffusivities, six spontaneously-hypertensive rats (SHR) in different ages were scanned on a 7T small animal MR scanner. The differences of heterogeneity of diffusivities and kurtosis between different ages were revealed, which may imply its possibility for tissue characterization. Therefore, the diffusional heterogeneity could be suggested to be a potential image-based biomarker for evaluating tissue integrity. |
| 4553 | In vivo Diffusion Tensor Magnetic Resonance Imaging of Chronic Cocaine Administered Mouse Brain | |
| Ethan A Cook1, Shannon E Callen2, Shilpa Buch2, and Balasrinivasa R Sajja3 | ||
1College of Medicine, University of Nebraska Medical Center, Omaha, NE, United States, 2Pharmacology and Experimental Neuroscience, University of Nebraska Medical Center, Omaha, NE, United States, 3Radiology, University of Nebraska Medical Center, Omaha, NE, United States |
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In vivo imaging-based biomarkers that can accurately detect the brain structural and functional changes due to chronic drug abuse play a significant role to understand and assess brain damage due to cocaine abuse and to determine the efficacy of the treatment. To this end, we have demonstrated that diffusion tensor MRI could detect brain structural changes, particularly demyelination in white matter structures, in chronic cocaine administered mice. |
| 4554 | WITHDRAWN |
| 4555 | Brain microstructural alterations of left precuneus mediate the association between KIBRA rs17070145 and working memory in healthy adults. | |
| Junxia Wang1, Sichu Wu2, Jilei Zhang3, and Bing Zhang2 | ||
1Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, China, 2Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China, 3Clinical Science, Philips Healthcare, Shanghai, Shanghai, China |
||
We used voxel-based independent sample t-test to investigate differences of DKI and resting-state fMRI parametric maps between KIBRA rs17070145 polymorphism in 163 young adults. Mediation analysis was used to explore the association between the KIBRA polymorphism, brain and working memory. We observed that KIBRA C-allele carriers had increased AD, RD, MD and decreased FA, MK, RK, ALFF compared with KIBRA TT homozygotes. The MK, RK of the left precuneus mediated the association between the KIBRA polymorphism and the working memory performance. These findings may be useful in understanding the neural mechanisms of KIBRA and provide a biological pathway of gene-brain-behavior. |
| 4556 | A Longitudinal Study on Assessing the Recovery of Spinal Cord on Incomplete Traumatic Spinal Cord Injury using Diffusion Tensor Imaging | |
| Bing Yao1,2, Hannah Ovadia1, Gail Forrest3, and Steven Kirshblum2,4 | ||
1Rocco Ortenzio Neuroimaging Center, Kessler Foundation, West Orange, NJ, United States, 2Department of Physical Medicine and Rehabilitation, Rutgers University, Newark, NJ, United States, 3Center for Mobility and Rehabilitation Engineering Research, Kessler Foundation, West Orange, NJ, United States, 4Kessler Institute for Rehabilitation, West Orange, NJ, United States |
||
Physicians rely on self-reports to monitor and evaluate the functional outcome in patients with spinal cord injury during their rehabilitation. These clinical and outcome measurements can be subjective and sometimes impractical if patients have cognitive difficulty. Traditional clinical MRI scans can provide doctors more objective information but they are not sensitive to detect the progression or repair during patient’s recovery. In this study, we investigated the sensitivity of DTI technique in detecting SCI injury and its progression or recovery over the course of rehabilitation in the individuals with SCI. |
| 4557 | Quantitative assessment of thyroid and parathyroid lesions by using ZOOMit-based IVIM, DKI and DWI | |
| Bing Liu1,2, Xiangtao Lin1,2, Peng Zhao1, Xianshun Yuan1,2, Mengxiao Liu3, Xiang Feng4, Lei Xue5, Mimi Tian2, Shuai Zhang1,2, Dejuan Shan1,2, and Xiaoli Li1,2 | ||
1Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China, 2Shandong University, Jinan, China, 3MR Scientific Marketing, Diagnostic Imaging, Siemens Healthcare Ltd, Shanghai, China, 4MR Scientific Marketing, Diagnostic Imaging, Siemens Healthcare Ltd, Beijing, China, 5MR Application, Siemens Healthcare Ltd, Jinan, China |
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The aim of this study was to evaluate the diagnostic performance of three advanced diffusion techniques (IVIM, DKI and DWI) which based on ZOOMit in demonstrating lesions in thyroid and parathyroid area. Results showed that D* in IVIM, MK in DKI and ADC in DWI were superior than other diffusion parameters (D, F in IVIM, MD in DKI) in accurately locating lesions as well as differentiating between lesions and normal thyroid parenchyma. |
| 4558 | Quantitative evaluation of IVIM-DWI combined with simplified DKI for subtype diagnosis and grading prediction in retroperitoneal liposarcoma | |
| Zhang Jiulong1, Shi Nannan1, Zhang Yijun1, Ye Wen1, Zhang yong2, Shan fei1, and Shi Yuxin1 | ||
1radiology department, Shanghai public health clinical center, shanghai, China, 2General surgery, Shanghai public health clinical center, shanghai, China |
||
This study used ivim-dwi combined with sDKI models to quantitatively evaluate the differential diagnosis and histological grading prediction of retroperitoneal liposarcoma subtypes. Our results indicated that IVIM-DWI combined with sDKI models could accurately differentiate partial subtypes of RPLS, which was helpful for clinical selection of the optimal treatment strategy. |
| 4559 | Is ADC Measurement of Parotid Gland Tumor Sufficient using the Largest Slice rather than Whole Tumor | |
| Shao-Chieh Lin1, Jui-Heng Lin1, Chun-Jung Juan2,3,4, Kai-Min Chien5, Teng-Yi Huang6, Yi-Jui Liu7, Chang Hsien Liu 5, Ya-Hui Li5, Szu Hsien Chou 5, and Chi-Feng Hsieh5 | ||
1Master 's Program of Biomedical Informatics and Biomedical Engineering, Feng Chia University, Taichung, Taiwan, 2Department of Medical Imaging, China Medical University Hsinchu Hospital, Hsinchu, Taiwan, 3Department of Radiology, School of Medicine, College of Medicine, China Medical University, Taichung, Taiwan, 4Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan, 5Department of Medical Imaging, Chinese Medical University Hsinchu Hospital, Hsinchu, Taiwan, 6Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, 7Department of Automatic Control Engineering, Feng Chia University, Taichung, Taiwan |
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The study is to quantitatively compare the diagnostic ability of ADC in distinguishing three types of parotid tumor between the ADC measurement on slice with the largest tumor and whole tumor. This retrospective study enrolled 13 patient for each PMAs, WTs and MTs. All participants underwent 1.5-T fat-saturated EP-DWI. Our results show that ADC and AUC on largest slice and whole tumor were similar in three tumors. ADC of the slice with the largest tumor, which tumor size over 1/3 whole tumor volume, could instead the ADC of whole tumor to diagnosis the PMA, WT and MT in parotid gland. |
| 4560 | Intravoxel incoherent motion and diffusion kurtosis imaging in the assessment of pathological grades of clear cell renal cell carcinoma | |
| Qing Xu1, Weiqiang Dou2, and Jing Ye1 | ||
1Department of Radiology, Clinical Medical School of Yangzhou University, Northern Jiangsu People’s Hospital, Yangzhou, 457, China, 2GE Healthcare, MR Research China, Beijing, China |
||
In this study, we aimed to investigate whether intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) techniques can be used to evaluate the pathological grade of clear cell renal cell carcinoma (ccRCC) patients preoperatively. As a result, the IVIM-related parameters (ADC, apparent diffusion coefficient; D, true diffusivity) and DKI-related parameters (MD, mean diffusivity; MK, mean kurtosis) have shown significant differences between low- and high-grade ccRCC(0.58±0.11 vs 0.48±0.08, 1.39±1.18 vs 0.98±0.21, 2.12±0.35 vs 1.59±0.32, 0.53±0.13 vs 1.59±0.32; p<0.05). Therefore, IVIM and DKI techniques can be used effective tools to differentiate low- and high-grade ccRCC. |
| 4561 | Investigating multi-compartment diffusion MRI models in the cervical spinal cord of multiple sclerosis patients | |
| Kurt G Schilling1, Kristin P O'Grady1,2, Samantha By3, Haley Feiler1, Francesca Bagnato4, Bennett A Landman1,5,6,7, and Seth A Smith1,5,8 | ||
1Vanderbilt University Institute of Imaging Science, Nashville, TN, United States, 2Radiology and Radiological Sciences, Vanderbilt University Medial Center, Nashvillet, TN, United States, 3Hyperfine Research Inc, Guilford, CT, United States, 4Neurology, Vanderbilt University Medical Center, Nashville, TN, United States, 5Biomedical Engineering, Vanderbilt University, Nashville, TN, United States, 6Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States, 7Electrical Engineering, Vanderbilt University, Nashville, TN, United States, 8Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN, United States |
||
We investigate multi-compartment diffusion MRI models in the in vivo spinal cord of multiple sclerosis (MS) patients. We find significant differences in diffusion measures of tissue microstructure and diffusivity indices between healthy controls (N=21) and MS patients (N=12). We also explore their relationships to clinical data, including disability scores, 25-foot walk tests, and disease duration, and note unique trends in these measures with increasing disability. These models may enable improved in vivo characterization of the spinal cord in MS patients and enable quantification of changes in meaningful tissue microstructure indices. |
| 4562 | Radiomics Analysis of Apparent Diffusion Coefficient Maps with Various b-value Combinations for Differentiation of Prostate Cancer | |
| Eo-Jin Hwang 1 and Moon Hyung Choi2 | ||
1Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea, 2Eunpyeong St.Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea |
||
Prostate Imaging-Reporting and Data System (PI-RADS) suggests acquiring multiple apparent diffusion coefficient (ADC) maps including the lowest b-values between 50-100s/mm2 and highest b-values greater than 1400s/mm2. Radiomics is a novel field in medical imaging to advance decision support by utilizing large amount of quantitative features. In this study, we employed radiomics from ADC maps and a linear regression model to differentiate prostate cancer from benign tissues and evaluated the effect of various b-value combinations on ADC maps. We discovered that ADC with the b-values of 100 and 1000s/mm2 was most effective in discriminating prostate cancer with high accuracy. |
| 4563 | Two-step approach in IVIM parameter quantification | |
| Xin Li1, Ryan Kopp2,3, William D Rooney1, Fergus Coakley4, and Mark Garzotto2,3 | ||
1Advanced Imaging Research Center, Oregon Health & Science University, Portland, OR, United States, 2Portland VA Medical Center, Portland, OR, United States, 3Urology, Oregon Health & Science University, Portland, OR, United States, 4Diagnostic Radiology, Oregon Health & Science University, Portland, OR, United States |
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The goal of this study is to investigate a new two-step approach in intra-voxel incoherent motion (IVIM) imaging data quantification. This methods first determines the slow diffusion constant (D) then the pseudo-perfusion parameters (D*, f) using the IVIM model fitting but holding D at pre-determined value. Results show that the new approach returns more consistency parametric maps and the new modeling is favored by Akaike information criterion (AIC). |
| 4564 | Prostate cancer detection with biophysical modeling of diffusion and relaxometry | |
| Gregory Lemberskiy1,2, Yousef Mazaheri3, Herbert Alberto Vargas3, Ricardo Otazo3, Els Fieremans1, and Dmitry S Novikov1 | ||
1Radiology, New York University School of Medicine, New York, NY, United States, 2Microstructure Imaging INC, New York, NY, United States, 3Memorial Sloan Kettering Cancer Center, New York, NY, United States |
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For prostate cancer imaging, increasing the echo time selectively suppresses the cellular tissue, and emphasizes luminal water. We study the ADC dependence on echo time and diffusion time in 3 patients with PIRADS≥4 lesions, and propose a modeling strategy to interpret the changes in signal, as lumen diameter and volume fraction shrink during cancer progression. We evaluate cellular and luminal diffusivities, volume fractions, and luminal diameters as cancer biomarkers. |
| 4565 | Breast MRI combined with clinicopathologic characteristics for Preoperative Prediction of Axillary Lymph Node Metastasis in Breast Cancer | |
| Mei Xue1, Lizhi Xie2, and Jing Li3 | ||
1Radiology, Cancer Hospital Chinese Academy of Medical Sciences, Beijing, China, 2GE Healthcare, MR Research China, Beijing, Beijing, China, 3Cancer Hospital Chinese Academy of Medical Sciences, Beijing, China |
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Accurate identification of axillary lymph node(ALN) involvement in patients with breast cancer is crucial for prognosis and treatment strategy decisions. We developed a clinical model based on breast MR imaging and clinicopathologic characteristics to predict ALN metastasis. Our findings suggest that the clinicopathological features of breast tumor are highly correlated with axillary lymph node metastasis. It can be used to assist clinicians to predict LN metastasis non-invasively. |
| 4566 | Assessment with Partial Peripheral Nerve Transection with Diffusion MRI | |
| Isaac Vicente Manzanera Esteve1, Angel F Farinas1, Alonda C Pollins1, Wesley P Thayer1, Mark Does1, and Richard Dortch1 | ||
1VUIIS, Vanderbilt University Medical Center, Nashville, TN, United States |
||
High-resolution DTI of ex vivo rat sciatic nerve yields viable biomarkers of peripheral nerve recovery following partial transection and surgical repair. FA values decreased with increasing cut depth at 4 weeks. By week 12, the three partial cuts showed elongated FA distributions, most likely representing regions with regenerated (high FA values) and degenerated axons (low FA values). FA finding are influenced by pathological features that affect diffusion both perpendicular and parallel to the axons. |
| 4567 | Characterisation of placentome function using combined diffusion-relaxometry MRI and flow anisotropy | |
| Dimitra Flouri1,2, Jack RT Darby3, Stacey L Holman3, Sunthara R Perumal4, Anna L David5,6, Andrew Melbourne1,2, and Janna L Morrison3 | ||
1School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom, 2Department of Medical Physics & Biomedical Engineering, University College London, London, United Kingdom, 3Early Origins of Adult Health Research Group, University of South Australia, Adelaide, Australia, 4Preclinical Imaging and Research Laboratories, South Australian Health and Medical Research Institute, Adelaide, Australia, 5Institute for Women's Health, University College London, London, United Kingdom, 6NIHR University College London Hospitals Biomedical Research Center, London, United Kingdom |
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Abnormal development of the placenta is postulated as the root cause of preeclampsia and fetal growth restriction. Diffusion-Weighted imaging techniques are considered to give additional placental information. Animal models have been important in invasive validation studies for MRI measurements, as they allow for controlled experiments and analysis of multiple time-points during pregnancy. This study characterises diffusion and perfusion properties of the placenta such as the apparent diffusion coefficient, T2 measurements, fractional anisotropy and perfusion fraction derived from intravoxel incoherent motion analysis on sheep placental tissue in order to validate new imaging markers of placental function. |
| 4568 | Tracing and Therapeutic Evaluation of Transplanted Mesenchymal Stem Cell in The Spinal Cord Injury of Beagles using Diffusion Tensor Imaging | |
| Junting Zou1, Jilei Zhang2, Yuanyuan Xie3, yunpeng Shen4, Jiacheng Du4, Yang Chen4, Yang Chen4, Bing Zhang3, and Xiaoli Mai5 | ||
1Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, China, 2Clinical Science, Philips Healthcare, Shanghai, China, 3Nanjing Drum Tower Hospital, Nanjing, China, 4Southeast University, Nanjing, China, 5Radiology, Nanjing Drum Tower Hospital, Nanjing, China |
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The labelled SPIO of the transplanted MSCs were found in spinal cord segment of TSCI based on T1w and T2w images. The DTI can be of great value in the dynamic evaluation of morphological and neurological changes in beagles after TSCI. FA values are correlated with the impairment and repair of the fiber tracts of the spinal cord. The FA value can satisfactorily evaluate the completeness of the fiber tracts after SCI and the repair of them by stem cells. The combination of conventional MRI and DTI is of great clinical importance for the diagnosis and therapeutic evaluation of SCI. |
| 4569 | Mono-exponential bi-exponential and stretched-exponential diffusion imaging in characterization of nonalcoholic fatty liver disease | |
| Xianfu Luo1, Jing Ye1, Weiqiang Dou2, Jun Sun1, and Wei Xia1 | ||
1Radiology, Clinical Medical School of Yangzhou University, Northern Jiangsu People’s Hospital, Yangzhou, China, 2GE Healthcare，MR Research China, Beijing, China |
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We aimed to compare mono-exponential bi-exponential and stretched-exponential diffusion-weighted imaging(DWI) model in characterizing nonalcoholic liver disease (NAFLD) by providing multiple quantitative parameters. The diagnosis performance for early detection nonalcoholic steatohepatitis (NASH) was compared using characteristic operating curve analysis. Stretched-exponential DWI performed as well as bi-exponential DWI and better than mono-exponential DWI in the noninvasive characterization of NAFLD severity. |