Keywords: Cancer, Breast, Triple-negative breast cancer; Non-triple-negative breast cancer; Amide proton transfer imaging; DWI

Motivation: Triple-negative breast cancer (TNBC) is a highly malignant and prognostically challenging subtype of breast cancer often elusive in conventional MRI scans ^[1.4.5]. Three-Dimensional Amide Proton Transfer Imaging (3D-APT), a non-invasive molecular imaging technique, shows promise in improving TNBC diagnosis. 

Goal(s): This study aimed toinvestigate the diagnostic potential of 3D-APT, alone and in conjunction with diffusion-weighted imaging (DWI), in distinguishing TNBC from non-TNBC.

Approach: Quantitative analysis and comparison of APTw and DWI were conducted.

Results: Results revealed higher APTw and ADC values in TNBC compared to non-TNBC. Both APTw and DWI exhibit commendable diagnostic efficiency individually, while their combined application demonstrates superior discriminatory power.

Impact: These findings provide essential insights for tailoring individualized treatment strategies and assessing prognosis in clinical practice.

Keywords: Cancer, Cancer

Motivation: Enhance the accuracy of distinguishing misdiagnosed or ambiguous cases of pleomorphic adenoma (PA) and Warthin tumor (WT).

Goal(s): This study aims to construct various MRI-based radiomics models employing different machine learning classifiers to determine the optimal models for identifying misdiagnosed or ambiguous PA and WT cases.

Approach: we evaluate the effectiveness of various MRI-based radiomics models.

Results: A nomogram demonstrates exceptional and consistent diagnostic performance. In routine practice, combining clinical parameters is essential for distinguishing between PA and WT.

Impact: MRI-based radiomics models can effectively differentiate misdiagnosed or ambiguous cases of PA and WT. The nomogram is a valuable tool for preoperatively and non-invasively distinguishing between PA and WT, a task often challenging for clinicians and radiologists before surgery.

Keywords: Cancer, fMRI

Motivation: This study aims to establish a predictive model based on IVIM and DCE-MRI that could ultimately improve the prognosis of nasopharyngeal carcinoma (NPC) patients.

Goal(s): This research paves the way for more effective and tailored treatment approaches for NPC patients.

Approach: Patients in the CR group and the NCR group underwent IVIM and DCE-MRI experiments and their quantitative parameters were compared. 

Results: The CR group exhibited higher K^trans value and lower D and ADC values compared to the NCR group. ROC analysis showed that the AUC values of K^trans, D and ADC before treatment were approximately 0.772, 0.751, and 0.699, respectively. 

Impact: Early prediction of the efficacy of NPC patients can optimize the treatment plans, functional MRI techniques can offer insights into the pathological and physiological state of living tissues before morphological changes, prolong their survival, and hold immense clinical significance. 

Keywords: Cancer, Cancer

Motivation: MRI is one of the major methods to diagnose parotid gland tumors. Substantial overlap in the appearance of tumors may be seen on anatomic MR images.

Goal(s):  To assess the usefulness of combined DCE with SWI in the differentiation of benign and malignant tumors.

Approach: We assess the value of DCE and ITSS in the differential diagnosis between malignant and benign parotid tumors.

Results: Results showed that the differences between malignant and benign tumors in Kep (p=0.024) and ITSS (p<0.01) were statistically significant. Combined with ITSS, the diagnostic performance of Kep was improved for differentiating malignant from benign tumor (AUC 0.718 vs 0.927).

Impact: Our current study showed that DCE can elucidate perfusion characteristics of parotid tumors. SWI is a new complementary technique that can detect signal intensity changes from both T2WI and susceptibility differences between tissues. These fndings suggest that SWI and DCE quantitative parameters may facilitate the understanding of the pathophysiological characteristics of parotid tumors.

Keywords: Cancer, Perfusion

Motivation: Tumour cellularity indicates tumour proliferation. Although perfusion MRI parameters have been proposed for non-invasive assessment of tumour cellularity, few studies have validated this theory, particularly in lung cancer. Previous studies provided a free-breathing perfusion MRI method using GRASP.

Goal(s): Therefore, our aim is to investigate the relationship between tumour cellularity and perfusion parameters of MRI using GRASP.

Approach: Pearson correlation coefficients were used to illustrate the relationship between perfusion parameters and cell density.

Results: The findings indicated an inverse correlation between tumour cellularity and V_e. However, the study found no significant correlation between K^trans and cell density.

Impact: It suggests that GRASP perfusion MRI has potential as a non-invasive technique to assess tumour cellularity in lung cancer.

Keywords: Cancer, Cancer, Peritoneal, MRI-Based-CFD

Motivation: High-grade serous ovarian cancer (HGSOC) is hypothesized to initiate at fallopian tubes and ovaries, and then spreads by detaching and floating through the peritoneal fluid to the upper abdomen.

Goal(s): Create a framework that could potentially assess HGSOC cell movement and deposition in the peritoneal cavity using MRI-based computational fluid dynamics.

Approach: Under the assumption that ovarian cancer cells are already prevalent in peritoneal fluid, ovarian cancer cell displacement can be analyzed using MRI-based CFD.

Results: Velocity maps and streamlines and WSS maps were created using CFD simulation results to predict cells transport to the lower peritoneum and diaphragm.

Impact: MRI-based CFD allows temporal and volumetric analysis of the peritoneal cavity and provides insight in ovarian cancer cell spread due to peritoneal fluid flow. Velocities and wall shear stress analysis can be used to identify stagnation points for cell deposition. 

Keywords: Cancer, Head & Neck/ENT

Motivation: Radiomic texture features are considered promising biomarkers for tumor’s response to therapy.

Goal(s): To identify texture features that can enhance predictive accuracy regarding tumor treatment outcomes.

Approach: The study included 13 patients with head and neck cancer undergoing radiation therapy, with MRI (T2w, DWI) conducted before treatment and during early-treatment phase. Image processing, tumor segmentation, and feature extraction are performed.

Results: Wilcoxon signed-rank tests with a Holm-Bonferroni correction reveals that Skewness in T2w-images exhibits significant changes during early treatment. This finding suggests that this feature may hold promise for predicting therapeutic responses, although larger studies are needed to confirm these results.

Impact: The study's preliminary findings suggest that Skewness in T2w images may have the potential to provide useful information for early response assessment in head and neck cancer patients undergoing radiation therapy, warranting further investigation to confirm its clinical significance.

Keywords: Treatment Response, Cancer

Motivation: After curative radiotherapy (RT), there is no commonly accepted method to distinguish between patients with residual disease that may eventually cause disease progression and those who are already cured of the disease in nasopharyngeal carcinoma (NPC).

Goal(s): We proposed a four-category MRI-based lymph node regression (MRI-LRG) grading system to investigate its prognostic value for NPC after RT. 

Approach: 387 NPC patients were included in this retrospective study. Lymph node regression grade was assessed on MRI based on the areal analysis of RT-induced fibrosis and the residual tumor.

Results: Our results showed that MRI-based LRG was an independent prognostic factor for progression-free survival.

Impact: A nomogram, based on LRG-sum, pretreatment EBV DNA, post-RT EBV DNA, sex and N stage factors, was proved to be useful to facilitate risk stratification in NPC. This approach might help to stratify treatment modalities and develop a more effective tailored surveillance program in patients with NPC.  

Keywords: Breast, Cancer, Treatment response, DCE-MRI, neoadjuvant therapy

Motivation: No imaging biomarkers are currently available for predicting response to neoadjuvant systemic treatment (NAST) in triple negative breast cancer (TNBC), contributing to toxicity to patients from ineffective treatment regimens.

Goal(s): To evaluate if quantitative analyses of breast parenchyma can serve as noninvasive biomarker of treatment response in TNBC.

Approach: Mean background parenchymal enhancement (BPE) and radiomic features of fibroglandular tissue from longitudinal DCE-MRI were evaluated using AUC analysis on a prospective cohort of 273 TNBC patients.

Results: Four first order radiomic features were predictive of pCR with AUC>0.6. Multivariable radiomic models and BPE changes had AUC<0.6 for pCR prediction in TNBC undergoing NAST.

Impact: Radiomic features from fibroglandular tissue and background parenchymal enhancement changes in ipsilateral and contralateral breasts using DCE MRI during treatment of triple-negative breast cancer patients were evaluated as noninvasive biomarkers for prediction of pathologic complete response to neoadjuvant systemic therapy.

Keywords: Cancer, Cancer

Motivation: Restriction spectrum imaging (RSI) has demonstrated potential to isolate cervical cancer signal from that of surrounding tissues. Women with post-treatment disease progression wait 3-6 months post treatment to get PET/CT exam to allow for edema/inflammation to subside. Cervical cancer-specific RSI model may allow us to evaluate response-to-treatment earlier.

Goal(s): The goal of this work was to develop an RSI cervical cancer model from a larger cohort of patients.

Approach: We used RSI-derived information from normal cervixes to convert RSI outputs to Z-score maps in cancer patients.

Results: Demonstrated the utility of RSI Z-score maps in differentiating cancers from healthy tissues without exogenous contrast.

Impact: Standard of care evaluation of cervical cancer response-to-treatment is PET/CT 3-6 months post-treatment to allow for edema/inflammation to subside. Cervical cancer-specific RSI model may allow us to evaluate response-to-treatment earlier and better inform patient treatment response without unnecessary delay.

Keywords: Cancer, Prostate, mpMRI, Gleason Score, Upgrading

Motivation: Given discrepancies in biopsy-confirmed histopathology and final pathology in prostate cancer, there is a clinical need to improve diagnosis and treatment planning using multiparametric MRI (mpMRI).

Goal(s): To assess associations between mpMRI lesion location and upgrading of prostate cancer from biopsy-confirmed histopathology to final pathology.

Approach: 191 patients who underwent both MRI-ultrasound fusion biopsy and prostatectomy were included. A modified χ² test assessed associations between mpMRI lesion location and upgrading from biopsy-confirmed histopathology to final pathology. 

Results: mpMRI lesions in the peripheral zone and posterior region were more likely to be upgraded than lesions in the transition zone and anterior region respectively.

Impact: In patients who undergo MRI-ultrasound fusion biopsy and prostatectomy, mpMRI lesions in the peripheral zone and posterior region were more likely to be upgraded from biopsy-confirmed histopathology to final pathology than lesions in the transition zone and anterior region respectively.

Keywords: Cancer, Prostate, Image Registration

Motivation: Bi-parametric MRI (bpMRI) is now part of the diagnostic workup for prostate cancer (PCa). Radiologists cognitively coregister bpMRI sequences when interpreting MRI. Conversely, machine learning (ML) algorithms have difficulty learning this implicit coregistration because of the distortion often present in diffusion-weighted images.

Goal(s): Introduce a novel method for automated 1) bpMRI coregistration; and 2) detection of csPCa. 

Approach: A weakly supervised learning paradigm was employed for bpMRI co-registration. A combination of co-registered bpMRI and the patient’s clinical data was used for automated csPCa detection. 

Results: The proposed method achieved a true and false positive rate of 86% and 41% on 100 test cases.

Impact: The obtained results demonstrated the value of co-registration and including patient clinical data for designing ML-based methods for automated csPCa detection. The proposed algorithm might improve the accuracy of reading bpMRI, thereby beneficial for patients with prostate cancer. 

Keywords: Cancer, Bladder, APT, DWI

Motivation: Conventional MRI has certain limitations in distinguishing between malignant and benign urinary bladder (UB) lesions. 

Goal(s): Compare the diagnostic value of Amide proton transfer (APT) imaging with diffusion-weighted imaging (DWI).

Approach: Participants with confirmed UB lesions underwent preoperative multiparametric MRI. The APT signal intensity (represented by asymmetric magnetization transfer ratio, MTR_asym), and apparent diffusion coefficient (ADC) values were compared between malignant and benign UB lesions, and their diagnostic performance was evaluated with receiver operating characteristic (ROC) curve analysis. 

Results: The MTR_asym value was significantly better in differentiating urothelial carcinoma from benign UB lesions than the ADC value.

Impact: Conventional MRI exhibits limitations in accurately distinguishing between malignant and benign urinary bladder (UB) lesions. Amide Proton Transfer (APT) imaging shows promise in effectively discriminating between malignant and benign UB lesions, surpassing the performance of Diffusion-Weighted Imaging (DWI).

Keywords: fMRI Analysis, Quantitative Imaging, ovarian tumor

Motivation: Accurate diagnosis and staging of ovarian cancer play a key role in the selection of treatment plan, surgical method and determination of the circumference

Goal(s): Tumor intratumoral susceptibility signal (ITSS) can reflect the new growth inside the tumor
Vascular and bleeding conditions, ITSS have been widely used in many departments
Although few studies have applied this technique to ovarian cancer

Approach: Automatically quantitative ITSS prediction of clinical FIGO staging of ovarian cancer was performed by using AS (AnatomySketch 1.0) software (Dalian University of Technology)

Results: The automatic quantitative ITSS rate was significantly higher in advanced ovarian cancer than in early ovarian cancer

Impact: Automatic quantitative ITSS is expected to be applied to the study of ovarian tumors and more sites in the future. ITSS can effectively predict FIGO type of ovarian cancer and provide valuable information for making treatment plan and judging prognosis

Keywords: fMRI Analysis, Breast

Motivation: Limited clinical studies have explored the potential of Amide Proton Transfer Weighted Imaging (APTWI)  in discriminating between benign and malignant breast lesions and molecular subtypes of breast cancer.

Goal(s): This study aims to assess the clinical utility of APTWI and DKI in the evaluation of benign and malignant breast diseases and the determination of molecular subtypes of breast cancer.

Approach:  We quantitatively analyzed lesions in breast MRI scans of patients prior to surgery and evaluated the diagnostic value of each quantitative parameter.

Results:  APTWI did not exhibit superior diagnostic efficacy compared to DKI and ADC in characterizing the molecular subtypes of breast cancer.

Impact: Our study underscores that APT imaging, as a novel quantitative magnetic resonance technique, does not confer a diagnostic advantage over DKI and ADC in the context of breast disease assessment.

Keywords: fMRI Analysis, Breast

Motivation: The lack of guidelines or recommendations for the ROI size of DWI and synthetic MRI.

Goal(s): To investigate the effect of different ROI positioning methods on both ADC and synthetic MRI measurements and to subsequently evaluate the diagnostic performance of differently shaped ROIs.

Approach: Four different ROI positioning methods on ADC and synthetic parameters measurements. 

Results: Square ROI showed the optimal AUC followed by freehand ROI. T2 + ADC were more diagnostic than ADC or T2 alone.

Impact: The different ROI positioning methods used had a significant impact on the quantitative measurements and the performance in differentiating benign from malignant breast tumors.

Keywords: Breast, Breast, diffusion magnetic resonance imaging; deep learning, Magnetic resonance imaging; kaiser score

Motivation: While the Kaiser score serves a pivotal role in diagnosing breast cancer, it still encounters scenarios where false positives necessitate biopsy confirmation.

Goal(s): This study aims to investigate approaches to enhance the diagnostic efficacy of the Kaiser score through MRI.

Approach: Leveraging deep learning to enhance both the quality of DWI images and diagnosis, we sought more effective indicators in conjunction with the Kaiser score.

Results: ADC values derived from DWI images reconstructed using deep learning, with a b-value of 800 s/mm², in tandem with the Kaiser score, significantly enhance the diagnostic performance nearing 1.

Impact: Integrating DWI under deep learning with the Kaiser score can elevate the accuracy of differentiating between benign and malignant breast cancers to almost 100%, leading to substantial improvements in breast cancer diagnosis and a reduction in unnecessary biopsies.

Keywords: fMRI Acquisition, Breast, Amide proton transfer weighted imaging, Diffusion kurtosis imaging

Motivation: Breast Imaging Reporting and Data System (BI-RADS) is an internationally recognized scoring standard for the diagnosis of breast lesions, but it is highly subjective.

Goal(s): To evaluate the diagnostic performance of amide proton transfer weighted imaging (APTWI) and diffusion kurtosis imaging (DKI) in terms of differentiating breast lesions and to compare them with the BI-RADS independently or jointly.

Approach: Prospective cohort study

Results:  APTWI and DKI can be used to distinguish  breast lesions. The combination with APTWI and DKI can significantly improve the AUC values and specificity when compared with BI-RADS alone. The APTWI+DKI+BI-RADS has the best diagnostic performance in distinguishing  breast lesions.

Impact: The combined APTWI and DKI outperformed BI-RADS alone in distinguishing benign and malignant breast lesions.

Keywords: fMRI Analysis, Breast, Cancer

Motivation: APTWI and DWI had still some controversies between their parameters and some biological status.

Goal(s): To assess the value of amide proton transfer-weighted imaging (APTWI) and diffusion weighted imaging (DWI) in differentiating biological subtypes and predicting the biological status of breast tumors.

Approach: The Kruskal-Wallis H test and Post-hoc pairwise comparison, Pearson's correlation analysis. Independent samples t-test. Receiver operating characteristic (ROC) analysis.
 

Results: MTRasym (3.5 ppm) was higher in breast tumours that were TN, ER-, PR-, and high-Ki-67. Compared to DWI, APTWI is more useful in predicting the biological status of breast cancers.

Impact:  Compared to DWI, APTWI is more useful in predicting the biological status of breast cancers.

Keywords: Breast, Cancer

Motivation: DWI’s challenging spatial resolution could be addressed by deep-learning-based image reconstruction, by reducing noise without increasing acquisition time.

Goal(s): To compare the image quality of the Echo-Planar-Imaging-Deep-Learning (EPI-DL) DWI sequence with the clinically used simultaneous-multi-slice (SMS) RESOLVE in breast lesions.

Approach: EPI-DL and RESOLVE breast images from 20 participants were qualitatively evaluated ed. Quantitative image quality metrics of SNR and CNR on both high b-value (b800) images and ADC maps were calculated.

Results: SNR in RESOLVE vs. EP-DL differed statistically significantly in manually delineations for b800 (p=0.006), ADC maps (p=0.001), and in ADC circularly delineations (p=0.001).

Impact: DWI-DL reconstruction may be clinically useful for addressing low-spatial resolution without compromising acquisition time and image quality. Such benefits coupled with the available methods of readout segmentation and SMS acquisitions may further enhance the value of DWI in breast imaging.

Keywords: Breast, Breast

Motivation: Noninvasive imaging methods capable of revealing molecular characteristic heterogeneity in breast cancer may help to compensate for the sampling errors of biopsy and guide tailored treatment.
  

Goal(s): To explore the value of T1ρ mapping in preoperatively predicting the status of ER, PR, HER-2 and Ki-67 in breast cancer.

Approach: This is a prospective diagnostic study. The differences of T1ρ values of tumors with different status of ER, PR, HER-2 and Ki-67 were compared between groups.

Results: The T1ρ values showed significant differences in ER (P<0.01), PR(P=0.01), HER-2 (P=0.04), and Ki-67(P=0.02) negative and positive groups, with respective AUCs of 0.867, 0.79, 0.77, and 0.75.

Impact: T1ρ mapping is expected to be a non-invasive tool to help evaluate ER, PR, HER-2, and Ki-67 status before surgery in breast cancer, and to provide assistance in individualized treatment.

Keywords: Segmentation, Machine Learning/Artificial Intelligence, Fibroglandular tissue; Background parenchymal enhancement; Breast cancer

Motivation: Fully automatic segmentation of fibroglandular tissue (FGT) and background parenchymal enhancement (BPE) quantification methods with high generalizability for different FGT levels are still lacking.

Goal(s): We aimed to improve the segmentation accuracy and generalizability across various FGT levels that accurately quantify FGT density and BPE.

Approach: A novel anatomy-aware loss function based on the variations in FGT level was applied in a fully automatic segmentation model training on breast MRIs.

Results: The accuracy of breast tissue segmentation, FGT density estimation, and BPE quantification were improved at various FGT levels.

Impact: The anatomy-aware loss function can help improve the generalization of the breast tissue segmentation model on patients with different breast densities, thereby enabling the model to be more widely used in fibroglandular tissue density estimation and background parenchymal enhancement quantification.

Keywords: Breast, Breast, CEST, CEST-MRF, DRONE

Motivation: To enable quantitative CEST and MT maps in breast tissue for potential tumor characterization.

Goal(s): To explore the feasibility of simultaneously obtaining T1, T2, CEST and MT maps in breast tissue.

Approach: A CEST-MRF pulse sequence was used to measure the amide and semi-solid exchange rate and volume fractions. Quantitative maps were obtained using a neural network trained on physics-derived signals.

Results: The proposed approach yields water T1 and T2 relaxation maps, amide exchange and volume fraction maps, and semi-solid exchange and volume fraction maps in the breast in a scan time of less than 2 minutes.

Impact: Comprehensive quantitative T1, T2, amide CEST and MT bilateral breast imaging in under 2 minutes can improve the detection and characterization of breast cancer and the response to treatment in a clinical setting without the use of a contrast agent.

Keywords: Breast, Cancer, sodium, breast, inversion recovery, DCE-MRI

Motivation: Breast cancer MRI has high sensitivity but has an unmet need for increased specificity. Sodium MRI has the potential to improve tumor characterisation and thus treatments.

Goal(s): To determine whether there is a relationship between tissue permeability by correlating intracellular sodium fraction with pharmacokinetic parameters.

Approach: Conventional DCE-MRI parameters were acquired as well as intracellular sodium fraction maps (= inversion recovery sodium / total sodium concentration) in 17 breast cancer lesions (grade 1:n=3; grade 2: n=9; grade 3:n=7).

Results: The fraction of intracellular sodium to total sodium concentration had significant correlations (p-values <0.11) with K_trans and k_ep, and with cancer grade.

Impact: Breast cancer imaging has an unmet need to differentiate ductal carcinoma from benign and invasive lesions. Sodium MRI can provide intra- and extra-cellular sodium measurements, which may improve lesion differentiation by using endogenous contrast.

Keywords: Software Tools, Breast, background parenchymal enhancement

Motivation: Background parenchymal enhancement (BPE) is linked to cancer treatment outcomes. Unfortunately field strength, acquisition parameters, etc, influence BPE. More reliable methodology is needed.

Goal(s): We tested a novel BPE measure as contrast concentration to differentiate patient groups. Test1: pathologically complete response after neo-adjuvant therapy vs incomplete response. Test 2: pre- vs post-menopause.

Approach: From a large public imaging archive we randomly selected 32 exams each for Tests 1-2 to compare effect sizes for signal and concentration-based BPE.
 

Results: For both tests, group effects measured using Cohen-d were 2X larger for concentration-based BPE. BPE robustness is improved by converting MR signal to contrast concentration

Impact: Background parenchymal enhancement (BPE) is linked to cancer treatment outcomes. Unfortunately field strength, acquisition parameters, etc, influence conventionally acquired BPE. We propose and validate, using two independent datasets, a more reliable BPE methodology based on quantitative measurement of contrast concentration.

Keywords: Breast, Breast

Motivation: Elevated interstitial fluid pressure (IFP) or reduction in velocity (IFV) in breast cancer patients has been shown to contribute to treatment resistance, but its measurement is impractical in clinical practice.

Goal(s): Our goal is to map IFP and IFV from DCE breast MRI and to evaluate its association with treatment response.

Approach: We developed pharmacokinetic-fluid flow models to evaluate its association between IFP, IFV and neoadjuvant chemotherapy (NAC) responses.

Results: We observed small differences in IFP and IVF between NAC treatment cohorts. Initial data based on pre-NAC DCE-breast MRI suggest a potential for early prediction of treatment response of primary tumors.

Impact: Non-invasive pharmacokinetic and computational fluid dynamics modeling in breast DCE-MRI can provide information of tumor IFP and IFV. This approach has the potential to serve as a valuable non-invasive clinical tool for predicting early treatment response.

Keywords: Liver, Liver

Motivation: Liver metastases with contrast uptake on hepatobiliary phase images in patients with pancreatic ductal adenocarcinoma (PDAC) were related to poor prognosis. Prior study focused on visual assessment of the tumor, however, reliable quantitativeness is necessary.

Goal(s): To evaluate the relationship between the gadoxetic acid uptake in liver metastases and overall survival (OS) in patients with PDAC using histogram analysis.

Approach: The best quantitative parameter was analyzed comparable with visual assessment using receiver operating characteristic curve analysis.

Results: Patients with the entropy of >5.422 in the greatest liver metastasis exhibited lower OS rates than those with ≤5.422 (mean, 9.6 months vs 37.7 months).

Impact: Liver metastases with contrast uptake on hepatobiliary phase images were related to poor prognosis. Entropy on histogram features in the greatest liver metastasis can be a potential quantitative imaging biomarker to predict overall survival in patients with pancreatic ductal adenocarcinoma.

Keywords: Liver, Cancer

Motivation: Looking for an economical and convenient magnetic resonance imaging technique to detect whether hepatocellular carcinoma is complicated with venous tumor thrombi.

Goal(s): Using a 5.0T ultra-high field MRI imaging sequence to detect the presence of cancer thrombi in HCC patients without the use of contrast agents.

Approach: Statistical analysis of the accuracy of magnetic sensitivity weighted imaging (SWI) in the diagnosis of cancer thrombi using enhanced scanning as the diagnostic criteria.

Results: SWI has high diagnostic accuracy for cancer thrombi without the use of contrast agents.

Impact: Whether HCC with thrombi is crucial for determining clinical treatment plans. Some patients may not be able to use contrast agents, and the cost of contrast agents is high. SWI can effectively display tumor thrombi,  and can reduce patient costs.

Keywords: Cancer, Cancer, PDAC

Motivation: The poor prognosis of pancreatic ductal adenocarcinoma (PDAC) creates an urgent need to identify new targets. PDAC is a metabolically active cancer that is glutamine avid.

Goal(s): We downregulated the glutamine transporter, SLC1A5, in the patient-derived human cancer cell line, Pa04C, and observed significant tumor growth delay.

Approach: High-field, high-resolution ¹H MRS was performed of extracts from wild type, empty vector, and SLC1A5 downregulated tumors that was mapped to transcriptomic analysis of the corresponding cells, and to mass spectrometry imaging (MSI) of human normal and PDAC tissue.

Results: Common pathways were identified from the analysis that identify new targets for PDAC.

Impact: This study contributes to our comprehension of how the glutamate transporter SLC1A5 impacts the transcriptomics of pancreatic cancer cells, influences tumor metabolism, and its connection to variations in human PDAC metabolism. These findings could provide new insights into PDAC cancer.

Keywords: fMRI Analysis, Cancer

Motivation: The T staging of rectal cancer mainly relies on high-resolution T2-weighted MRI sequences. However, there are cases of both over-staging and under-staging.

Goal(s): To investigate the preliminary application value of quantitative susceptibility mapping in the T staging of rectal cancer.

Approach: In addition to the conventional scanning sequences, horizontal axial T2-weighted imaging (T2WI) and QSM sequences were acquired. The tumor segmentation was done with reference to T2WI images at the QSM-weighted image. The magnetic susceptibility histogram data of tumor tissues were calculated with FireVoxel build 394D software.

Results: The differences of magnetic susceptibility histogram parameters in different T-stage rectal cancer were statistically significant.

Impact: Quantitative susceptibility histogram shows promise in aiding the T staging of rectal cancer.

Keywords: fMRI Analysis, Bladder

Motivation: The evaluation of muscular invasion in bladder cancer is essential for determining the optimal surgical approach for patients¹. The application of Synthetic magnetic resonance imaging (MAGic resonance imaging, MAGiC) in assessing muscular invasion has not been reported previously².

Goal(s): To assess the value of MAGiC in diagnosing muscular invasion in bladder cancer.

Approach: This study evaluated the differences of T1/T2/ADC and VI-RADS between non-muscle invasive and muscle invasive lesions and the differentiation performance of the indices. 

Results: Improved diagnosis performance was obtained with combined T2 relaxometry and VI-RADS in compared with each single index.

Impact: The findings of this study demonstrate that quantitative MRI parameters enhance the precision and objectivity of assessing muscular invasion in bladder cancer, exhibiting minimal dependence on the clinical experience of diagnostic physician, thus holding promise for their wide-ranging application.

Keywords: Kidney, DSC & DCE Perfusion, kidney, renal blood flow, standardisation, consensus

Motivation: Clinical translation of renal functional and quantitative MRI is hindered by a lack in standardisation of scan protocols.

Goal(s): To develop expert consensus-based technical recommendations on the acquisition and post-processing of renal DCE-MRI.

Approach: Experts were recruited and surveyed following the Delphi method to create consensus-based technical recommendations in renal DCE-MRI. Preliminary results will be used to construct the second survey round.

Results: 16 experts responded to the preliminary survey. Consensus statements informed by the responses were drafted and will be circulated and refined in the next phase of the project.

Impact: The insights obtained from this work will be invaluable in delivering recommendations that are comprehensive and widely accepted. Consensus-based technical recommendations for renal DCE-MRI aim to contribute to harmonisation of MRI scan protocols across sites, facilitating clinical translation.

Keywords: Kidney, Data Analysis, Layers

Motivation: To provide improved methods to estimate cortical-medullary changes in multiparametric MRI measures of the kidney.

Goal(s): To develop an analysis method for use with 3D data to generate quantitative-depth-based cortical-medullary layers which can be applied to any multiparametric map.

Approach: 3DQLayers segments the kidney into layers based on their distance from the renal surface using the Trimesh Python library.

Results: Generated 3D layers can be applied to multiparametric MRI scans collected in the same session. Here, this is applied to assess cortical layer profiles and contour plots of quantitative T₁-mapping, R₂^*-mapping and perfusion measures, and to estimate renal cortical thickness.

Impact: 3DQLayers provides a layer-based analysis technique for renal multiparametric MRI data, extending traditional ROI-based methods. Layer profiles of any quantitative MRI data can be output and average renal cortical thickness estimated, these are important measures to study in renal disease.

Keywords: Kidney, Kidney

Motivation: ASL-measured perfusion values are assumed to change homogeneously across the kidney. We believe that additional information might be retrieved by analyzing regional perfusion differences. 

Goal(s): Renal perfusion is assumed to decrease with aging but also in renal pathologies.

• Does renal perfusion decrease uniformly?

Approach:

• Retrieve renal ASL images from 27 subjects.
• Create one 2D mesh per subject.
• Pool the results for 3 different groups.
• Analyze the variation of renal perfusion.

Results:

• Patients compared to younger healthy volunteers (HVs) show lower perfusion.
  
• Patients compared to older HVs exhibit a negative variation in the kidney lateral outermost region, while other regions show higher perfusion values.

Impact: Understanding kidney blood flow patterns could aid early disease detection and personalized treatments. Identifying specific regions affected in kidney patients might improve targeted therapies. This knowledge may enhance patient outcomes, potentially leading to a better life quality for kidney patients.

Keywords: Kidney, Kidney

Motivation: Whole-organ renal oxygen metabolism increases by 40-65% during early stages of kidney disease. Current biomarkers are sensitive to later kidney disease stages once tissue damage has already occurred.

Goal(s): Non-invasively quantify renal metabolic rate of oxygen during free-breathing, to be used as a potential biomarker for early diagnosis of kidney disease. 

Approach: A new MRI sequence was tested in healthy adults at the left kidney that simultaneously measures blood water T₂ and blood flow rate, from which metabolic rate of oxygenation is determined from Fick’s Principle. 

Results: Quantification of metabolic parameters show good agreement between free-breathing and breath-hold acquisitions.

Impact: The renal metabolic rate of oxygen was non-invasively quantified at the left kidney during free-breathing in healthy adults. Renal oxygen metabolism can be a valuable physiological biomarker for early diagnosis of kidney disease before irreversible tissue damage occurs.

Keywords: Kidney, Motion Correction

Motivation: Post-contrast T1-weighted imaging is vital for diagnosing renal MRI by assessing vasculature, finding vascular abnormalities, and evaluating kidney function. However, breathing motion degrades image quality, which is problematic since breath-holding is difficult for some patients, especially children. 

Goal(s): There is an urgent need for motion-robust renal imaging for breath-holding challenged patients.

Approach: In this study, we demonstrated the effectiveness of FIDnavs in correcting motion-related artifacts in clinical post-contrast T1w-imaging of kidneys. We evaluated our pipeline on 5 pediatric patients, both retrospectively and prospectively, using FIDnav-based motion correction (MoCo).

Results: Utilizing FIDnavs for MoCo, reduced motion artifacts and blurring in post-contrast T1w-imaging. 

Impact: Use of FID-navigated motion correction for post-contrast T1w-imaging of kidneys can reduce motion artifacts and minimize the scan time by eliminating the need of gating. However, the calibration step required for prospective motion correction should be eased for pediatric patients. 

Keywords: Kidney, Kidney

Motivation: Alterations of renal water transport and exchange may reflect kidney function and disease.

Goal(s): To develop and test a novel sequence for quantitative assessment of intrarenal fluid exchange.

Approach: We developed a T₂ selective labeling sequence for water exchange quantification and tested it on healthy subjects.

Results: Images showed a characteristic spatial distribution of signal with increased signal in the renal medulla, in support of its detection and assessment of fluid exchange.

Impact: Exchange imaging by T₂ selective saturation may open new possibilities for the study of water transport and exchange and the diagnosis of renal disorders.

Keywords: Kidney, MR Fingerprinting

Motivation: A free-breathing renal joint T₁-T₂ MR fingerprinting technique with respiratory navigators would allow kidney function to be mapped non-invasively in patients that cannot hold their breath.

Goal(s): To assess the effect of rejected respiratory navigators on the relaxation times and their precision.

Approach: Joint kidney T₁-T₂ maps with four different navigator acceptance window widths (NAWW, from ±4mm to ±32mm) were acquired in 8 healthy volunteers and compared to clinical routine maps.

Results: Map accuracy and precision were high and did not change as a function of NAWW, suggesting that the NAWW can be chosen as a balance between navigator inefficiency and through-plane motion.

Impact:  This work demonstrates the feasibility of a free-breathing 2D joint T₁-T₂ renal MR fingerprinting in healthy volunteers. The navigator allows a free breathing acquisition with limited through-plane motion.

Keywords: Kidney, Quantitative Imaging

Motivation: Quantitative MRI techniques, such as T₂ and T₂* mapping, have the potential to become important imaging biomarkers for non-invasive renal tissue assessment. However, clinical T₂ and T₂* mapping faces challenges posed by respiratory motion.

Goal(s): This study explores the feasibility of simultaneous T₂ and T₂* mapping of the human kidneys with mitigated respiratory motion artifacts, using the 2in1-RARE-EPI technique.

Approach: We used the distinctive acoustic noise pattern generated by the gradient coil switching during 2in1-RARE-EPI data acquisition to guide the subject to time their respiration during the scan.

Results: This approach facilitates high in-plane resolution (1x1x5mm³) T₂ and T₂* mapping of human kidneys. 

Impact: Our approach for simultaneous and motion-synchronized T₂ and T₂* mapping of the human kidney provides a technical foundation for swift translation into the clinic and for gaining a better mechanistic understanding of renal (patho-)physiology.

Keywords: Kidney, Kidney, Renal blood flow, Perfusion, Phase contrast, Arterial spin labelling

Motivation: Variations in dietary conditions can impact renal blood flow (RBF), but it is currently unknown whether fasting overnight can affect the measurement. A recent consensus for phase contrast (PC) advises against fasting, but similar consensus for arterial spin labelling (ASL) was not reached. Other laboratory tests might require fasting, leading to variability in preparation for MRI. It is therefore critical to understand whether fasting affects the measurement

Goal(s): This study investigates the effect of fasting compared to the recommended MRI preparation.

Approach: ASL and PC acquired in healthy volunteers.

Results: No significant difference between fasting and consensus-preparation was found for RBF and perfusion.

Impact: A strict control for diet may not be required for MRI studies measuring renal blood flow and perfusion using phase contrast and arterial spin labelling. 

Keywords: Kidney, Kidney

Motivation: Magnetic Resonance Elastography (MRE) can determine tissue isotropic stiffness measurements to assess kidney disease and injury. Similarly, Diffusion Tensor Imaging (DTI) in combination with MRE can provide additional information regarding tissue health through anisotropic stiffness.

Goal(s): The goal of this study is to compute tissue isotropic and anisotropic stiffness of the cortex, medulla, and whole kidney to compare against both measurements.

Approach: 9 subjects were imaged for both MRE and DTI scans to estimate isotropic and anisotropic stiffness, respectively.

Results: Preliminary results indicate a good correlation between isotropic stiffness and anisotropic stiffness in all regions.

Impact: The application of MRI diffusion scans in conjunction with MRE shows promise in elucidating hard to detect disease and injury in human kidney.

Keywords: Kidney, Data Analysis, Aging, chronic kidney disease, diagnosis,renal stiffness, intravoxel incoherent motion, shifted apparent diffusion coefficients ,virtual elastography

Motivation: Various b values of shifted apparent diffusion coefficients (sADC) and virtual magnetic resonance elastography (vMRE) were not validated for renal stiffness. Hence, a new method was required for assessing chronic kidney disease (CKD) noninvasively.

Goal(s): To investigate the relationship between sADC and vMRE and the clinical indicators and diagnostic efficacy of CKD.

Approach: The μ_diff generated with sADC was used to quantify renal stiffness. The data were analyzed using Spearman, partial correlation, Mann–Whitney U test, and receiver-operating characteristic curves. 

Results: sADC and vMRE were effective in assessing renal function and diagnosing CKD, but distinctly at various b values.

Impact: This study provides a reference b value for sADC and vMRE and suggests that vMRE could be used as a new noninvasive technique to assess chronic kidney disease. 

Keywords: Kidney, Arterial spin labelling, Magnetic resonance elastography, chronic kidney disease, perfusion assessment, renal stiffness

Motivation:  The impact of renal perfusion on stiffness values is yet to be conclusively validated, which has hindered the diagnostic application of magnetic resonance elastography (MRE) in patients with chronic kidney disease (CKD).

Goal(s): To explore the characteristics of renal perfusion and stiffness values in patients with CKD and their correlation.

Approach:  Renal MRE and arterial spin labeling (ASL) were used to measure renal stiffness and blood flow. The study employed t-test, receiver-operating characteristic curves, and Spearman correlation for data analysis.

Results:  The two techniques were effective in diagnosing CKD, simultaneously confirming the influence of perfusion factors on stiffness.

Impact: This preliminary human study further supported the correlation between renal stiffness and perfusion, supporting the enhanced diagnostic efficacy of combining MRE and ASL for CKD, thus facilitating staging.

Keywords: Kidney, Kidney, CKD, ASL, DWI, BOLD, MRE

Motivation: Multiparametric (mp) MRI can enable functional characterization of entire kidneys for the assessment of patients with chronic kidney disease (CKD).

Goal(s): To evaluate quantitative mpMRI for functional characterization in CKD patients and compare against healthy volunteers.

Approach: Seven CKD patients and 6 healthy volunteers underwent MRI including ASL (perfusion), DWI (cellularity), BOLD (oxygenation), and MRE (fibrosis).

Results: ASL measured perfusion was significantly lower in CKD patients compared to healthy volunteers (P<0.05), while DWI measured ADC was not different (P=0.36). BOLD measurement was statistically different in Medulla (T2*: P=0.009; R2*: P=0.05), but was not different in cortex (T2*: P=0.08; R2*: P=0.32).

Impact: Multi-parametric MRI, particularly using ASL measured perfusion and BOLD measured R2* provides functional characterization of kidneys that could facilitate longitudinal monitoring and therapeutic interventions in CKD patients.

Keywords: Kidney, Transplantation, kidney

Motivation: Although renal biopsy is the gold standard for the diagnosis of renal allograft dysfunction, it is an invasive procedure. Magnetic resonance imaging (MRI) can be used to evaluate renal allograft function in a noninvasive manner.

Goal(s): To investigate the utilities of various diffusion models in evaluating early renal allograft function.

Approach: Follow-up MRI was performed at 14, 30, and 90 days after renal transplantation to evaluate correlations between MRI parameters and estimated glomerular filtration rate, along with their abilities to measure renal function after transplantation.

Results: Various diffusion models can reflect changes in early renal function after transplantation.

Impact: Intravoxel incoherent motion and diffusion kurtosis imaging models may serve as useful tools to investigate early renal function after transplantation.

Keywords: Lung, Lung, Mid-field

Motivation: Pulmonary perfusion imaging requires ionizing radiation (CT) or gadolinium-based contrast agents (MR) and therefore cannot be used on all patients.

Goal(s): We propose an easy-to-prescribe non-contrast pulmonary perfusion imaging method to improve the diagnosis and monitoring of pulmonary hypertension.

Approach: We designed a free-breathing arterial spin labeling imaging sequence that is compatible with whole-lung coverage at 0.55T. We demonstrate this method in healthy volunteers and a swine model. 

Results: We measured 11.55±4.09% and 7.76±2.62% ASL signals using inversion and saturation labeling which was comparable between breath-held and free-breathing scans. Perfusion defects were clearly visualized in the swine model. 

Impact: Our method should enable qualitative assessment of non-contrast pulmonary perfusion in patients who are contraindicated for gadolinium-based contrasts or who need frequent monitoring of pulmonary perfusion. Our method would contribute to enabling contrast-free comprehensive pulmonary exams at 0.55T.

Keywords: Lung, Lung

Motivation: Vascular stiffness and secondary pulmonary hypertension in COPD are common. Noninvasive measurement of pulse wave velocity as a marker of arterial stiffness by PREFUL MRI is feasible. The effect of bronchodilators on PWV is unclear.

Goal(s): To determine the effect of bronchodilators on pulmonary artery stiffness as measured by PWV derived using PREFUL MRI.

Approach: PREFUL MRI in 52 patients before and after placebo-controlled bronchodilator treatment.  

Results: In patients with elevated PWV, a significant decrease in PWV was measured after treatment. In the placebo control period and in the patients with normal baseline PWV, no significant changes were observed. 

Impact: Pulmonary artery stiffness can be measured by PREFUL MRI-based pulse wave velocity (PWV) calculation.  PREFUL MRI is a promising tool to monitor PWV changes after bronchodilator treatment.

Keywords: Lung, Quantitative Imaging

Motivation: The optimum flip angle which provides a trade-off between ventilation and perfusion signal in free-breathing proton MRI (3 T) of the lung is unknown. 

Goal(s): To optimise the acquisition of free-breathing pulmonary proton MRI to maximise both ventilation and perfusion signals.

Approach: Assessment of the flip angle in a 2D fast field echo (FFE) sequence in healthy volunteers utilising voxel-wise lung ventilation (VOLVE) analysis.

Results: Increasing the flip angle tends to reduce the ventilation signal but increase the perfusion signal. A flip angle higher than the Ernst angle for lung parenchyma is recommended when assessing both perfusion and ventilation.

Impact: Demonstration of the dependence of 2D FFE proton MRI ventilation and perfusion signal on flip angle to inform future studies. A flip angle greater than the parenchyma Ernst angle maintains a strong ventilation signal without supressing the perfusion signal.

Keywords: Lung, Lung, DCE-MRI

Motivation:  DCE-MRI were used to valuate the vascular construction of solid solitary nodules (SPN) to help the qualitative clinical diagnosis.

Goal(s):  To evaluate the value of DCE-MRI in the vascular architecture of solid SPN.

Approach: 32 patients with SPN underwent chest DCE-MRI. Pathological specimens and vascular structural parameter MVD and MPI were evaluated by immunohistochemical markers CD31, VEGF, and SMA.

Results: Ktrans and Ve from DCE-MRI had significant differences between benign and malignant SPN, and high diagnostic efficacy with AUC of 0.893 and 0.880. Ktrans and Kep were significantly positively correlated with CD31-MVD and VEGF, while negatively correlated with MPI. 

Impact: Dynamic enhancement Magnetic resonance imaging can be used as an effective auxiliary means to distinguish benign and malignant pulmonary nodules.

Keywords: Lung, DSC & DCE Perfusion, Lung

Motivation: Dynamic Contrast Enhancement-CT (DCE-CT) and Dynamic Contrast Enhancement-MRI (DCE-MRI) are among the most valuable imaging techniques for the noninvasive assessment of tumor vascular perfusion and trophoblast angiogenesis in lung cancer.

Goal(s): To evaluate the image quality value of free-breathing GRASP in MRI of lung cancer.

Approach: All patients underwent free-breathing DCE-MRI with breath-holding VIBE sequence before and after contrast injections. Two experienced thoracic radiologists independently evaluated the overall image quality, lesion contour, artifact level, and diagnostic confidence using the patient's simultaneous CT images as a reference.

Results: Free-breathing GRASP DCE-MRI technique is a reliable method for the high-resolution imaging of pulmonary lesions.

Impact: The study showcases GRASP's superiority over BH-VIBE in lung cancer imaging, offering clearer results with patient comfort. This breakthrough prompts investigation into GRASP's broader clinical applications and sets a new standard in patient-friendly MRI diagnostics.

Keywords: Lung, Cancer, ultrashort echo time (UTE)；oxygen-enhanced MRI (OE-MRI)

Motivation: People pay more and more attention to the high incidence and mortality of lung cancer. 

Goal(s): To develop a non-invasive, radiation-free imaging scheme to distinguish between benign and malignant solid pulmonary nodules and to improve the management of patients with pulmonary nodules.

Approach: Two three-dimensional ultrashort echo time series scans of pulmonary nodules were performed on 3.0T MRI under the condition of 21% and 100% oxygen, respectively, and the percent signal enhancement was used as the evaluation index of benign and malignant nodules.

Results: The increase of the percent signal enhancement in benign pulmonary nodules was higher than that in malignant pulmonary nodules.

Impact: This imaging tool will reduce or eliminate the radiation damage caused by computed tomography, reduce clinicians' over-dependence on high resolution computed tomography, and bring new gospel for personalized and accurate diagnosis and treatment of patients.

Keywords: Lung, COVID-19, Lung

Motivation: COVID-19's persistent respiratory effects are well-documented, but the long-term pulmonary consequences, particularly after severe illness, remain inadequately understood.

Goal(s): To identify enduring perfusion deficits in the lungs of individuals previously hospitalized with COVID-19, using dynamic contrast-enhanced (DCE) MRI.

Approach: The study recruited adults post-COVID-19 for a comprehensive pulmonary assessment. Dynamic contrast enhanced MRI was used to quantify lung perfusion and relating them to COVID-related hospitalization.

Results: The study found a significant correlation between MRI perfusion parameters and previous hospitalization for COVID-19. It indicated that patients with a history of hospitalization due to COVID-19 might experience persistent alterations in lung perfusion.

Impact: Our research, through dynamic contrast-enhanced MRI, reveals persisting lung perfusion deficits in post-hospitalized COVID-19 patients, notably related to severity of initial disease. This aids in understanding post-COVID pulmonary sequelae, guiding future patient management and research on long-term COVID-19 impact.

Keywords: Digestive, Digestive, PC-MRI, Intestine

Motivation: Measuring the reproducibility of 2D PC-MRI measures of intestinal blood flow is important for its clinical application.

Goal(s): The aim is to examine the precision of 2D PC-MR measures of resting intestinal blood flow and postprandial blood flow changes.

Approach: Ten healthy men were scanned on eight different days collecting at least three repeated 2D PC-MRI measures each day. Participants were also given an oral glucose tolerance test. 

Results: A CoV of 6%-9% was obtained for consecutive flow measures and 13%-15% for between day measurements. Flow increased 75% in the arteria mesenterica superior and 60% in the vena portae after glucose consumption.

Impact: The low variability of repeated flow measures in the arteria mesenterica superior  and vena portae compared to the high change in flow after glucose consumption makes 2D PC-MRI measures of flow changes in these vessels a feasible diagnostic test.

Keywords: Vessels, Vessels

Motivation: The blood flow of carotid artory can be assessed by the standard 2D PC MRI, as well as the advanced 4D Flow MRI.

Goal(s): The aim of this study is to test the potential of 4D flow for accuracy of quantification of carotid flow parameters compared to the reference standards 2D PC MRI in patients.

Approach: 4D Flow MRI and 2D PC MRI were performed in patients with carotid artery stenosis. Quantitative hemodynamics of carotid arteries were measured in 2D PC and 4D Flow MRI. 

Results: 4D Flow MRI and 2D PC MRI had a good consistency in the evaluation of carotid hemodynamics.
 

Impact: This study found that 4D Flow MRI and 2D PC MRI had a good consistency in the evaluation of carotid hemodynamics in patients with mild to moderate carotid artery stenosis.

Keywords: Vessels, Heart, NMR spectroscopy

Motivation: Heart valve disease (HVD) is a complex condition with a poorly known pathogenesis. 

Goal(s): NMR-based serum metabolomics of HVD patients (aortic, mitral valve, and double valve replacement) and healthy controls to identify potential biomarkers for HVD.

Approach: Proton NMR spectroscopy 

Results: The results obtained from PLS-DA and VIP score plots of metabolites in serum showed a separation between patients with HVD and HC. 

Impact: To understanding the potential metabolic alteration such as BCAA, and fatty acids, amino acids, and carbohydrate metabolism associated with inflammation, oxidative stress, and tissue degradation of HVD.

Keywords: Vessels, Low-Field MRI, Magnetic Resonance Angiography

Motivation: The recent resurgence of ultra-low-field MRI (i.e., below 0.1 T) is showing great promise for future clinical applications due to its low cost, portability, and accessibility, potentially advancing neck MRA for evaluating and diagnosing carotid diseases in point-of-care scenarios and low/mid-income countries.

Goal(s): To explore the neck MRA using TOF technique at 0.05 Tesla.

Approach: Flow-compensated 2D GRE sequences with and without flow saturation for multi-slice neck scans.

Results: Carotid arteries/bifurcations and jugular veins can be visualized with strong vessel-to-background contrast. We envision that usable and quality neck MRA can be potentially achieved at ULF with further sequence and/or post-processing optimization.

Impact: Ultra-low-field (ULF) neck MRA can potentially advance the evaluation of carotid stenosis and occlusion, as well as the diagnosis of stroke and aneurysms, in point-of-care scenarios and low/mid-income countries.

Keywords: Kidney, Perfusion

Motivation: Noninvasive assessment of renal function is necessary in transplanted renal artery stenosis (TRAS), which significantly impacts graft function and prognosis.

Goal(s): The purpose was to evaluate renal function in patients with TRAS using ASL-MRI and IVIM-MRI.

Approach: We used ASL-MRI and IVIM-MRI to evaluate renal blood flow (RBF), D, D^*, and f in TRAS, and analyzed their correlation with eGFR.

Results: Renal allograft in the stenosis group displayed notably lower RBF and f, both of which were positively associated with eGFR. This research highlights the importance of noninvasive techniques like ASL-MRI and IVIM-MRI in the clinical management of TRAS.

Impact: This study demonstrates that TRAS reduces renal perfusion, thereby affecting transplanted kidney function. ASL-MRI and IVIM-MRI can indirectly and noninvasive reflect renal function impacted by TRAS, providing valuable information for treatment decisions and active monitoring.

Keywords: Vessels, Blood vessels

Motivation: The introduction of ultra-high field  5 tesla (T) system provides brand-new opportunities in whole-body MR that can potentially be applied in peripheral MR angiography (MRA).

Goal(s): This study performed two-dimensional (2D) time-of-flight (TOF) MRA of the lower body in ten healthy volunteers for both 3T  and 5T systems. 

Approach: MRA with high spatial resolutions (true voxel sizes, 1$$$\times$$$1.25$$$\times$$$2) from different field strengths were evaluated quantitively and qualitatively.

Results:  2D TOF MRA at 5 T is capable of providing superior vessel delineation and image quality (in both quantitative and subjective assessment) to 3 T.

Impact: This comparative study demonstrated the superiority of  5T to 3T in TOF MRA for pelvis and lower extremities. 5T TOF MRA provides a possible alternative for the clinical assessment of peripheral  arteries.

Keywords: Vessels, Vessels, velocity; high-field MR

Motivation: Unenhanced MRA on feet has always been challenging due to slow blood flow. The ultra-high field strength MR systems have been proved to offer improved visualization of distal small vessels.

Goal(s): We aim to assess the visualization of foot vessels using three-dimensional phase contrast MRA (3D-PC-MRA) at 5T field-strength. 

Approach: Participants were prospectively recruited and underwent 5T 3D-PC-MRA on feet with and without warm water immersion. 

Results: Immersion of feet in warm water significantly improves visualization of distal small branches, and increases the average velocity of blood flow by 40%, resulting in the visualized enhancement in blood signal.

Impact: 5T 3D phase-contrast MRA is effective in visualizing lower-extremity vasculatures and small branches, and its visualization can be significantly improved by immersing feet in warm water.

Keywords: Vessels, Blood vessels

Motivation: Inflow-based NCE MRA techniques have limited capability of background and venous suppression at the high field strength.

Goal(s): This study described a new arterial spin labeling (ASL)-based method for lower limb MR angiography (MRA) called FINE (Flow-Inversion Non-Enhanced).

Approach: The performance of FINE was evaluated on ten healthy volunteers and compared with 2D TOF MRA on 3T. 

Results: 2D FINE technique provides superior suppression of background and venous signal with reduced acquisition time than that of 2D TOF.

Impact: The results of this study demonstrate the feasibility of FINE MRA of the lower limbs at 3T.

Keywords: Vessels, Velocity & Flow, iliac venous compression

Motivation: Hemodynamic changes are important for evaluating Iliac venous compression syndrome.  CFD simulation can obtain individualized and quantitative hemodynamic information that traditional imaging methods cannot obtain.

Goal(s): Qbtain hemodynamic parameters through the establishment of patient individualized vascular model and CFD simulation. By observing hemodynamic parameters, the changes in blood flow caused by iliac venous compression can be more accurately evaluated.

Approach: The 3D model is constructed based on the MRA images.  After CFD simulation,  changes of flow dynamics parameters observed due to the influence of iliac venous compression.
 

Results: The CFD simulation shows that iliac venous compression can cause significant changes in hemodynamics

Impact: Hemodynamic changes are the pathological basis of iliac venous compression. Accurate diagnosis of blood flow changes is helpful to guide the surgical treatment of iliac venous compression and provide powerful help for clinical decision-making.

Keywords: Kidney, Kidney

Motivation: Previous studies have demonstrated a correlation between kidney fibrosis and corticomedullary difference in apparent diffusion coefficient (ADC). However, separately measuring ADC in cortex and medulla is challenging due to the low contrast between the tissues. 

Goal(s): To facilitate measurement of corticomedullary ADC. 

Approach: T1-weighted, distortion-matched echo planar imaging (EPI) with high corticomedullary contrast were acquired in addition to diffusion weighted EPI. Regions-of-interest were performed in the T1-weighted images and propagated to the distortion-matched ADC maps to obtain measurements. 

Results: Corticomedullary ADC differences were obtained in four datasets from two healthy volunteers with values within the range of previously published values. 

Impact: T1-weighted, distortion-matched EPI with high corticomedullary contrast greatly facilitates measurements of cortex and medulla in diffusion weighted EPI.  

Keywords: Kidney, Kidney, ASL, DWI, ADC, Perfusion, Age, BMI

Motivation: The demand for accurate and non-intrusive renal function evaluation methods.

Goal(s): To discern how age and BMI affect:

• Renal perfusion measured with ASL (Arterial spin labeling).
• Renal diffusion measured with Apparent diffusion coefficient (ADC) from DWI (Diffusion-weighted images).

Approach:

1. Recruit and scan healthy volunteers.
2. Create a database with the results.
3. Apply statistics:

• Evaluating correlations (Spearman coefficient).
• Evaluating differences between groups (Mann-Whitney U test).

Results:  
ASL:

• Negative significant age-related perfusion and significant differences between age groups.
• Negative significant correlations of BMI with perfusion in inner regions of the kidneys.

• No significant correlation with age.
• Negative significant correlations of BMI with ADC maps.

Impact: These findings provide insights for the MRI community, enhancing tailored renal understanding and diagnostic precision. Personalized approaches, using age and BMI, have the potential to enhance patient outcomes. This study encourages focused research, promoting personalized medicine and refining renal imaging.

Keywords: Kidney, Quantitative Imaging, type 2 diabetes mellitus; IDEAL-IQ; proton-density fat fraction; diabetic kidney disease

Motivation: Renal parenchymal fat deposits play a crucial role in the development of diabetic kidney disease (DKD). Noninvasive measurement of renal parenchymal fat deposits using functional MRI provides valuable insights into the pathogenesis of DKD.

Goal(s): Exploring the reproducibility of IDEAL-IQ imaging in quantifying renal lipid deposition and to investigate the differences observed in DKD patients.

Approach: A total of 26 healthy participants underwent two IDEAL-IQ scans without repositioning and 96 type 2 diabetes mellitus (T2DM) patients underwent a single IDEAL-IQ scan.

Results: IDEAL-IQ imaging is a reproducible technique for noninvasively quantifying renal lipid deposition. Furthermore, the technique shows promising performance in staging DKD.

Impact: This study highlights the potential benefits of IDEAL-IQ imaging in evaluating renal lipid deposition in DKD patients. It contributes to a better understanding of the pathogenesis and progression of DKD, to improved diagnostic and management strategies for T2DM patients.

Keywords: Kidney, Genetic Diseases, ARPKD, Pediatric Genetic Disease

Motivation: There are no clinically available therapies for ARPKD.

Goal(s): We evaluated the ability of T₁ and T₂ from MR Fingerprinting (MRF) to assess kidney cystic burden and Arterial Spin Labeling (ASL) to assess kidney perfusion to detect and stage ARPKD kidney disease.

Approach: 12 ARPKD patients and 10 healthy adult volunteers were scanned on a Siemens 3T with kidney MRF and ASL MRI methods to generate kidney cortical perfusion maps.

Results: Significant increases in kidney T₁ and T₂, and reduced perfusion were observed between ARPKD patients and healthy volunteers (p<0.001) and between ARPKD patients with early and mild-to-moderate CKD based on eGFR (p<0.03).

Impact: The multi-modal MRI biomarkers in combination evaluated were able to distinctly stratify all three cohorts, including the two ARPKD patient cohorts, demonstrating the utility of a multi-modal MRI approach during future clinical trials aimed at limiting ARPKD kidney disease progression.

Keywords: Kidney, Quantitative Susceptibility mapping, Autosomal polycystic kidney disease, ADPKD, complex cysts, hemorrhage, renal calcifications

Motivation: Current MRI-based approaches for assessment of the complications related to the ADPKD (hemorrhage and calcifications) suffer from low specificity due to the complex and nonlinear dependence of T1/T2 relaxation times on tissue composition.

Goal(s): The aim of this study is to assess QSM as an enrichment biomarker suited for unambiguous differentiation of various complex ADPKD cysts.

Approach: We perform a cross-sectional study in ADPKD subjects categorizing complex cysts based on their appearance on QSM and assessing their prevalence in patient population.

Results: The results of our imaging study demonstrate that QSM can provide complimentary characterization of cyst composition and visualize calcifications within kidneys.

Impact: Our results indicate that QSM can identify unique susceptibility properties of complex cysts unattainable with traditional imaging approaches, which may serve as an enrichment biomarker for ADPKD progression and the development of cyst complications.

Keywords: Kidney, Kidney, Multi-parameter magnetic resonance imaging; Clear cell likelihood score; Clear cell renal cell carcinoma; Pseudocapsule

Motivation: Clear cell likelihood score version 2.0 (ccLS v2.0) is not yet able to predict malignancy in small renal masses (SRMs). Pseudocapsule may provide added value with ccLS v2.0

Goal(s): To develop a modified clear cell likelihood score based on pseudocapsule (m-ccLS) for predicting malignancy in SRMs

Approach: Receiver operating characteristic curve (ROC), net reclassification index (NRI), and integrated discrimination improvement (IDI) were used to compare diagnostic value of m-ccLS and ccLS v2.0

Results: Area under curve (AUC), NRI and IDI of m-ccLS were superior to those of ccLS v2.0 for the diagnosis of malignancy. The likelihood of malignancy increased with higher m-ccLS scores

Impact: M-ccLS achieved predict malignancy of small renal masses (SRMs). M-ccLS may be a valuable tool for expanding the clinical application of this scoring system and contributing to its further promotion and dissemination

Keywords: Kidney, Kidney

Motivation: To observe the renal oxygenation in patients with primary aldosteronism (PA).

Goal(s): To explore the renal oxygenation in patients with PA by blood oxygenation level-dependent magnetic resonance imaging (BOLD-MRI) compared with healthy controls (HCs).

Approach: A total of 40 participants were included and underwent renal BOLD-MRI. The correlation between renal BOLD parameters and clinical indicators was analyzed by Pearson correlation analysis or Spearman correlation analysis. A ROC curve was used to distinguish the PA patients and HCs.

Results: The cortical R2* of the PA patients was higher than that of the HCs, suggesting that the cortices of PA patients were relative hypoxia.

Impact: Our results suggested that BOLD-MRI could detect the oxygenation level of the renal cortex and medulla of PA patients and may have the potential to noninvasively assess renal status.

Keywords: Kidney, Cancer, Hyperpolarised MRI, renal cancer, VERDICT

Motivation: Accurate differentiation of renal tumour subtype and grade is not currently possible using standard of care imaging.

Goal(s): To use combined functional and microstructural MRI in the form of diffusion weighted imaging with VERDICT, proton density fat fraction and hyperpolarised [1-13C]pyruvate to detect the different histological and metabolic features of different renal tumours.
Two patients with histologically proven renal tumours (grade 2 clear cell and grade 3 papillary) underwent MRI imaging.

Approach: Two patients with histologically proven renal tumours (grade 2 clear cell and grade 3 papillary) underwent MRI imaging.

Results: Combined function and microstructural MRI differentiated tumour types and normal kidney.

Impact: This study demonstrates the first combined use of VERDICT, PDFF and hyperpolarised [1-13C]pyruvate. The differentiation of renal tumours has proven difficult on imaging and this combination is a promising approach to this significant clinical problem.

Keywords: Urogenital, Kidney

Motivation: In renal tumors, it is often difficult to differentiate between benign and malignant tumors, which could reduce unnecessary biopsies and surgeries.

Goal(s): To differentiate between angiomyolipoma (AML) and renal cell carcinoma (RCC).

Approach:  Imaging with two types of diffusion-weighted images (DWI) with different Echo times (TE) and comparing T2 signals in AML and RCC at DWI (b=0) and DWI (b=1200).

Results: T2 signals at high diffusion restriction DWI (b=1200) were significantly lower in AML compared to RCC.

Impact:  There is potential to preoperatively differentiate AML non-invasively, which previously due to the difficulty in differentiation, led to invasive diagnostic methods such as biopsies and unnecessary surgeries.

Keywords: Kidney, Kidney

Motivation: As the current diagnostic tools are insensitive to early kidney damage in radiation nephropathy, there is a clinical need for improved biomarkers that can be used to noninvasively assess tubulointerstitial changes in RN.

Goal(s): To verify whether MRI-based T2 mapping can detect microstructural changes in renal parenchyma resulting from radiation-induced kidney damage.

Approach: We performed T2 mapping in two mouse models of radiation nephropathy, one involving external beam irradiation and the other utilizing internal irradiation with α-particle-emitting actinium (²²⁵Ac) radiolabeled antibody.

Results: Increased T2 values were found in the cortex and outer medulla of the treated mice compared to the healthy controls.

Impact: MRI-based T2 values could serve as a quantitative biomarker for detecting microstructural changes specific to EBRT and αRPT.

Keywords: Kidney, Tumor, Carcinoma, Renal Cell; Lymphatic Metastasis; Nephrectomy; Magnetic resonance imaging; Prognosis.

Motivation: The prognostic property of regional lymph node metastasis (RLNM) has been widely recognized, but the diagnostic workup has stagnated for renal cell carcinoma (RCC).

Goal(s): This study aimed to assess the diagnostic performance of MRI-based Node Reporting and Data System (Node-RADS) for RLNM and to explore its prognostic impact on patients with RCC.

Approach: A single-center retrospective comparative study.

Results: MRI-based Node-RADS presented better diagnostic performance for RLNM than the size criteria and previous clinical models (AUC, 0.91 vs 0.79–0.85; all P<.05), and exhibited a substantial prognostic value for RCCs regarding progress-free survival and overall survival (both P<.001).

Impact: Node-RADS, a concept that combines size, texture, margin, and shape, is a promising approach for lymph node metastasis in RCCs, which may contribute to improving clinical node staging and guiding clinical decision making.

Keywords: Kidney, Kidney

Motivation: 4D flow MRI provides volumetric time-resolved blood flow measurements in short scan times. Nevertheless, 4D Flow MRI techniques have not been clinically applied to abdominal neoplasms invading into the vasculature, altering blood flow and posing unique surgical problems. 

Goal(s): Describe the clinical implementation of 4D Flow MRI for treatment planning of RCC patients with venous tumor thrombus undergoing nephrectomy and thrombectomy. 

Approach: Our institution has established a 4D flow MRI workflow for blood flow assessment based on multidisciplinary collaboration and several other factors. 

Results: Clinical 4D flow for treatment planning of RCC patients has been successfully implemented at our institution.

Impact: 4D flow MRI allows for comprehensive non-invasive assessment of the abdominal circulation in the clinical setting. The methodology presented here has provided unvaluable input to the care team of patients with complicated cases of advanced RCC during treatment planning. 

Keywords: Pelvis, Body

Motivation: Setting up a noninvasive and accurate method to predict tumor grade preoperatively is urgently needed. However, the comparison between the potential of the bpMRI-based radiomics model and that of traditional MRI model in estimating the grade of BCa have not yet been investigated.

Goal(s): The purpose of this study was to construct a radiomics model based on bp-MRI for the preoperative prediction of BCa grade and compare it with traditional MRI model.

Approach:  A logistic regression  classifier was used to develop the radiomics signatures. 

Results: Radiomics model was outperformed the traditional MRI model in distinguishing high-grade and low-grade bladder cancer. 

Impact: The bp-MRI radiomics model was useful in distinguishing high-grade and low-grade bladder cancer. Radiomics model was outperformed the traditional MRI model.

Keywords: Pelvis, Bladder, cancer

Motivation: NacVI-RADS based on mpMRI, was exclusively constructed to evaluate the response to systemic therapy and provided a reference for further treatment for patients with muscle-invasive bladder cancer (MIBC).

Goal(s): To examine the feasibility of the nacVI-RADS criteria in driving the therapeutic decision. 

Approach: Patients received bladder sparing treatment were retrospectively retrieved. Pre-treatment and follow-up MRI were independently reviewed by two readers using the nacVI-RADS. We observed the pathological results from salvage RC and oncological outcomes for patients continuing systemic treatment with different nacVI-RADS category.

Results: We confirmed the consistency between the nacVI-RADS score and outcomes to initial treatment both pathologically and oncologically.

Impact: We preliminarily verified the feasibility of mpMRI in determining continuing or quitting bladder-sparing strategy after initial systemic therapy for MIBC. Besides, we modified nacVI-RADS, which showed a significantly improved performance in predicting the oncological outcomes after undergoing bladder sparing strategy.

Keywords: Urogenital, Bladder, Uro-Dynamic MRI

Motivation: Current standards for assessing the lower urinary tract (LUT) provide limited anatomical information. Uro-Dynamic MRI proves to be a valuable non-invasive tool for LUT biomechanics analysis. Bladder shape has been studied in static imaging but not in dynamic imaging.

Goal(s): Build a comprehensive, non-invasive framework to study bladder biomechanics in healthy and diseased subjects.

Approach: Uro-Dynamic MRI was implemented and used in five healthy and five BPH subjects. Novel MRI-derived bladder shape metrics were developed and quantified in all subjects.

Results: We observe quantifiable differences on correlation coefficients of flowrates and calculated bladder shape metrics between healthy and patients with benign prostatic hyperplasia.

Impact: Uro-Dynamic MRI allows biomechanical and shape analysis of the lower urinary tract(LUT), allowing comparisons between healthy and diseased subjects. Higher correlation values with flowrates observed on healthy subjects. Coupled Bladder biomechanical and shape analysis allows potential characterization of LUT disease. 

Keywords: Urogenital, MR Fingerprinting

Motivation: Azoospermia care often requires performing microdissection procedures for sperm extraction that are unsuccessful in 50% of men. 

Goal(s): Investigate the feasibility of a combined MRF and diffusion mapping protocol of the testicles, as well as quantify the normal ADC, T1 and T2 values of the left and right testicles.

Approach: Regions of interest were annotated on ADC and T1 maps, these were copied to T2 maps.

Results: Mean ADC, axial T1 and T2 values were similar between left and right testicles. Mean coronal T1 and T2 values of the left testicles were higher than those of the right testicles.

Impact: The acquisition of a dedicated protocol for combined MRF and diffusion mapping of the testicles is feasible. This work paves the way for prospective studies investigating non-invasive characterization of the testicles in patients with obstructive and non-obstructive azoospermia.

Keywords: Lung, Low-Field MRI

Motivation: The image quality generated using respiratory triggered sequences on low-field scanners is sometimes degraded, and it is currently not well known what causes this. This degradation can lead to image misinterpretation.

Goal(s): Our goal was to determine possible predictors of image quality degradation in low-field lung MRI.

Approach: Six radiologists graded anatomic 0.55T MRI images, and then analysis of patient clinical history, demographics, and respiratory navigation was conducted to determine any patterns.

Results: We found that clinical conditions including fibrotic interstitial lung disease and pulmonary artery pathologies, as well as descriptors such as increased body mass index can predict image quality degradation.

Impact: Our observation of degradative predictors serves as the foundation for research into altering of 0.55T MRI parameters to limit the degree of degradation, so that at-risk patients can still be scanned on these low-field machines with optimal image quality.

Keywords: Lung, Lung, Low-field

Motivation: Sarcoidosis is a systemic inflammatory disease in particular affecting lung tissue, thus there is a need for non-invasive and ionizing radiation free technique to assess regional lung function.

Goal(s): To examine correlations between functional lung MRI and pulmonary lung function tests in patients with sarcoidosis.

Approach: Lung ventilation and perfusion was assessed using matrix pencil decomposition MRI at a low-field 0.55T MR-scanner in sarcoidosis patients and a control group of healthy volunteers. Conventional lung function tests in patients were performed with spirometry and body plethysmography.

Results: Strong correlations between the functional lung MRI and the metrics from conventional pulmonary function tests were observed.

Impact: To our knowledge, this is the first study focused on the evaluation of lung function using MRI in sarcoidosis patients. Our results support the use of MRI as a non-invasive diagnostic tool to assess lung function in patients with sarcoidosis. 

Keywords: Lung, Low-Field MRI

Motivation: The current clinical standard for screening lung imaging is chest CT, which is associated with radiation exposure and only provides static, anatomical information of the lung and concurrently imaged heart.

Goal(s): We are exploring an alternative method for lung pathology screening.

Approach: Using a 0.55T MRI scanner and the proposed screening Lung MRI protocol, we conducted lung MRI scans on 10 healthy volunteers.

Results: Initial assessments demonstrate concurrent evaluation of the anatomy, motion, and tissue characteristics of the lung and heart in around 25 minutes.

Impact: We propose a screening Lung MRI protocol as a potential alternative imaging option in screening as well as follow up imaging in particular conditions, with the benefit of eliminating radiation dose and additional respiratory and cardiac motion and tissue information 

Keywords: Lung, Low-Field MRI, Quantitative parametric mapping, Upright MRI, Gravity on Lung

Motivation: Quantitative lung parametric mapping can characterise morphometric and functional changes in pulmonary disorders. Higher field lung-MRIs suffer from field inhomogeneity, and supine MRI does not replicate physiology during daily tasks and is not suitable for some lung patients.

Goal(s): Use low-field, upright-MR, quantify T1 and T2* of different lung regions and investigate how gravity impacts these parameters while seated. 

Approach: A 0.5T ASG MROpen scanner was used to acquire breath-hold images using multi-TE GE (T2*) and variable flip angle method (T1); linear regression extracted the relaxation times.

Results: Although supine position showed similar T1 and T2*, gravity incurred a cranial-caudal gradient while seated.  

Impact: Our low-field, upright-MR parametric mapping mitigates the limitations of higher-field lung-MRI and explores how relaxations change with gravity. Using the proposed methods, clinicians can characterise pathologies like COPD as well as get crucial functional information of lungs during diurnal postures.

Keywords: Lung, Lung

Motivation: The T₂^* of inhaled perfluoropropane gas is determined by lung microstructure due to its dependence on the magnetic susceptibility of airway and tissue components, granting the potential to report on lung pathophysiology.

Goal(s): To implement a robust measurement of the T₂^* of inhaled perfluoropropane, to lead to early detection of structural alterations from lung pathologies.

Approach: We’ve acquired spatially localized ¹⁹F-MRS T₂^* measurements of perfluoropropane in healthy volunteers at different inhalation depths.

Results: We observed a 12% variation in T₂^* between maximum and minimum inhalation, demonstrating T₂^*’s sensitivity to physiological change, and potential for early detection of microstructural change associated with lung disease.

Impact: A spatially localized measurement of perfluoropropane T₂^* has sensitivity to change in lung microstructure due to physiological change. These data show the potential of ¹⁹F-MRI to report on pathology-driven microstructural change, which may allow for early detection of lung disease.

Keywords: Lung, Quantitative Imaging, Registration

Motivation: To develop ¹H MRI methods to study dynamical lung expansion as a marker of lung function. 

Goal(s): To collect free breathing ¹H MRI over the respiratory cycle and investigate the feasibility of using the Jacobian determinant of the registered images for dynamic functional assessment of local expansion, instead of the signal intensity as is used in FD/PREFUL analyses. 

Approach: Voxel-wise lung ventilation (VOLVE) analysis using the timecourse of deformation based Jacobian determinant to assess the ventilation correlation coefficient.

Results: Significant differences in the Jacobian-derived correlation coefficient between healthy and COPD groups indicating differences in local expansion which may provide a lung functional marker.

Impact: The Jacobian determinant obtained from registering free breathing ¹H lung MRI images provides a metric of local expansion related to respiratory phase, which is sensitive to lung disease. This motivates future work to combine signal intensity-based and deformation-based functional assessments.

Keywords: Lung, Lung, Spirometry, biomarkers, biomechanical

Motivation: New mechanical biomarkers to characterize lung pathophysiology using 3D MR spirometry.

Goal(s): To investigate the dynamics of lung elongations along the three anatomical directions when the lungs are constrained during breathing.

Approach: 3D MR spirometry was performed in 25 healthy volunteers spontaneously breathing and in a healthy volunteer for three types of breathing (spontaneous, thoracic, diaphragmatic). 

Results: The main respiratory driving force is produced by the diaphragm as it is assessed here with a dominant superior-inferior normal strain in basal pulmonary regions.  In spontaneous breathing, it is supplemented mainly by the anterior-posterior normal strain in the apical regions. 

Impact: Dynamic normal strains are original mechanical biomarkers that provide new insight on the regional anisotropic behaviour of the lungs.

Keywords: Lung, Lung, sms, functional, pulmonary

Motivation: Pulmonary functional imaging is critical for diagnosing lung diseases. However, sequential acquisition of multiple slices hinder the investigation of concurrent breathing dynamics while prolonging the overall the acquisition time.

Goal(s): Our goal is to investigate the use of simultaneous multi-slice (SMS) imaging as an alternative approach for accelerating dynamic acquisitions for functional lung imaging.

Approach: We obtained dynamic images using bSSFP and GRE acquisitions at 1.5T, from two healthy volunteers. Afterwards, registered images were analyzed using dynamic mode decomposition to generate pulmonary ventilation and perfusion maps.

Results: Functional maps were obtained using both pulse sequences with SMS in both sagittal and coronal views.

Impact: Dynamic lung imaging often requires multiple slices for volumetric coverage, which can be time-consuming. Simultaneous multi-slice (SMS) technique enables the acquisition of multiple slices at the same time, thus enabling the observation of concurrent breathing dynamics in an efficient manner.

Keywords: Lung, COVID-19

Motivation: Perfusion disturbances can be observed up to a year after acute COVID-19 infection.

Goal(s): Evaluate the relationship between pulmonary perfusion and sex, age and disease severity in patients hospitalised due to COVID-19.

Approach: 198 patients hospitalised due to COVID-19 were recruited from 13 centres as part of the C-MORE study. 3T dynamic contrast enhanced lung perfusion imaging was acquired at follow-up. 

Results: Men previously hospitalised with severe COVID-19 showed increased pulmonary mean transit time (MTT) and more heterogenous pulmonary MTT at follow up compared to men with less severe disease. Disease severity was not associated with increased MTT at follow up in women. 

Impact: Dynamic contrast enhanced lung perfusion imaging can identify prolonged pulmonary transit times in patients hospitalised due to COVID-19 and demonstrates that at patient follow-up pulmonary perfusion depends on patient sex, age and, in male patients, acute disease severity. 

Keywords: Lung, COVID-19

Motivation: It is unclear the extent to which abnormal lung ventilation is present in long COVID subjects without prior respiratory diseases.

Goal(s): Evaluate ¹²⁹Xe lung ventilation imaging in a cohort without prior respiratory disease, consisting of patients with long COVID (with and without dyspnea) and controls.

Approach: 60 patients with long COVID (53 with dyspnea, 7 without dyspnea) and 20 controls underwent successful ventilation imaging and were included in analysis. 

Results: ¹²⁹Xe ventilation imaging metrics did not find significant differences between controls and patients with long COVID, however a subset of long COVID patients with dyspnea had lung ventilation defects despite normal PFTs. 

Impact: Impact (40 words): The majority of patients with long COVID have normal 129Xe lung ventilation imaging. 129Xe ventilation imaging may be able to identify candidates with long COVID who may be candidates for treatments targeted at airways disease.

Keywords: Visualization, Lung

Motivation: The Pulmonary perfusion defects were unknown in post-acute COVID-19 syndrome (PACS). 

Goal(s): To investigate the utility of phase-resolved functional lung (PREFUL) MRI in detecting pulmonary perfusion disturbances inPACS.

Approach: Participants diagnosed with PACS were recruited, along with healthy (NCT05933317). The quantified parameter QDP derived from PREFUL MRI represents abnormal pulmonary blood flow.

Results: 44 participants with PACS, and 43 healthy were assessed. QDP significantly exceeded  healthy controls in PACS (39.81% ± 15.0% vs 8.2% ± 3.3%) and was notably higher in inpatients (46.8% ± 17.0% vs 34.5% ± 10.8%). Moreover, males exhibited higher QDP than females (43.9% ± 16.8% vs 34.4% ± 10.2%).

Impact: PREFUL MRI demonstrates notable perfusion defects in participants with PACS.

Keywords: Lung, Lung

Motivation: In ¹⁹F MR pulmonary ventilation imaging, variations in inspiratory gas volumes can compromise the evaluation of dynamic ventilation parameters. 

Goal(s): To account for these variations, a correction of the inhaled volumes (CIV) can be applied during post-processing. 

Approach: This study examined the repeatability of dynamic ventilation parameters and the correlation with spirometric lung function testing with and without CIV in 24 patients with chronic obstructive pulmonary disease. 

Results: Using CIV increases the correlation of all assessed ventilation parameters with spirometry as well as their repeatability in terms of intraclass correlation coefficient and coefficient of variation between different scans.

Impact: The increased repeatability and stronger correlation with spirometry suggest that the implementation of CIV can improve the evaluation of the pulmonary gas wash-in process retrospectively, without requiring additional MR scans or changes in the experimental procedure.

Keywords: Lung, Hyperpolarized MR (Gas)

Motivation: Study on the effects of e-cigarette use is needed to understand its damaging effects on the pulmonary system. 

Goal(s): Anticipating a need for multi-center clinical trials in the future this study, performed for the first time, studied the repeatability of Xe-129 gas-exchange MRI of the same subjects at two centers. 

Approach: Same subjects were imaged at University of Virginia and Duke University to directly assess technique harmonization and repeatability of Xe-129 metrics.

Results: Note the statistically insignificant differences for each subject, for ventilation and gas-exchange, with signal-to-noise ratio for ventilation scans being the only statistically significant parameter (p=0.027) to differ between the sites. 

Impact: Harmonization of Xe-129 MRI gas-exchange and ventilation imaging methodology among the two sites was successfully achieved, opening the way for a large clinical trial with these two institutions.

Keywords: Lung, Lung

Motivation: Lung T₁(TE) quantification using 2D UTE was demonstrated as an interesting tool but needs expansion to 3D UTE for better comparability and coverage. However, streaking artefacts originating from the edges of the Field of View are particularly problematic in Lung T₁(TE) maps.

Goal(s): To reduce streakings in T₁(TE) maps caused by B₀ inhomogeneities.

Approach: A Shinnar LeRoux (SLR) minimum phase pulse was used to limit excitation to a 320mm slab in the Multi Ultra-short TE Look-Locker Inversion Recovery sequence.

Results: T₁(TE) maps produced using sagittal SLR excitation showed less streakings than using transverse SLR excitation and rectangular pulses, but still had residual streaking.

Impact: Inhomogeneity streakings in 3D UTE lung T₁(TE) maps were greatly reduced by employing a SLR pulse. With additional efforts during reconstruction, it may be possible to remove the remaining artefacts and quickly acquire parameter maps of the entire lungs.

Keywords: Lung, Lung, UTE；fractional ventilation；pulmonary function tests；

Motivation: This study aimed to assess the feasibility of using single breath-hold UTE MRI to quantify pulmonary function and its spatial uniformity in patients with obstructive lung disease.

Goal(s): Comparison of FV in patients with different respiratory stages and correlation with PFTs.

Approach: FV map was obtained from UTE MRI, and IQR of FV was calculated. Group differences of UTE parameters were compared, and correlation between UTE MRI with PFT parameters was assessed.

Results: We found significant differences in whole lung FV and left lung FV among groups, with a positive correlation between FV and PFT parameters such as FEV1 and MMEF.

Impact: This study demonstrates the potential of UTE MRI for assessing pulmonary function in obstructive lung disease patients. By providing regional functional information, UTE MRI might be a useful tool in lung disease management.

Keywords: Lung, Spectroscopy, Metabolomic imaging, acute respiratory distress syndrome, nuclear magnetic resonance, metabolomics, metabolites

Motivation: ARDS currently has unacceptable high mortality and long-term complications, which underscores the urgency of improving our understanding and management of ARDS.

Goal(s): To establish pathology-guided serum metabolomic profiles for ARDS patients by comparing them with profiles from patients without ARDS.

Approach: We measured ARDS serum using high-resolution magic angle spinning (HRMAS) magnetic resonance spectroscopy (MRS) to establish serum metabolomic profiles for ICU-patients with and without ARDS following various clinical outcomes.

Results: Serum specimens measured by HRMAS MRS enables the predictions of ARDS patient outcome in ICU.

Impact: Our initial results highlight the feasibility of HRMAS MRS in investigating ARDS metabolomic mechanisms, which may lay the basis for future diagnostic and therapeutic research, offering promising prospects for innovation in ARDS management.

Keywords: Prostate, Data Analysis, Biopsy Targeting, Lesion Identification, Risk Categorization

Motivation: The accurate localization and assessment of aggressiveness in patients with prostate cancer is key to appropriate treatment, especially radiation therapy (RT) planning.

Goal(s): To evaluate the performance of a Habitat Risk Scoring (HRS) system in MRI/Ultrasound-fused biopsy of prostate cancer at the time of the fiducial marker placement prior to RT.

Approach: The yield of significant prostate cancer biopsy findings under HRS guidance was compared with alternative standard techniques.

Results: Patients from the Miami BLaStM trial were analyzed with and without HRS guidance. The biopsies obtained through HRS guidance yielded more clinically significant cancer.

Impact: The implementation of the Habitat Risk Scoring (HRS) system in transperineal platform for MRI-US biopsies significantly improved the delineation of aggressive cancer. These volumes are integral to the safe delivery of focal escalated radiation doses.

Keywords: Prostate, Cancer

Motivation: If reliable preoperative risk factors to predict Gleason score (GS) upgrading after radical prostatectomy (RP) are identified, such could be helpful to reduce the risk of misclassification of PCa patients.

Goal(s): To investigate the relationship between Prostate Imaging Reporting and Data System version 2.1 (PI-RADS v2.1) and GS change after RP.

Approach: Multivariate analyses were performed to analyse the factors influencing GS change after RP.

Results: Multivariate regression analysis showed positive biopsy cores of ≥ 4, biopsy Gleason score of <7 and PI-RADS v2.1 score of 4–5 were independent predictors of GS upgrading after RP (all P < 0.05). 

Impact: Combining the number of positive biopsy cores, biopsy Gleason score and PI-RADS v2.1 score could significantly improve the diagnostic efficiency for Gleason score upgrading after radical prostatectomy.

Keywords: Prostate, Prostate

Motivation: Introduction of Extended Grid Sampling (EGS) to overcome the limitations of Hybrid Multidimensional MRI (HM-MRI) in prostate cancer (PCa) detection.

Goal(s): Our primary goal is to assess the effectiveness of EGS in improving the accuracy of PCa detection and lesion extension using HM-MRI.

Approach: Integrate EGS data with standard HM-MRI, utilizing biexponential fits for short and long T2 component estimation, followed by joint analysis, and risk map generation to enhance the precision of prostate cancer detection and characterization.

Results: EGS integrated with HM-MRI can provide more accurate delineation of prostate tissue compartments, notably improving the detection of prostate cancer lesions.

Impact: By enhancing prostate cancer (PCa) detection accuracy with Extended Grid Sampling (EGS) integrated into Hybrid Multidimensional MRI (HM-MRI), we empower clinicians to make more precise diagnoses and treatment decisions, directly benefiting patients. 

Keywords: Prostate, Prostate

Motivation: Preoperative prediction of the risk of positive surgical margin (PSM) is important for optimal treatment decision-making in patients with prostate cancer.

Goal(s): To develop preoperative nomograms using risk factors based on clinicopathological and MRI for predicting the risk of PSM after radical prostatectomy.

Approach: Preoperative clinicopathological factors and MRI-based features were recorded for analysis. The presence or absence of PSM (oPSM) at pathology and the multifocality of PSM (mPSM) were evaluated.

Results: The nomogram for oPSM reached an AUC of 0.717 in development and 0.716 in internal verification. The AUC of the nomogram for mPSM was 0.790 in both development and internal verification.

Impact: The proposed nomograms showed good performance and were feasible in predicting oPSM and mPSM. The evaluation of risk factors and the application of nomograms preoperatively might facilitate individualized management of prostate cancer.

Keywords: Prostate, Screening, PIRADS

Motivation: Prostate cancer is highly incident in Africa. Early screening and detection is recommended to lower this rate. BpMRI and PIRADS are used to detect, stage prostate cancer. The accuracy of PIRADS in an African population hasn’t been determined

Goal(s): Determine the accuracy of PIRADs to screen Prostate cancer in an African population

Approach: We assessed the accuracy of PIRADS alone, PIRADS and PSAD, PIRADS and ADC, PIRADS, PSAD and ADC using the AUC to discriminate a positive histological prostate case

Results: PIRADS had AUC 0.70, combination of PIRADS V2.1 and PSAD had AUC 0.73, combination of PIRADS, PSAD and ADC had AUC 0.72

Impact: PIRADS accurately predicts PCa satisfactorily AUC 70%. It may be used in an African population in combination with clinical information and history. This is because they were some cases graded as PIRADS 2 and yet had a high gleason score.

Keywords: Prostate, Prostate, Prostate Imaging Reporting and Data System, Relaxation time quantitative technique, Synthetic magnetic resonance imaging

Motivation:  It’s essential to explore new imaging methods to improve the diagnostic performance of bp-MRI (T2W+DWI) PI-RADS v2.1 in the absence of DCE.

Goal(s): To evaluate the potential of quantitative relaxometry from synthetic MRI in combination with bp-MRI PI-RADS v2.1 score for differentiating clinically significant prostate cancer.

Approach: T2WI, T2WI fs, DWI and synthetic MRI with magnetic resonance image compilation (MAGiC) imaging in 3T MR

Results:  Integrating T1, T2, PD and ADC with PI-RADS score improves the diagnostic performance for lesions in peripheral zone significantly with increased both sensitivity and specificity, but not significantly for the lesions in transitional zone.

Impact: The introduction of relaxometry from synthetic MRI can help improve the diagnostic efficiency in the peripheral zone when integrated with PI-RADS in the absence of DCE, which avoid the increase of peripheral zone lesions with PI-RADS score of 3.

Keywords: Prostate, Prostate

Motivation: In prostate cancer (PCa), multiparametric MRI (mpMRI) and PSMA-PET aid pre-surgical assessment. This study evaluates parameters linked to the agreement/disagreement of PSMA-PET and mpMRI with histopathology.

Goal(s): To evaluate the concordance between PSMA-PET, mpMRI, and histopathology in PCa lesion identification.

Approach: Patients with PSMA-PET, mpMRI, and histopathology data were analyzed. Imaging lesions were contoured independently. Sensitivity and agreement were assessed. Logistic regression models examined factors affecting concordance.

Results: Among 114 patients, PSMA-PET and mpMRI identified 170 and 138 lesions, respectively. Tumor aggressiveness and size impacted agreement. Higher SUVmax on PSMA-PET and higher ISUP grade and size on pathology were associated with concordance.

Impact: This work improves prostate cancer diagnosis by identifying key factors influencing the agreement between PSMA-PET, mpMRI, and histopathology, offering valuable insights for more precise pre-surgical assessments.

Keywords: Prostate, Prostate, Undersampling, PI-RADS

Motivation: Increasing prostate cancer cases are leading to a rising demand for prostate MRI, which is a time-consuming protocol. Speeding up of this protocol will help relieve the rising pressure on the healthcare system.

Goal(s): To speed up the T2W TSE by undersampling the data, while maintaining the diagnostic outcome. 

Approach: Echo-trains with center-lines farthest from the k-space center are removed, to undersample the data semi-incoherently , followed by a Compressed Sense reconstruction. 

Results: Up to 17% time gain can be achieved while the diagnostic outcome remains unaffected.

Impact: The scan time of T2W TSE can be reduced by selectively removing echo-trains based on their center-line distance to the k-space center, without affecting the diagnostic outcome, defined by the PI-RADS score and qualitative parameter ratings.

Keywords: Prostate, Prostate, prostate cancer, 3D MRF Fingerprinting

Motivation: MRF has shown to have potential to separate cancer from non-cancer in the prostate. Improving resolution and accuracy of tissue property maps while lowering acquisition times could expedite clinical adoption of this technique.

Goal(s): To obtain high-resolution 3D T₁ and T₂ maps in the prostate in a single rapid scan.

Approach: A highly undersampled isotropic 1 mm³ SoS MRF FISP sequence with B₁+ and B₀ correction was developed.

Results: We obtained high-resolution 3D T₁ and T₂ maps of the prostate from a single 6-minute scan and report these values in the normal-appearing prostate from 6 subjects and a PIRADS 5 suspected lesion.

Impact: High-resolution quantitative 3D T₁ and T₂ maps using a single 6-minute scan may enable this technology to be used for detection and characterization of prostate lesions and encourage clinical adoption.

Keywords: Prostate, Prostate, magnetic resonance fingerprinting

Motivation: Prostate MRI alone cannot avoid all unnecessary biopsies in MRI-negative patients. This results in overdiagnosis, added morbidity and overtreatment.

Goal(s): Investigate if MRF-derived T1 and T2 maps alone or in combination with conventional ADC mapping can reduce unnecessary biopsies while maintaining optimal significant prostate cancer detection.

Approach: Regions of interest encompassing the right and left lobes of the peripheral zone were used to compute the mean T1, T2, and ADC values.

Results: With a linear regression of mean T1 and T2 values, 63% of all biopsies could be avoided, at the cost of missing one significant prostate cancer.
 

Impact: The use of MR Fingerprinting in prostate biopsy decision-making pathways could reduce unnecessary biopsies while maintaining optimal detection of significant prostate cancer in MRI-negative patients with clinically indicated biopsies. The prospective validation of these findings is crucial for patient outcomes.

Keywords: Prostate, Quantitative Imaging, Active Surveillance, Prostate Cancer, T2 Mapping

Motivation: Multiparametric MRI as a widespread tool for AS management has limitations of diagnostic dilemma and inconsistency in identifying pathologic reclassification. 

Goal(s): To further investigate the added value of estimated T2 maps generated by deep learning network on AS.

Approach: Retrospectively estimated T2 maps from T1WI and T2WI using a trained deep learning network. Quantitative analysis was performed on the same lesion ROIs of the estimated T2 maps on baseline and follow-up for progression differentiations. 

Results: The estimated T2 is consistent with the intensity level of the prostate tumor. T-test results verified the significant difference of the mean T2 values between processor and non-progressor. 

Impact: The estimated T2 information derived from standard clinical MRI has the potential for more accurate PCa progression detection. 

Keywords: Prostate, Prostate, Prostate Cancer, Radiomics Analysis

Motivation: Despite the growing use of multiparametric MRI (mpMRI), there remains an unmet need for additional quantitative methods to improve prostate cancer (PCa) localization by prostate anatomic zones.

Goal(s): To extract radiomics features that determine differences in detection rates (DRs) and positive predictive values (PPV) for clinically significant PCa (csPCa). 

Approach: We extracted shape- and first-order based features from 543 csPCa lesions across 468 male subjects and used the Mann-Whitney U test to assess differences in key features.

Results: csPCa lesions located at anterior and TZ prostate regions had significantly larger shape-based features and significantly smaller first-order features than posterior and PZ regions, respectively.

Impact: For patients with csPCa, significant radiomics features extracted from mpMRI lesions in the anterior and transition zone prostate regions show significantly larger shape-based features and significantly smaller first-order features than csPCa lesions in the posterior and peripheral zone regions, respectively.

Keywords: Prostate, Prostate

Motivation: Prostate specific antigen(PSA) and PSA density (PSAD) are inadequate for PCa screening.

Goal(s): Our goal was to combine PSA and MRI measures from Hybrid Multi-dimensional MRI (HM-MRI) to improved PCa diagnosis.

Approach: Blood PSA level, prostate volume from mpMRI and tissue volumes (epithelium, lumen) from HM-MRI were used to measure PSAD and PSAD normalized by tissue type (nPSAD).

Results: nPSAD_epithelium is significantly lower and nPSAD_lumen is significantly higher in cancer patients compared to benign subjects. The diagnostic accuracy of nPSAD to detect subjects with PCa, was significantly higher than conventional PSAD, and further improved by combining nPSAD with tissue composition measures from HM-MRI.

Impact: We introduce a new cancer biomarker that combines PSA (blood-based biomarker) with tissue composition from HM-MRI. nPSAD_lumen and nPSAD_epithelium improve PCa diagnosis. These new biomarkers may signal effects of PCa on normal prostate and may indicate cancer aggressiveness.

Keywords: Prostate, Prostate

Motivation: Prostate growth rate analysis helps to reveal the development of benign prostate hyperplasia.

Goal(s): To analyze the growth rates in different prostate zones using a previously developed segmentation model.

Approach: The prostate zonal volume and morphology features (zonal width, thickness, height, and sphericity) were computed from the automatic segmentation results to calculate the annual growth rate.

Results: The prostate whole gland volume and transition zone volume increased with age, while the peripheral zone volume decreased with age. Besides, prostate zonal volume growth rate varied between ages, and different locations of the prostate exhibited verified growth rates.

Impact: Prostate growth rate analysis could be done efficiently with the assistance of a deep-learning-based segmentation model. Our study facilitated a detailed investigation of prostate growth patterns and found that different zones and locations of the prostate exhibited different growth rates.

Keywords: Prostate, Prostate

Motivation: Super-resolution deep learning reconstruction (SR-DLR) can simultaneously reduce noise and improve spatial resolution.

Goal(s): Our goal was to evaluate the usefulness of SR-DLR in prostate T2-weighted imaging (T2WI) with conventional and reduced acquisition times.

Approach: SR-DLR was applied to both conventional acquisition time T2WI and short acquisition time T2WI. Visibility of the anatomical structures of the prostate and image quality were evaluated.

Results: SR-DLR significantly improved image quality of prostate T2WI and visibility of detailed anatomical structures, especially in the small structures such as ejaculatory ducts.

Impact: SR-DLR improves T2WI image quality in prostate MRI and improves the visibility of detailed anatomical structures, and has the potential to reduce acquisition time while maintaining adequate image quality for diagnosis.

Keywords: Prostate, Prostate, radiomics; pathomics; biochemical recurrence;multi-modality

Motivation: Prostate cancer (PCa) biochemical recurrence (BCR) following prostatectomy (RP) is correlated with a higher risk of distant metastasis, local recurrence, and even PCa-specific death

Goal(s): To develop and validate a machine learning multi-modality model based on preoperative magnetic resonance imaging (MRI), surgical whole-slide images (WSIs) and clinical variables for predicting PCa BCR following RP.

Approach: Radiomics signature and pathomics signature were constructed using preoperative MRI and surgical WSI, respectively. A multi-modality model was constructed by combining radiomics signature, pathomics signature and clinical factors.

Results: The multi-modality model exhibited the best predictive efficacy, which is significantly higher than all single-modality models.

Impact: Our research could provide an innovative and useful tool for facilitating precision decision-making and personalized treatment in PCa patients. Future studies could utilizing deep learning to analyses mpMRI and WSIs.

Keywords: Prostate, Prostate, radiomics, deep learning, Gleason score

Motivation: Gleason Score (GS) could only be obtained through biopsy or radical prostatectomy (RP), which might carry a multitude of complications and pose additional financial burdens and emotional strain.

Goal(s): To explore the predictive value of mixed model combined clinical features, radiomics features and deep learning features for GS.

Approach: The mixed model was constructed to classify grade group 0 (GG0) (benign), GG1, GG2, GG3, GG4 and GG5. DenseNet was used to establish the model.

Results: The mixed model had the best predictive ability, with Kw of 0.74 and relative accuracy of 0.76.

Impact: Clinicians could obtain GS without biopsy or surgery, which could avoid a lot of complications and financial burdens. Future studies could integrate automated VOI segmentation algorithm to optimize AI model.

Keywords: Prostate, Prostate

Motivation: Multiparametric MRI is highly sensitive for identifying clinically significant prostate cancer (csPCa), but has a poorer specificity, meaning many men undergo unnecessary prostate biopsies.

Goal(s): To evaluate whether artificial intelligence (AI) could improve the diagnostic accuracy of MRI compared to current clinical methods, including Likert score and PSA density (PSAd).

Approach: We carried out independent evaluation of a prostate MRI lesion classifier model using a large multisite and multivendor prostate MRI dataset (1,039 patients).

Results: The AI model matched the sensitivity and specificity of Likert score plus PSAd cut-offs on data similar to the training set, but did not generalise to other data.    

Impact: An infrastructure has been successfully established to allow robust and independent evaluation of prostate MRI lesion classification models to accelerate the development of such tools and to ensure adequate testing pre-deployment.

Keywords: Prostate, Diffusion/other diffusion imaging techniques, B0-inhomogeneity distortion correction

Motivation: The Jacobian intensity correction (JIC) of conventional EPI-distortion correction methods can conceal severe under-correction and even create false anatomical structure.

Goal(s): Demonstrate the shortcomings of JIC methods and present an alternative distortion-correction technique that obviates the need for a JIC.

Approach: Acquiring DWI images with opposite phase-encoding polarity at multiple b-values and normalizing prior to estimating tissue displacement eliminates the need to account for intensity scaling with the JIC. This approach, referred to as mRPG, was compared against conventional distortion correction methods.

Results: mRPG significantly improved the estimation and removal of spatial distortions compared to conventional methods.

Impact: Jacobian intensity correction (JIC) can generate misleading improvement of EPI distortion and create false structure in prostate diffusion images. Eliminating the JIC, by acquiring opposed-phase images at multiple b-values and normalizing prior to correction, results in improved EPI distortion correction.

Keywords: Prostate, Prostate, apparent diffusion coefficient; repetition time; diffusion-weighted imaging; magnetic resonance imaging; prostate cancer

Motivation: Assessing whether short repetition time (TR) diffusion-weighted imaging (DWI) surpasses conventional long TR DWI for prostate cancer detection.

Goal(s): To compare the image quality and diagnostic accuracy of short TR DWI to long TR DWI using a 3.0-Tesla MRI.

Approach: Twenty-five prostate cancer patients were imaged with both short (1850 ms) and long (6000 ms) TR DWI. We analyzed signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC), with additional qualitative diagnostic assessments.

Results: Short TR DWI yielded higher CNR and visual scores with stable SNR, alongside robust ADC correlations, enhancing diagnostic performance notably for non-specialist readers.

Impact: Short repetition time diffusion-weighted imaging's improved prostate cancer detection could enhance diagnostic performance for non-specialist readers, influencing treatment and patient outcomes. It invites new magnetic resonance imaging research and may transform standard prostate cancer diagnostic protocols, reducing unnecessary invasive procedures.

Keywords: Prostate, Cancer

Motivation: A sensitive imaging method that distinguishes benign or low-grade prostate lesions from aggressive ones is one of the greatest needs in prostate cancer.

Goal(s): To develop new prostate DWI technique using a non-linear gradient (NLG) to improve the diagnostic accuracy of prostate cancer.

Approach: Using an NLG coil, we can circumvent the challenge of high b-value requirements by having a gradient with a high amplitude within a limited field of view, which applies to prostate imaging.

Results: We demonstrate feasibility of using an NLG for prostate imaging, after validation with a polyvinylpyrrolidone (PVP) phantom and testing SE and EPI sequences with prostate ADC-mapping.

Impact: To better diagnose prostate cancer with high sensitivity, we use an NLG insert coil. Using only one DWI and one non-diffusion image we showed comparable ADC maps to those produced using gold standard multi-shell linear gradient sequences.

Keywords: Radiomics, Radiomics, diffusion-weighted imaging (DWI), repeatability, magnetic resonance imaging (MRI)

Motivation: Typically, diffusion-weighted imaging (DWI) modelling is assumption-based using e.g. exponential models, but nonparametric (data-based) methods have not been explored. 

Goal(s): We propose a information-theoretic paradigm for DWI modelling which results in a novel radiomics for DWI of prostate cancer (PCa).

Approach: The proposed radiomics, EDDIE (entropy of divergence of DWI decay curve) is formulated as entropy of information lost from approximating a reference by DWI decay curves. It is subjected to classification of clinically significant and insignificant PCa using test-retest DWI datasets of 78 patients.

Results: EDDIE achieved an AUC score of 0.77 and an ICC (3,1) of 0.78 which indicates good repeatability. 

Impact: The proposed approach is nonparametric (assumption-free), interpretable (mathematically and physically meaningful) and complete (higher-order measurement). These may contribute towards more accurate and efficient DWI modelling. Besides, the associated novel radiomics could help ushering in more information-theoretic developments in this field. 

Keywords: Prostate, Prostate, Clinically Significant Prostate cancer,PSA density,PSA gray zone,PI-RADS v2.1

Motivation: It is crucial to improve the accuracy of detection of clinically significant prostate cancer (csPCa) within the PSA gray zone.

Goal(s): To combine PI-RADS v2.1 with prostate-specific antigen density(PSAD) derivatives to improve the predictive value of csPCa in the PSA gray zone.

Approach: Based on a dual-center study, logistic regression was used to analyze the predictive value of the multi-parameter combination on csPCa in the training group, the receiver operating characteristic curve(ROC) curves were used to evaluate the diagnostic performance, and conducting external validation.

Results: The area under curve (AUC) of combining of PI-RADS v2.1 and PSAD was the highest for predicting csPCa.

Impact: The dual-center study demonstrates combining of PI-RADS v2.1 and PSAD improved the predictive performance of csPCa in the PSA gray zone, and grouping PSAD with PI-RADS risk stratification can have more direct clinical applications.

Keywords: Prostate, Artifacts

Motivation: Clinically utilized diffusion weighted imaging (DWI), an essential part of prostate MRI, relies on echo planar imaging (EPI) and is prone to geometric distortion and signal loss due to susceptibility from rectal gas and metal hip prostheses.

Goal(s): To improve the robustness of prostate DWI in the setting of field inhomogeneities from hip prostheses and rectal gas.

Approach: Prospective study of 10 patients undergoing prostate MRI with diffusion prepped fast spin echo (FSE) sequence, as well as single-shot and multi-shot DW-EPI, comparing prostate measurements.

Results: We show feasibility of using a diffusion prepped FSE sequence in prostate MR with decreased distortion and artifact.

Impact: A diffusion prepped fast-spin echo sequence avoids distortion and signal loss from susceptibility artifacts seen with echo planar imaging, and is a feasible method to obtain robust diffusion weighted imaging of the prostate.

Keywords: Prostate, Prostate

Motivation: The diagnostic utility of whole tumor amide proton transfer–weighted (APTw) imaging analysis for predicting prostate cancer(PCa) has not been reported.

Goal(s): The purpose of this study was to evaluate the diagnostic performance of whole tumor APTw histogram analysis, for the depiction of PCa compared with multiparametric MRI with Prostate Imaging Reporting and Data System (PI-RADS) version 2.1. 

Approach: Diagnostic performance was assessed by ROC with AUC analysis. 

Results: We found that combining PI-RADS version 2.1 and APTw histogram achieved the best results in distinguishing  transition zone PCa from benign prostatic hyperplasia and peripheral zone PCa from chronic prostatitis.

Impact: Whole-tumor histogram analysis of APTw images improved the diagnostic performance of multiparametric MRI with PI-RADS version 2.1 in detecting prostate cancer in both the peripheral and transition zones.

Keywords: Prostate, Elastography, MRE, Lower Urinary Tract Symptoms, Shear Stiffness, LUTS

Motivation: There is a critical need for significant improvements in image-based assessment of the prostate in men with lower urinary tract symptoms (LUTS).

Goal(s): To develop non-invasive image-based biomarkers that will optimize clinical management of men with LUTS.

Approach: Quantify transition zone complex shear modulus (henceforth ‘stiffness’) with transperineal magnetic resonance elastography (pMRE) at 90Hz and 100Hz.

Results: Mean periurethral TZ stiffness increases with frequency (3.0clip_image006.png">0.4kPa).

Impact: Transperineal pMRE is technically feasible, generates volumetric whole prostate quantitative parametric maps that can differentiate zonal prostate anatomy. Periurethral TZ stiffness, measured with pMRE, may be a clinically useful biomarker for identifying discrete phenotypes of LUTS.

Keywords: Prostate, Prostate

Motivation: Accurate prediction of prostate cancer(PCa) bone metastases can be challenged by radiologists. The utility of APTw histogram methods for evaluating bone metastases involvement in PCa is still unclear.

Goal(s): The purpose of this study was to evaluate APTw-derived whole-tumor histogram analysis parameters in predicting PCa bone metastases. 

Approach: Diagnostic performance was evaluated using ROC analysis and the AUC comparisons were conducted using the DeLong method.

Results: Our preliminary research showed that whole-tumor histogram analysis of APTw images combined with clinical factors (tPSA, cT stage) showed good diagnosis efficiency in predicting PCa bone metastases while using ⁶⁸Ga-PSMA PET/CT as the reference standard. 

Impact: Our preliminary research showed that whole-tumor histogram analysis of APTw images combined with clinical factors(tPSA, T stage) showed good diagnosis efficiency in predicting prostate cancer bone metastases while using ⁶⁸Ga-PSMA PET/CT as the reference standard. 

Keywords: Prostate, Cancer, prostate cancer, brachytherapy, radiotherapy, MR spectroscopy

Motivation: Monitoring time-dependent effects of prostate brachy- and radiotherapy.

Goal(s): Assessment of prostate metabolic activity during and three months after the completion of brachy- and/or external beam radiotherapy. 

Approach: Single-voxel ¹H-MRS with a surface receiver coil. 

Results: It is demonstrated that the proposed ¹H-MRS approach is a useful tool for monitoring metabolic changes in prostate tissues treated with brachy- and/or external beam radiotherapy. We found reduction of citrate intensity close to the noise level to be the most reliable measure for identification of metabolic atrophy and response to therapy.

Impact: Single-voxel ¹H-MRS with a surface receiver coil is an effective method for monitoring the response of prostate tissues to brachy- and/or external beam radiotherapy. Good response to prostate radiotherapy might be characterized by low citrate intensity.

Keywords: Prostate, Prostate, Cancer, Hyperpolarized MR

Motivation: Monitoring the progression or response of advanced prostate metastases is a current clinical unmet need that is not reliably delineated with current CT and PET. 

Goal(s): Here, we developed a high-resolution whole abdominopelvic [1-¹³C]pyruvate HP MRI approach for the metabolic biomarker characterization of metastases in prostate cancer patients.

Approach: A variable-resolution imaging approach was used to provide high-resolution [1-¹³C]pyruvate, robust spatiotemporal denoising and B₁+ variation correction methods were used to quantify the rate-constant for the conversion of [1-¹³C]pyruvate to lactate, k_PL. 

Results: Improved conspicuity of [1-¹³C]pyruvate distribution and k_PL conversion maps of metastatic lesions were achieved with the new approach. 

Impact: The improvement in [1-¹³C]pyruvate resolution and clear delineation of highly metabolically active metastatic lesions in k_PL maps demonstrated the potential of [1-¹³C]pyruvate HP MRI in advanced prostate cancer.  

Keywords: Prostate, Hyperpolarized MR (Non-Gas), Prostate cancer, Preclinical models

Motivation: Diagnosis and treatment assessment of aggressive small cell neuroendocrine prostate cancer (SCNC) is challenging due to its admixture presence in conjunction with adenocarcinoma phenotype and differential response to treatments subjective to the metastatic sites.

Goal(s): This study aims to assess the therapeutic efficacy of platinum-based chemotherapy in preclinical SCNC metastatic models using patient derived xenografts.

Approach: Hyperpolarized ¹³C MRI was used to measure the apparent rate of change in glycolysis (k_PL) in PDX models of SCNC in metastatic sites.

Results: k_PL values clearly demonstrated a decrease upon treatment concordant to the change in tumor volume in both the liver and bone metastatic models.

Impact: k_PL, measured by hyperpolarized MRI, can be used to assess treatment efficacy yielding a non-invasive, potentially early biomarker readily translatable for use in patients with metastatic tumors for optimal therapeutic approaches.

Keywords: Prostate, Prostate, High-field MRI

Motivation: To better detect and delineate prostate cancer using ultrahigh field MRI.

Goal(s): To investigate if clinical prostate MRI at 7T using recent technological advances is feasible.

Approach: Prostate MRI was performed in 5 healthy volunteers using the latest generation of whole-body 7T MRI scanners incorporating enhanced gradient performance, advanced deep learning based image reconstruction and an 8Tx/16Rx torso array.

Results: High image quality with an unprecedented spatial resolution and a sharpness obtained at 7T outperformed those obtained at 3T even when time-matched sequences were acquired.

Impact: The preliminary data obtained from several volunteers provides a great encouragement to start clinical studies in prostate cancer patients.

Keywords: Prostate, Prostate, BPH, PCa

Motivation: Accurate interpretation of prostate MRI demands a high level of expertise and deep learning models for prostate cancer (PCa) detection often suffer from low specificity.

Goal(s): To explore the value of annotation of benign prostatic hyperplasia (BPH) to prostate cancer (PCa) detection.

Approach: We retrospectively collected 96 patients with PCa and 92 patients with BPH, all scanned with PI-RADS protocol. Two deep learning models were built: Model1 only detected PCa while Model2 simultaneously detected BPH and PCa.

Results: Model2 achieved superb performance with test AUC of 0.995, outperforming Model1 whose test AUC was 0.770.

Impact: Explicitly using the BPH label improved the performance of PCa detection significantly, implying multi-task deep learning models targeting multiple diseases are not only more in line with the needs of clinical applications, but can also bring about performance improvement.

Keywords: Pancreas, Image Reconstruction, AI, Super Resolution

Motivation: Abdominal diffusion-weighted imaging (DWI) plays a significant role in the detection and characterization of lesions. However, the spatial resolution of single-shot echo-planar imaging (ssh-EPI) readout is limited by the acquisition time.

Goal(s): To enhance the image quality and sharpness of abdominal ssh-EPI-DWI image using a prototype AI-based reconstruction technique (SuperRes).

Approach: We examined eight healthy volunteers using abdominal ssh-EPI-DWI, and the acquired data were reconstructed using both conventional Compressed SENSE and SuperRes. The image quality was assessed qualitatively and quantitatively.

Results: SuperRes demonstrated a significant improvement in the image quality and sharpness of both DWI and ADC map. 

Impact: The dedicated deep learning-based super-resolution technique enhanced the image quality and sharpness in abdominal ssh-EPI-DWI. Enhanced sharpness resulted in better delineation of structures, such as the pancreas. The improvement in image quality was demonstrated in both qualitative and quantitative assessments.

Keywords: Breast, Image Reconstruction

Motivation: DWI MRI is widely used in diagnosis and treatment evaluation of breast cancer but is prone to artifacts due to the breast's superficial location and large field of view (FOV).

Goal(s): To investigate the feasibility and performance of reduced-FOV FOCUS DWI and FOCUS DWI with deep learning-based reconstruction (DLR) for breast MRI in Asian patients with small breast volumes.

Approach: Both subjective and objective methods were used to compare the image quality of FOCUS DWI, FOCUS-DLR DWI and conventional DWI for breast cancer imaging.

Results: Our results demonstrated that FOCUS-DLR DWI showed improved image quality and higher image scores compared to conventional DWI.

Impact: FOCUS-DLR DWI enhances the visibility of lesion details, offering a novel approach to optimize breast MRI. This technique also holds promise for improving diffusion imaging in other regions of the human body, particularly small organs with surrounding tissue.

Keywords: Digestive, Diffusion/other diffusion imaging techniques

Motivation: Microsatellite instability (MSI) in esophagogastric junction adenocarcinoma (EGA) can serve as a predictor of sensitivity to immunotherapy and affect the prognosis. Predicting MSI preoperatively can enable personalized and precise treatment for EGA patients.

Goal(s): This study investigates the use of fast non-Gaussian diffusion-weighted imaging with deep learning-based reconstruction (DLRecon) to assess MSI in EGA.

Approach: We compared image quality between conventional scanning (CS) and DLRecon, calculated diffusion parameters, and assessed their ability to distinguish MSI status.

Results: DLRecon exhibited superior image quality and reduced scan time. Diffusion parameters effectively differentiated MSI status in EGA.

Impact: DLRecon non-Gaussian DWI significantly improved image quality and reduced acquisition time. Multiple diffusion parameters may serve as imaging markers, and their combination provides high diagnostic accuracy for discriminating MSI status in EGA.

Keywords: Prostate, Prostate

Motivation: Multiparametric prostate MRI is lengthy and costly, presenting a challenge for widespread implementation.

Goal(s): To develop an automated triage protocol using a deep learning classifier to discern, based on an abbreviated biparametric MR examination, between high-risk patients who would benefit from additional sequences and low-risk patients who would not.

Approach: A double-branched ResNet50 with 3D convolutions was trained on biparametric scans to predict the presence of clinically significant prostate cancer.

Results: The classifier achieved a sensitivity of 0.93 with 88% negative predictive value, indicating potential to reduce comprehensive MRI exams for those without clinically significant disease by 40%.

Impact: Our triage protocol has the potential to streamline prostate cancer screening by reducing the number of full mpMRI exams, thereby lowering healthcare costs. The classifier could pave the way for personalized, risk-adaptive screening protocols, allowing more precise and resource-efficient diagnostics.

Keywords: Cancer, Prostate, rostate cancer diagnosis, Gleason score prediction, Magnetic Resonance Imaging (MRI), Convolutional Neural Networks (CNN), Pathological upgrading detection, Lesion characterization, Clinical significance determination, Artificial Intelligence (AI) in medical imaging, Precision medicine, Patient management, Predictive modeling in oncology, Diagnostic precision, Risk assessment in prostate cancer, Biopsy accuracy, Medical imaging technologies, Machine learning in healthcare

Motivation: Patients with low risk (Gleason 6) MR visible prostate cancer on initial biopsy are frequently upgraded to aggressive higher risk (Gleason 7 or higher) cancer. Identifying this progression early is difficult.

Goal(s): To address this using a neural network trained with radiologist labels and whole mount histology of Gleason ≥7 cases to predict pathological upgrading in our cohort.

Approach: DecNet was applied to the Gleason 6 initial MRIs to assess if the model could retrospectively identify patients with higher grade disease.

Results: Our model had a sensitivity of 84.6% for lesions upgraded to Gleason 7, outperforming PSA density, lesion size and ADC values.

Impact: These results showcase the potential of our model in unveiling higher-grade prostate cancer within lesions initially diagnosed as lower grade on pathology.

Keywords: Prostate, Prostate

Motivation: The need to improve prostate cancer diagnosis through advanced understanding of lesion characteristics and reducing false positives led to this research.

Goal(s): To create a pioneering integrated system using deep learning, capable of accurately assessing the benignity or malignancy of prostate MRI images, whilst reducing labeling costs and enhancing the reliability of classifications.

Approach: The approach involves training a convolutional network with multi-parametric MRI images, incorporating credibility analysis to provide visually interpretable prostate cancer prediction results and reject low-credibility predictions. 

Results: The results showed improved reliability and efficacy, with the model discarding low-credibility predictions, thus mitigating potential risks associated with prediction failures.

Impact: This study equips clinical practitioners with the ability to comprehend the decision-making process of the CAD system and manage the output results through an intuitive display. This results enhance diagnostic accuracy, potentially impacting clinicians' decision-making and patient outcomes.

Keywords: Pancreas, Pancreas

Motivation: Cystic fluid appears hyperintense via T2WI, the most sensitive detection method and T2WI is a conventional sequence. However, distinguishing pancreatic MCNs from SCNs using T2WI is difficult because both neoplasms appear as hyperintense lesions, especially when both are unilocular.

Goal(s): We aimed to develop and validate a T2WI radiomics nomogram for the differentiation of SCNs from MCNs.

Approach: A radiomics model that was included clinical characteristics, MRI characteristics, and T2WI rad-scores for differentiating MCNs from SCN.

Results: We developed and validated a T2WI radiomics nomogram that functions as a non-invasive and convenient tool for preoperatively predicting the presence of SCNs and MCNs.

Impact: The tool has the potential to help clinicians identify patients requiring surveillance or surgery.

Keywords: Kidney, Radiomics

Motivation: Kidney cancer is often diagnosed as either clear cell renal carcinoma (ccRCC) or non-clear cell renal carcinoma (non-ccRCC) to determine treatment recommendations. Additionally, many patients with kidney cancer cannot receive contrast medium due to renal function disorders.

Goal(s): for the distinction of ccRCC from other types of RCC without contrast medium administration

Approach: A model using automated machine learning (AutoML) based on radiomics features 

Results: Our results indicate that the best model from the AutoML process demonstrated a mean sensitivity of 0.819 and a mean specificity of 0.729 in distinguishing between ccRCC and non-ccRCC.

Impact: To demonstrated that the TPOP-radiomics-based classification model can effectively discriminate between ccRCC and non-ccRCC using MRI without the need for contrast medium.

Keywords: Digestive, Radiomics, Crohn’s disease; Fibrosis; MR Enterography

Motivation: Fibrostenosis is a severe complication of Crohn's disease that significantly impacts patients' quality of life. Currently, there are no effective medical interventions for severe intestinal fibrosis

Goal(s): We aimed to develop MRI-based radiomic models to improve the diagnostic accuracy of radiologists in characterizing intestinal fibrosis in patients with Crohn’s disease.

Approach: Radiomic models based on different MR sequence combinations were developed and validated in an independent test cohort. 

Results: The radiologists’ interpretation aided by MRI-radiomics outperformed visual interpretation in characterizing intestinal fibrosis in Crohn's disease (AUC=0.86-0.93 vs. AUC=0.63-0.77).

Impact: The utilization of MRI-based radiomic models significantly enhances the diagnostic accuracy of radiologists in characterizing intestinal fibrosis.

Keywords: Fetal, Data Processing

Motivation: The cerebral cortex of the fetus is undergoing intricate development. Abnormal cortical development may potentially alter brain function. However the methods for processing fetal MRI images, especially cortical reconstruction, are still far behind those used for adults.

Goal(s): To develop an accurate cortical surface reconstruction method and perform morphological calculations for fetal MRI.

Approach: Trustworthy AI segmentation and refined Freesurfer were used to process T₂-weighted fetal brain image. 

Results: The proposed mothod (FetalSurfer) allows for trustworthy reconstruction of the cortical surfaces of the fetal brain and calculation of indicators to measure the morphology of fetal development.

Impact: FetalSurfer implements a novel fetal cerebral cortex reconstruction method without manual refinement by professional doctors, filling the gap of fetal image processing methods. Calculated indicators as curvature, thickness and sulcal depth can be used to perform morphological analysis.

Keywords: Hepatobiliary, Radiomics

Motivation: To the best of our knowledge, our study is the first to non-invasively assess methyltransferase-like 3 (METTL3) expression in hepatocellular carcinoma (HCC) using multi-sequence MRI-based radiomics.

Goal(s): To develop a multi-region radiomics-based predictive model using multi-sequence MRI to assess METTL3 expression in HCC.

Approach: Three Models (Tumor, Tumor-Expand5, Tumor-Expand10) were constructed and evaluated.

Results: The Tumor-Expand5 model showed the highest efficacy with an AUC of 0.71 in the test set, outperforming both the Tumor and Tumor-Expand10 models. Multi-sequence MRI-based radiomics models hold the potential for preoperatively assessing METTL3 expression in HCC, aiding clinical decision-making.

Impact: This study introduces a novel multi-region radiomics-based model for predicting METTL3 expression in HCC using multi-sequence MRI. The results demonstrate the potential of radiomics, with an emphasis on the Tumor-Expand5 model, highlighting its promise for enhancing clinical decision-making in HCC.

Keywords: Digestive, Cancer, Rctal; Prognosis

Motivation: The prognostic value and importance of peritumoral radiomics remain underexplored in locally advanced rectal cancer (LARC).

Goal(s): To investigate the prognostic significance of peritumoral versus intratumoral radiomic features in LARC.

Approach: In a retrospective cohort of 409 patients with LARC, we extracted intratumoral and peritumoral radiomic features from pretreatment high-resolution small-field-of-view T2-weighted images. Various prognostic models incorporating clinicopathological and radiomic data were constructed and compared. Variable importance was analyzed.

Results: Peritumoral features demonstrated equivalent or superior prognostic value than intratumoral features, significantly enhanced accuracy of models relying on intratumoral or intratumoral-clinicpathological features. One peritumoral feature emerged as the leading predictor.

Impact: Peritumoral radiomics provides equal or even greater prognostic value compared to intratumoral radiomics, promising to enhance accuracy in prognostic estimation for locally advanced rectal cancer and thus facilitating personalized treatment strategies.

Keywords: Hepatobiliary, Low-Field MRI, Abdomen, deep-learning reconstruction

Motivation: Deep-learning reconstruction may overcome two shortcomings of 0.55T, low SNR and extended scan time, without compromising lesion conspicuity.

Goal(s): To demonstrate that image quality and SNR of deep-learning reconstructed 0.55T images are at least similar to 1.5T/3T images, while maintaining visibility of pathologies.

Approach: 23 patients imaged at 0.55T using standard and deep-learning HASTE and DWI. Three radiologists rated IQ and SNR at 0.55T and HF. Pathologies were evaluated in deep-learning images.

Results: Deep-learning reconstructed HASTE and DWI 0.55T images were of same or better quality and SNR than 1.5T/3T images. All pathologies were visible on deep-learning 0.55T images. DL reduced HASTE scan-time.

Impact: Deep-learning reconstruction algorithms of select sequences at 0.55T can help overcome low SNR and extended scan times of current 0.55T abdominal imaging, making it comparable or superior to standard-of-care 1.5/3T, thereby expanding global use of a more accessible MRI system.

Keywords: Kidney, Elastography, Magnetic resonance elastography, chronic kidney disease, renal stiffness

Motivation: The incorporation of automated kidney segmentation technology with multi-frequency MRE represents a novel approach in evaluating kidney diseases.

Goal(s): To explore the reliability of multi-frequency MRE combined with an automatic segmentation method and its diagnostic potential for CKD patients.

Approach: Constructed an automatic kidney segmentation model based on the nnU-Net network and measured the renal stiffness of MRE, employing T-tests, ROC curves, and Spearman correlation for data analysis.

Results: The incorporation of an automatic kidney segmentation model and multi-frequency MRE shows promise in effectively evaluating and monitoring kidney fibrosis.

Impact: The incorporation of automated kidney segmentation and MRE presents a new tool for reliably evaluating and monitoring kidney diseases, providing potential advancements in non-invasive diagnoses.

Keywords: Digestive, Biliary

Motivation: Differentiating CBD dilatation with CT alone is challenging, often necessitating MRCP(Magnetic Resonance Cholangiopancreatography). Yet, patients forego MRCP due to cost and time constraints. Hence, predicting CBD dilatation using CT is vital for diagnosis.

Goal(s): Developing deep neural networks to assess CBD dilatation only with CT data.

Approach: Cycle-GAN and 3D VGG Networks predicted CBD dilatation, where Cycle-GAN generated synthetic MRCP from CT and 3D VGG Network predicted dilatation using this synthetic data.

Results: The network trained with synthetic MRCP data predicted CBD dilatation with an AUROC of 0.7231, 30% improvement over using CT data alone, enabling CT-only diagnosis.

Impact: This study introduces a transformative solution for CBD dilatation diagnosis, enabling assessments using Only-CT data from Cycle-GAN and 3D VGG Network. Achieving a 30% improvement in AUROC, it enables reliable CT-only diagnoses, overcoming scarce MRCP data and improve patient care.

Keywords: Liver, Liver, Foundation model, Segmentation

Motivation: Accurate hepatic vessel segmentation can help to identify and avoid critical blood vessels during liver tumor ablation or resection. Existing methods are not accessible to most medical institutes, leading to questionable clinical relevance.

Goal(s): we present a handy foundation model-based hepatic vessel segmentation approach crafted for straightforward integration into clinical applications.

Approach: We employ a parameter-efficient few-shot learning strategy to fine-tune the foundation model, thereby enabling it to achieve competitive hepatic vessel segmentation performance with training on only five cases.

Results: The proposed method is effective and easy-to-access, and it has the potential for a substantial impact on clinical practice.

Impact: Existing hepatic vessel segmentation methods are not accessible to most medical institutes, leading to questionable clinical relevance. We present a clinically practical foundation model-based approach that achieves competitive performance with training on only five cases.

Keywords: Cancer, Radiomics

Motivation: In rectal cancer, the existing stratification of prognosis is mainly based on the established TNM tumor staging system, which limits clinical decision-making.

Goal(s): Construct a model to provides prognostic information preoperatively.

Approach: This study established radiomics models  to predict the disease-free survival (DFS) in rectal cancer, based on tumor, and multiple body components (including mesenteric fat and pelvic skeletal muscles) in MRI.

Results: The radiomics model based on tumor and multiple body components of MRI in rectal cancer, have good predictive value for DFS in rectal cancer patients at 2 years after surgery.

Impact: The model that provides prognostic information at the time of cancer diagnosis would be useful for optimizing treatment and monitoring.

Keywords: Kidney, Kidney, ASL, 3D Cartesian TSE, CS-AI, Deep Learning

Motivation: Motion and breathing can compromise 3D renal ASL MRI, reducing SNR and causing artifacts. Shorter-time acquisition is crucial for its clinical utility

Goal(s): To Evaluate the potential of CS-AI in accelerating renal ASL MRI with 3D Cartesian TSE. 

Approach: We accelerated renal ASL MRI 2-, 4-, and 6 times using CS-AI, comparing with SENSE. 

Results: CS-AI-accelerated images exhibited superior SNR and quality compared to SENSE, without affecting RBF quantification.

Impact: This study may enhance the clinical utility of 3D renal ASL, particularly in discerning perfusion alterations in small-sized lesions like small renal masses.

Keywords: Kidney, Genetic Diseases, ADPKD

Motivation: Height-adjusted total kidney volume (htTKV) growth rate measured on MRI or CT is a critical biomarker for monitoring autosomal dominant polycystic kidney disease (ADPKD) progression.

Goal(s): This study aims to develop a tool for accurate calculation of the htTKV growth rate based on all available MRI scans.

Approach: Accuracy of four MRI methods for calculating htTKV growth rate were assessed as compared to ground truth calculated from 10+ years of imaging follow up.

Results: Using 2-parameter least squares fitting with 3+ scans or 5+ years of follow up reduce error 2-fold compared to the current clinical standard, Mayo Imaging Classification.

Impact: Accurate estimation of kidney growth rate on abdominal MRI using FIT will enable better prediction of disease progression and response to therapy in patients with ADPKD.

Keywords: Lung, Lung

Motivation: Spiral-UTE MRI has been proposed for more efficient lung imaging to permit breath-hold ultra-short echo time acquisition of the lung. It is more valuable to further accelerate the acquisition of the spiral-UTE MRI of lung images, thus enabling shorter breath-holds and higher spatial resolutions.

Goal(s): This work presents a deep learning based method to enable the reconstruction of spiral-UTE MRI of lung images from accelerated spiral k-space.

Approach: An unrolled network was developed for reconstructing images from the accelerated non-cartesian k-space.

Results: The unrolled network allows for higher reconstruction quality for spiral-UTE MRI of lungs compared to a standard U-Net.

Impact: The proposed unrolled network tailored for spiral MRI reconstruction enables reconstruction of accelerated spiral-UTE of lung images to allow shorter breath-holds and higher spatial resolutions. This reconstruction technique can also extended to other multi-coil non-cartesian accelerated MRI reconstructions.

Keywords: Lung, Lung

Motivation: Ultrashort echo time (UTE) MR imaging has been developed to visualize lung tissues, but is limited by  long acquisition time and capacity for displaying pulmonary tissues. 

Goal(s):  3D free breathing stack-of-spirals UTE (spiral-UTE) could provide a higher readout efficiency, but its comprehensive performance  with and without contrast material for follow-up of patients with identified malignant tumors at 1.5T has not been reported. 

Approach: Aim to investigate  clinical feasibility of spiral-UTE  compared to enhanced-VIBE with CT as the reference.

Results: Spiral-UTE was superior with improved image qualities for depicting bronchi and lung parenchyma  than enhanced-VIBE in lung screening during the oncology patient follow-ups

Impact: Spiral-UTE provides a potential alternative to CT for lung follow-up with a significantly superior quality visualization of the pulmonary anatomy than routine enhanced-VIBE

Keywords: Lung, Lung, Zero echo time, pulmonary ventilation

Motivation: Lung MRI using UTE and ZTE techniques is limited by its SNR and tissue interface blurring. Deep learning based reconstruction (DLR) technique has been used to improve MRI image quality via noise reduction.

Goal(s): To evaluate potentially clinical applications of breath-hold DLR ZTE lung MRI in ventilation function.

Approach: DLR and conventional reconstructed ZTE lung images of thirty patients with pulmonary nodules were compared for image quality and image-based pulmonary ventilation estimation. 

Results: Compared to conventional reconstructed results, DLR ZTE images demonstrated improved image quality and better correlation with clinical measurements for ventilation estimation. 

Impact: This preliminary study demonstrated the feasibility of DLR ZTE technique in lung MRI. DLR ZTE images showed improved image quality and better correlation with clinical measurements for ventilation estimation. 

Keywords: Lung, Lung

Motivation: There is a lack of non-invasive approaches for quantitatively analyzing the patterns of respiration motion in proton MRI in patients with lung diseases such as post-COVID symptoms.

Goal(s): The goal of this work is to determine whether post-COVID-19 patients can be classified as having either long COVID or no symptoms by analyzing dynamic MRI motion fields within various regions of lungs.

Approach: A deep learning-assisted framework was developed for automatically analyzing localized respiratory motion in lung MRI.

Results: The framework was able to successfully categorize patients into different categories based on their degrees of no symptoms using the proposed image analysis framework.

Impact: This work develops an automated framework that can aid radiologists in quickly determining not only the presence but also the severity of long COVID. It can also be extended for applications in other lung diseases.

Keywords: Prostate, Machine Learning/Artificial Intelligence

Motivation: Radiologists face challenges in the accurate prediction of prostate cancer (PCa) with gray-zone PSA levels. Deep learning (DL) evaluated PCa with gray-zone PSA levels remains unclear.

Goal(s): The aim of this work was to investigate the comparative performance of DL and radiologists. We trained a 3D DenseNet 121 model for automatic PCa classification with gray-zone PSA levels.

Approach: We trained a 3D DenseNet 121 model for automatic PCa classification with gray-zone PSA levels.

Results: The DL model yielded an AUC of 0.95 (0.85-1.0) for the identification of PCa with gray-zone PSA levels in the test set, significantly improving performance over the inexperienced radiologists.

Impact: The deep learning model yielded an AUC of 0.95 (0.85-1.0) for the identification of PCa with gray-zone PSA levels in the test set, significantly improving performance over the inexperienced radiologists. 

Keywords: Prostate, Prostate, k-space data, public

Motivation: There is a lack of publicly available, raw k-space data for prostate MRI.

Goal(s): To compile and release raw k-space data for clinical prostate MRI and demonstrate its utility for development of deep learning methods for image reconstruction and automated diagnosis.

Approach: Biparametric MRI data from 312 patients with associated prostate cancer labels were added to the public fastMRI repository. Deep-learning models were trained on the data to reconstruct images from undersampled k-space and perform automated diagnosis of prostate cancer (PCa) on these images.

Results: SSIM > 0.866 and AUC > 0.80 (test set) for the deep-learning reconstruction and automated PCa diagnosis respectively.

Impact: Raw k-space data with clinical labels from fastMRI prostate will enable researchers to develop clinically relevant deep-learning reconstruction and automated diagnosis models which may ultimately advance the diagnosis and management of prostate cancer.

Keywords: Prostate, Metabolism, Metabolomics, NMR

Motivation: Current diagnostic methods cannot predict the aggressiveness of prostate cancer (PCa) at a treatable stage of  disease. 

Goal(s): To interrogate tumorigenesis of PCa and AI/ML techniques to NMR-based targeted blood plasma metabolomic profiling analysis for prediction of PCa. 

Approach: Use AI/ML approaches to NMR metabolic profiling for PCa patient blood plasma data analysis 

Results: Phosphocreatine, choline, 3-hydroxybutyrate, taurine and glucose showed highest discriminate using CFS, PLS-DA, OPLS-DA,  random forest models. 

Impact: It will pave way to enhance understanding of cancer pathogenesis and biomarker/s identification and early detection systems.

Keywords: Liver, Liver

Motivation: Liver T2-weighted imaging usually requires a long scan time. A faster sequence with adequate image qualities is essential in clinical practice.

Goal(s): To evaluate deep-learning reconstruction accelerated T2-weighted HASTE sequence in liver application on the image quality and diagnostic confidence.

Approach: One hundred and five patients were imaged using both sequences. Images were reviewed independently by two blinded observers.

Results: The DL HASTE sequence can detect more liver lesions and improve the CNR of the lesion compared to the conventional T2-weighted BLADE sequence, with a 2.5-fold reduction in acquisition time.

Impact: DL HASTE sequence has the potential to replace the conventional BLADE sequence in routine clinical liver MRI, reducing the scan time and detecting more liver lesions.

Keywords: Liver, Radiomics, Liver fibrosis; Gd-EOB-DTPA-enhanced MRI; nomogram

Motivation: Despite the effectiveness of elastography and serology tests in detecting liver fibrosis, diagnosing early-stage fibrosis remains challenging.

Goal(s): Develop and validate a reliable radiomics model using Gd-EOB-DTPA-enhanced MRI for early liver fibrosis diagnosis.

Approach: Create a radiomics model based on Gd-EOB-DTPA-enhanced MRI and establish a fused nomogram combining clinical characteristics and LSM. Compare the diagnostic performance of the fused model with single models for early-stage liver fibrosis.

Results: Gd-EOB-DTPA-enhanced MRI radiomics model effectively diagnoses early liver fibrosis. The fusion model enhances diagnostic efficiency.

Impact: To develop and validate a fusion model based on Gd-EOB-DTPA-enhanced MRI to identify early-stage liver fibrosis.

Keywords: Liver, Liver, LAVA-Flex, 3D FLEX DL

Motivation: Fat suppressed T1 images, such as LAVA-FLEX, are routinely used in liver imaging, but can suffer from SNR and IQ issues. 

Goal(s): Our goal was to validate application of 3D deep learning to 3D LAVA-FLEX in routine adult liver imaging via a reader study and noise characterization. 

Approach: DL and conventionally reconstructed images were assessed across several IQ attributes (motion, ringing, edge, vessel) by two radiologists. Noise characteristics were evaluated by calculation of total variation and edge detection. 

Results: Based on the calculated odds ratios, the radiologists preferred DL across the various IQ attributes, with decreased noise and improved sharpness in DL images. 

Impact: The application of 3D DL to routine 3D LAVA-FLEX imaging provides increased diagnostic quality, and has the potential to improve routine abdominal care in patients who can't hold their breath.

Keywords: Liver, Liver, TACE refractoriness，HCC，MRI，Radiomics

Motivation: Parts of HCC  respond poorly to TACE, and its efficacy declines as the number of procedures increases in the clinical practice, which is called TACE refractoriness.

Goal(s): To develop and validate a preoperative multiparametric MRI-based radiomics model to predict TACE refractoriness in HCC.

Approach: Radiomics feature selection was performed using PCC and RFE, and SVM was used to construct radiomic models based on each sequence and their combination, clinical-radiological model based on selected clinical-radiological predictor and combined model.

Results: The combined model exhibited excellent predictive performance. The multi-phase radiomics signature performed better in predicting TACE refractoriness compared to the best single-phase radiomics signature.

Impact:  The preoperative multiparametric MRI radiomics analysis can predict TACE refractoriness in hepatocellular carcinoma, which may provide better guidance for decision-making regarding further TACE treatment and optimize the mode of treatment and patient management, ultimately resulting in patient survival benefits.

Keywords: Liver, Cancer, Habitat imaging

Motivation: Isocitrate dehydrogenase 1 (IDH1) mutation is an important therapeutic target for intrahepatic cholangiocarcinoma (ICC).

Goal(s): To achieve non-invasive prediction of IDH1 mutation in ICC to assist in clinical management.

Approach: Preoperative Gd-EOB-DTPA-enhanced MRI features and clinical information were retrospectively collected. Habitat analysis was performed based on pre- and post-enhancement T1 maps. Nomogram prediction model was established based on filtered variables.

Results: Higher serum AFP level, higher T1 change ratio, more frequent intratumoral vessel and T2 central brightness, and habitat 5 are risk factors for IDH1-mutated ICC. The combined nomogram model demonstrated the highest diagnostic performance over the clinilal+imaging model and the habitat model.

Impact: The proposed strategy, Gd-EOB-DTPA-enhanced MRI and T1–based habitat imaging, can be applied for preoperatively and noninvasively identifying IDH1-mutation status in ICC, which offers potential benefits in terms to aid in clinical management.

Keywords: Liver, Multi-Contrast, Image-to-image translation

Motivation: Either fast 2D T2-weighted abdominal imaging or 3D T2 MIP techniques have limitations. There remains a need for fast 3D T2 abdominal high-resolution imaging.  

Goal(s): To develop a conditional GAN model to synthesize T2-weighted images from 3D high-resolution T1-weighted abdominal images preserving spatial resolution of the source images.

Approach: Abdominal images acquired from 39 volunteers were included for the study. A conditional GAN model was trained to generate T2-weighted images from T1-weighted images slice by slice.

Results: Overall, the generated T2-weighted images were similar to the real T2-weighted images, though some contrast differences in the bowels and kidneys were seen. 

Impact: This proof of principle study shows the GAN model can be used to generate T2-weighted images from T1-weighted images, with the potential for rendering high quality volumetric 3D high-resolution abdominal T2-weighted images that is superior to current 3D MIP methods.

Keywords: Cancer, CEST & MT

Motivation: Tumor budding (TB) is an important additional prognostic factor for patients with colorectal cancer (CRC).

Goal(s):  Accurate TB assessment before surgery can help guide clinical decisions and improve patient prognosis.

Approach: This study explored the feasibility of amide proton transfer-weighted (APTw) MR imaging in assessing TB grade in patients with rectal cancer (RC).

Results: We found that RC lesions with high-grade TB had higher APTw 90^th percentile values than low-grade TB.

Impact: APTw MRI may be beneficial for implementing more accurate personalized treatment and improving tumor prognosis.

Keywords: Cancer, Elastography, Liver, microvascular invasion, biomechanics

Motivation: In hepatocellular carcinoma (HCC), microvascular invasion (MVI), an indicator for tumor aggressiveness, is identified typically through post-resection pathology examination. Currently, non-invasive methods for assessing tumor aggressiveness are lacking. 

Goal(s): Our objective is to discover a non-invasive imaging biomarker for evaluating the presence/absence of MVI.

Approach: The alterations induced by the tumor, such as MVI, can modify the tissue architecture and, consequently, its mechanical properties. Magnetic resonance elastography at 40Hz was performed in 44 HCC patients who had liver resection.

Results: Peritumoral tissue phase angle accurately distinguish patients with/without MVI, indicative for aggressiveness. These results correlate with higher tumor differentiation in patients without MVI.

Impact: This clinical study introduces the phase angle as a new biomarker for gauging HCC aggressiveness whereby enabling patient stratification.

Keywords: Cancer, Cancer

Motivation: Distinct histopathological types are closely related to the prognosis of advanced gastric cancer. Adverse histopathological status (AHS) is linked to poor gastric cancer outcomes. Extra-dimensional volumetric interpolated breath-hold examination (XD-VIBE) offers high temporal and spatial resolution while allowing free breathing.

Goal(s): To improve the assessment of AHS, we explored the potential for XD-VIBE to improve DCE imaging. 

Approach: We evaluated the associations of quantitative DCE MRI parameters (e.g., Ktrans, Ve, and Kep) with AHS. 

Results: Using XD-VIBE, quantitative DCE MRI parameters allowed non-invasive assessment of AHS and helped to optimize treatment strategies for advanced gastric cancer.

Impact: In this single-institution study, quantitative DCE MRI features demonstrated promise as markers of AHS in advanced gastric cancer. These features could provide added prognostic value and identify patients who may benefit from adjuvant therapy.

Keywords: Digestive, Cancer

Motivation: Orthogonal axial images (OAI), which may improve staging performance, had been ignored in previous studies about gastric cancer (GC) T-staging using MRI.

Goal(s): To assess the value of MR OAI in GC preoperative T-staging.

Approach: Diagnostic performance metrics, over- and understaging fractions, overall accuracy (compared by McNemar test) for MRI lacking or incorporating OAI and MDCT were quantified referring to pathological T-stage.

Results: The overall accuracy was significantly higher for MRI with OAI than those without OAI, while marginally better than MDCT. Both MRI with OAI and MDCT exhibited superior staging performance than MRI without OAI.

Impact: By incorporating orthogonal axis images, MRI exhibited diagnostic performance marginally better than MDCT in preoperative T-staging of gastric cancer, thereby offering a superior, non-invasive and radiation-free protocol to determine prognosis and guide appropriate treatment strategies.

Keywords: Treatment Response, Cancer

Motivation: Neoadjuvant immunotherapy (nIT) combined with standard chemotherapy is the innovative treatment for esophageal squamous cell carcinoma (ESCC). Some patients may not respond to nIT.

Goal(s): To investigate the value of DWI-derived parameters for the assessment of pathologic response and detection of minimal residual cancer cell (MRC) to nIT.

Approach: The patient population was a sub-cohort from the clinical trial (ClinicalTrials.gov ID: NCT02611700). The pathological response evaluation according to the TRG system proposed by AJCC. DWI-derived parameters including ADC, D, D* and f.

Results: ΔADC and ΔD values were highlighting in assessment of pathologic response and detection of MRC to nIT.

Impact: Nowadays, evaluation of the response to neoadjuvant therapy for cancer mainly relies on the measurement of tumor size according to RECIST. Pseudo-progression with immunotherapy is often observed.  fMRI techniques can quantify therapy-induced changes before anatomic variation in tumor size.

Keywords: Cancer, Data Analysis

Motivation: Accurate prediction of disease-free survival (DFS) of rectal cancer patients has substantial influences on treatment planning.

Goal(s): To explore the value of ADC and T2W images in predicting DFS for rectal cancer patients.

Approach: Radiomics models using features extracted from ADC and T2W were built and evaluated.