Journal of Magnetic Resonance Imaging最新文献

{"title":"Federated Learning for Renal Tumor Segmentation and Classification on Multi-Center MRI Dataset.","authors":"Dat-Thanh Nguyen, Maliha Imami, Lin-Mei Zhao, Jing Wu, Ali Borhani, Alireza Mohseni, Mihir Khunte, Zhusi Zhong, Victoria Shi, Sophie Yao, Yuli Wang, Nicolas Loizou, Alvin C Silva, Paul J Zhang, Zishu Zhang, Zhicheng Jiao, Ihab Kamel, Wei-Hua Liao, Harrison Bai","doi":"10.1002/jmri.29819","DOIUrl":"10.1002/jmri.29819","url":null,"abstract":"<p><strong>Background: </strong>Deep learning (DL) models for accurate renal tumor characterization may benefit from multi-center datasets for improved generalizability; however, data-sharing constraints necessitate privacy-preserving solutions like federated learning (FL).</p><p><strong>Purpose: </strong>To assess the performance and reliability of FL for renal tumor segmentation and classification in multi-institutional MRI datasets.</p><p><strong>Study type: </strong>Retrospective multi-center study.</p><p><strong>Population: </strong>A total of 987 patients (403 female) from six hospitals were included for analysis. 73% (723/987) had malignant renal tumors, primarily clear cell carcinoma (n = 509). Patients were split into training (n = 785), validation (n = 104), and test (n = 99) sets, stratified across three simulated institutions.</p><p><strong>Field strength/sequence: </strong>MRI was performed at 1.5 T and 3 T using T2-weighted imaging (T2WI) and contrast-enhanced T1-weighted imaging (CE-T1WI) sequences.</p><p><strong>Assessment: </strong>FL and non-FL approaches used nnU-Net for tumor segmentation and ResNet for its classification. FL-trained models across three simulated institutional clients with central weight aggregation, while the non-FL approach used centralized training on the full dataset.</p><p><strong>Statistical tests: </strong>Segmentation was evaluated using Dice coefficients, and classification between malignant and benign lesions was assessed using accuracy, sensitivity, specificity, and area under the curves (AUCs). FL and non-FL performance was compared using the Wilcoxon test for segmentation Dice and Delong's test for AUC (p < 0.05).</p><p><strong>Results: </strong>No significant difference was observed between FL and non-FL models in segmentation (Dice: 0.43 vs. 0.45, p = 0.202) or classification (AUC: 0.69 vs. 0.64, p = 0.959) on the test set. For classification, no significant difference was observed between the models in accuracy (p = 0.912), sensitivity (p = 0.862), or specificity (p = 0.847) on the test set.</p><p><strong>Data conclusion: </strong>FL demonstrated comparable performance to non-FL approaches in renal tumor segmentation and classification, supporting its potential as a privacy-preserving alternative for multi-institutional DL models.</p><p><strong>Evidence level: </strong>4.</p><p><strong>Technical efficacy: </strong>Stage 2.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":"814-824"},"PeriodicalIF":3.5,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144093957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Current State of Evidence for Use of MRI in LI-RADS.","authors":"Ameya Madhav Kulkarni, Danielle Kruse, Kelly Harper, Eric Lam, Hoda Osman, Danyaal H Ansari, Umaseh Sivanesan, Mustafa R Bashir, Andreu F Costa, Matthew McInnes, Christian B van der Pol","doi":"10.1002/jmri.29748","DOIUrl":"10.1002/jmri.29748","url":null,"abstract":"<p><p>The American College of Radiology Liver Imaging Reporting and Data System (LI-RADS) is the preeminent framework for classification and risk stratification of liver observations on imaging in patients at high risk for hepatocellular carcinoma. In this review, the pathogenesis of hepatocellular carcinoma and the use of MRI in LI-RADS is discussed, including specifically the LI-RADS diagnostic algorithm, its components, and its reproducibility with reference to the latest supporting evidence. The LI-RADS treatment response algorithms are reviewed, including the more recent radiation treatment response algorithm. The application of artificial intelligence, points of controversy, LI-RADS relative to other liver imaging systems, and possible future directions are explored. After reading this article, the reader will have an understanding of the foundation and application of LI-RADS as well as possible future directions.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":"640-653"},"PeriodicalIF":3.5,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12335345/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143468313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Feasibility of MRI-Guided Transperineal Implantation of Microdevices for Drug Delivery and Response Assessment in Prostate Cancer.","authors":"Quinn Rainer, Kemal Tuncali, Wooseok Ahn, Fanni Viktoria Santa, Michelle Hirsch, Sharath Bhagavatula, Fumitaro Masaki, Clarissa Therese Young, Courtney Marlin, Samantha Martin, Destiny U Matthew, Filipe De Carvalho, Christine A Dominas, Benjamin V Stone, Clare Tempany, Oliver Jonas, Adam Stuart Kibel, Nobuhiko Hata","doi":"10.1002/jmri.29784","DOIUrl":"10.1002/jmri.29784","url":null,"abstract":"<p><strong>Background: </strong>Prostate cancer (PCa) treatment often involves systemic therapies with varying mechanisms of action, affecting individuals differently. Implantable microdevices (IMDs) are designed to test multiple drugs within a patient's tumor, but the feasibility of MRI-guided placement in PCa has not been evaluated.</p><p><strong>Purpose: </strong>To provide proof of concept for placing IMDs into lesions with MRI guidance to predict patient-specific responses to therapies.</p><p><strong>Study type: </strong>Prospective.</p><p><strong>Population: </strong>Fifteen participants undergoing prostatectomy for PCa.</p><p><strong>Field strength/sequence: </strong>3T MRI With T2-weighted (T2W).</p><p><strong>Assessment: </strong>In-bore MRI-targeted placement of IMDs was performed. Intra-procedural MRI scans were reviewed by a radiologist, using needle artifacts on T2W images to guide IMD placement. A genitourinary pathologist performed Gleason scoring around the IMDs. Drug response analysis included Enzalutamide + Nivolumab, Enzalutamide + Docetaxel, and single-agent Enzalutamide.</p><p><strong>Statistical tests: </strong>Mann-Whitney U test for continuous variables, p < 0.05 for significance.</p><p><strong>Results: </strong>Of 53 IMDs implanted into suspicious lesions in 14 participants, 48 (90%) were successfully placed within the lesions. The average distance from the needle tip to the tumor was 8.32 ± 4.02 mm. Larger lesion size (p = 0.009) and lower prostate imaging-reporting and data system score (p = 0.031) were significantly associated with successful IMD placement. Of the 53 IMDs, 49 (92.4%) were retrieved for histopathology and drug response analysis. In four participants, Gleason scores around the device were lower than preplacement biopsy in two and equal in two. Additionally, drug analysis in one patient demonstrated the feasibility of drug response analysis, revealing differences in apoptotic index, lymphocyte infiltration, dysplastic cell composition, and cellular profiles for each treatment. No complications or adverse events occurred.</p><p><strong>Conclusion: </strong>IMDs can be effectively and safely placed in prostate lesions using MRI guidance, with feasible histological and drug response analyses.</p><p><strong>Evidence level: </strong>2. Technical Efficacy: Stage 1.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":"707-718"},"PeriodicalIF":3.5,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12335932/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143996284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-Center, Multi-Vendor Validation of Simultaneous MRI-Based Proton Density Fat Fraction and R2* Mapping Using a Combined Proton Density Fat Fraction-R2* Phantom.","authors":"Jitka Starekova, David Rutkowski, Won C Bae, Hung Do, Ananth J Madhuranthakam, Vadim Malis, Sheng Qing Lin, Suraj Serai, Takeshi Yokoo, Scott B Reeder, Jean H Brittain, Diego Hernando","doi":"10.1002/jmri.29775","DOIUrl":"10.1002/jmri.29775","url":null,"abstract":"<p><strong>Background: </strong>Fat and iron deposition confound measurements of R2* and proton density fat fraction (PDFF), respectively, yet their combined impact on reproducibility is poorly understood.</p><p><strong>Purpose: </strong>To evaluate the multi-center, multi-vendor reproducibility of PDFF and R2* quantification using a PDFF-R2* phantom.</p><p><strong>Study type: </strong>Prospective multi-center, phantom study.</p><p><strong>Phantom: </strong>Commercial PDFF-R2* phantom with simultaneously controlled combination of PDFF (0%-30%) and R2* (50-600 s^-1) values.</p><p><strong>Field strength/sequence: </strong>1.5-T and 3-T, three-dimensional (3D) multi-echo, spoiled-gradient-echo sequences, in four different centers, each with a different vendor.</p><p><strong>Assessment: </strong>Two acquisition protocols were used, optimized for moderate R2* (Protocol 1) and high R2* (Protocol 2), respectively. The phantom was imaged multiple times at one of the centers to assess its stability.</p><p><strong>Statistical tests: </strong>Intraclass correlation coefficient (ICC), linear regression analysis, reproducibility coefficient (RDC) and repeatability coefficient (RC).</p><p><strong>Results: </strong>Excellent agreement was observed for PDFF measurements between centers, vendors, field strengths, and protocols (ICC = 0.97). Stratified by protocol, excellent agreement was observed, with ICC = 0.96 (RDC = 6.2%) for Protocol 1 and ICC = 0.99 (RDC = 3.8%) for Protocol 2. Increased variability in PDFF measurements was observed with increasing PDFF and especially with higher R2*. Excellent agreement was observed for R2* between centers, vendors, field strengths, and protocols (ICC = 0.99). Stratified by protocol, strong agreement was observed, with ICC = 0.988 (RDC = 66.7 s^-1) for Protocol 1 and ICC = 0.99 (RDC = 57.7 s^-1) for Protocol 2. Higher variability in R2* measurements was observed in vials with higher PDFF or R2*. Stability tests demonstrated an ICC = 1.0 for PDFF and R2*, and RC of 0.4% for PDFF and 12 s^-1 for R2*.</p><p><strong>Data conclusion: </strong>Excellent PDFF and R2* reproducibility was observed across centers, vendors, field strengths, and acquisition protocols. Reproducibility decreased slightly with increasing PDFF and R2*, especially for PDFF measurements in vials with high R2*.</p><p><strong>Evidence level: </strong>N/A.</p><p><strong>Technical efficacy: </strong>Stage 1.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":"800-811"},"PeriodicalIF":3.5,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12335339/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144011189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Broad Consent in Healthcare Research: What Is Efficient, What Is Right?","authors":"Jitka Starekova, Mark E Schweitzer","doi":"10.1002/jmri.70000","DOIUrl":"10.1002/jmri.70000","url":null,"abstract":"","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":"856-857"},"PeriodicalIF":3.5,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12335335/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144248271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cardiac Magnetic Resonance Elastography: Why Multiplex Approaches Hold the Key to Clinical Translation.","authors":"Johannes Castelein, Ronald J H Borra, Adam E Hansen","doi":"10.1002/jmri.70015","DOIUrl":"10.1002/jmri.70015","url":null,"abstract":"","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":"842-843"},"PeriodicalIF":3.5,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12335336/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144293869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Feasibility of Qualitative Evaluation and Quantitative T2 Mapping of Peripheral Nerves and Muscles Using GRAPPATINI.","authors":"A Z Lu, Y Lin, T Hilbert, Z Igbinoba, D Shakoor, X Cai, D B Sneag, E T Tan","doi":"10.1002/jmri.29803","DOIUrl":"10.1002/jmri.29803","url":null,"abstract":"<p><strong>Background: </strong>Quantitative T2 mapping holds promise for evaluating peripheral nerve and muscle disorders, but current methods lack speed and diagnostic feasibility. As a proof of concept, T2 mapping may be applied to assess the abnormality of the common peroneal nerve (CPN), leading to denervation of the tibialis anterior muscle and subsequent foot drop.</p><p><strong>Purpose: </strong>To evaluate the GRAPPATINI sequence (a combination of generalized autocalibrating partially parallel acquisition [GRAPPA] and model-based accelerated relaxometry by iterative non-linear inversion [MARTINI]) for qualitative assessment and quantitative T2 mapping in patients with foot drop. We hypothesized that GRAPPATINI would yield comparable qualitative image quality to conventional T2-weighted (T2w) turbo spin echo (TSE) while detecting T2 differences between abnormal and normal nerves and muscles.</p><p><strong>Study type: </strong>Prospective, cross-sectional study.</p><p><strong>Population: </strong>27 subjects (13 females; mean age: 54.4 years; range: 17-85 years) with clinical suspicion or diagnosis of foot drop.</p><p><strong>Field strength/sequence: </strong>3-Tesla, with GRAPPATINI T2 mapping (spin echo) and T2w-TSE Dixon for unilateral MRI of the knee region.</p><p><strong>Assessment: </strong>Three radiologists, blinded to the sequence type and clinical data, evaluated nerve and muscle visualization, diagnostic confidence, and abnormal signal detection. Quantitative T2 values were measured in six manually segmented muscles and in the CPN and tibial nerve.</p><p><strong>Statistical tests: </strong>Wilcoxon rank sum tests compared T2 values between abnormal and normal muscles/nerves (p < 0.05 indicates statistical significance). Intra-class correlation coefficients (ICCs) assessed interobserver agreement.</p><p><strong>Results: </strong>Qualitative scores for nerve visualization, muscle visualization, and diagnostic confidence were similar between GRAPPATINI and T2w-Dixon (p = 1.0). T2 values were significantly higher in all abnormal versus normal muscles (66.5 vs. 45.7 ms) and in all abnormal versus normal nerves (66.8 vs. 60.5 ms).</p><p><strong>Data conclusion: </strong>GRAPPATINI provided comparable qualitative image quality to T2w imaging while enabling quantitative T2 mapping to detect abnormalities in muscles and nerves in patients with foot drop.</p><p><strong>Evidence level: </strong>2.</p><p><strong>Technical efficacy: </strong>Stage 2.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":"781-789"},"PeriodicalIF":3.5,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144025146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimated Brain Age in Healthy Aging and Across Multiple Neurological Disorders.","authors":"Li Chai, Jun Sun, Zhizheng Zhuo, Ren Wei, Xiaolu Xu, Yunyun Duan, Decai Tian, Yutong Bai, Ningnannan Zhang, Haiqing Li, Yuxin Li, Yongmei Li, Fuqing Zhou, Jun Xu, James H Cole, Frederik Barkhof, Jianguo Zhang, Huaguang Zheng, Yaou Liu","doi":"10.1002/jmri.29667","DOIUrl":"10.1002/jmri.29667","url":null,"abstract":"<p><strong>Background: </strong>The brain aging in the general population and patients with neurological disorders is not well understood.</p><p><strong>Purpose: </strong>To characterize brain aging in the above conditions and its clinical relevance.</p><p><strong>Study type: </strong>Retrospective.</p><p><strong>Population: </strong>A total of 2913 healthy controls (HC), with 1395 females; 331 multiple sclerosis (MS); 189 neuromyelitis optica spectrum disorder (NMOSD); 239 Alzheimer's disease (AD); 244 Parkinson's disease (PD); and 338 cerebral small vessel disease (cSVD).</p><p><strong>Field strength/sequence: </strong>3.0 T/Three-dimensional (3D) T1-weighted images.</p><p><strong>Assessment: </strong>The brain age was estimated by our previously developed model, using a 3D convolutional neural network trained on 9794 3D T1-weighted images of healthy individuals. Brain age gap (BAG), the difference between chronological age and estimated brain age, was calculated to represent accelerated and resilient brain conditions. We compared MRI metrics between individuals with accelerated (BAG ≥ 5 years) and resilient brain age (BAG ≤ -5 years) in HC, and correlated BAG with MRI metrics, and cognitive and physical measures across neurological disorders.</p><p><strong>Statistical tests: </strong>Student's t test, Wilcoxon test, chi-square test or Fisher's exact test, and correlation analysis. P < 0.05 was considered statistically significant.</p><p><strong>Results: </strong>In HC, individuals with accelerated brain age exhibited significantly higher white matter hyperintensity (WMH) and lower regional brain volumes than those with resilient brain age. BAG was significantly higher in MS (10.30 ± 12.6 years), NMOSD (2.96 ± 7.8 years), AD (6.50 ± 6.6 years), PD (4.24 ± 4.8 years), and cSVD (3.24 ± 5.9 years) compared to HC. Increased BAG was significantly associated with regional brain atrophy, WMH burden, and cognitive impairment across neurological disorders. Increased BAG was significantly correlated with physical disability in MS (r = 0.17).</p><p><strong>Data conclusion: </strong>Healthy individuals with accelerated brain age show high WMH burden and regional volume reduction. Neurological disorders exhibit distinct accelerated brain aging, correlated with impaired cognitive and physical function.</p><p><strong>Level of evidence: </strong>4 TECHNICAL EFFICACY: Stage 2.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":"869-879"},"PeriodicalIF":3.5,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142716147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Systematic Review of the Variability of Ventilation Defect Percent Generated From Hyperpolarized Noble Gas Pulmonary Magnetic Resonance Imaging.","authors":"Vanessa M Diamond, Laura C Bell, Jeffrey N Bone, Bastiaan Driehuys, Martha Menchaca, Giles Santyr, Sarah Svenningsen, Robert P Thomen, Helen Marshall, Laurie J Smith, Guilhem J Collier, Jim M Wild, Jason C Woods, Sean B Fain, Rachel L Eddy, Jonathan H Rayment","doi":"10.1002/jmri.29746","DOIUrl":"10.1002/jmri.29746","url":null,"abstract":"<p><p>Hyperpolarized (HP) gas pulmonary MR ventilation images are typically quantified using ventilation defect percent (VDP); however, the test-retest variability of VDP has not been systematically established in multi-center trials. Herein, we perform a systematic review of the test-retest literature on the variability of VDP, and similar metrics, generated from HP MRI. This review utilizes the Medline, EMBASE, and EBM Reviews databases and includes studies that assessed the variability of HP MRI VDP. The protocol was registered to PROSPERO: CRD42022328535. Imaging techniques and statistical analysis characteristics were extracted and used to group studies to evaluate the overall ability to pool data across grouped studies. The ability to pool data to provide systematic evidence was assessed using a modified COSMIN tool. A total of 22 studies with 37 distinct aims for repeated HP MRI acquisition or quantification were included. Studies were grouped into six categories based on HP gas and analysis type: repeated imaging (¹²⁹Xe n = 13, ³He n = 12), interobserver repeated analysis (¹²⁹Xe n = 4, ³He n = 4) or intraobserver repeated analysis (¹²⁹Xe n = 1, ³He n = 2). Studies assessed variability using a variety of statistical tests including absolute difference, percent coefficient of variation, Bland-Altman limits of agreement, coefficient of reproducibility, or the intra-class correlation. Individual studies generally reported low variability of VDP (ICC range: 0.5-1.0; Bland-Altman bias range: -6.9-20%), but there was an overall inability to pool data and provide a meta-analysis due to methodological inconsistencies and small sample size. Overall, we found that VDP has low variability in most studies. However, inconsistent image acquisition and quantification methodologies between studies limits direct comparability and precludes grouping of study data for meta-analyses. Despite early efforts to standardize HP MRI acquisition, further work is necessary to standardize VDP quantification to allow broader validation and clinical implementation. Evidence Level: 2 Technical Efficacy: Stage 3.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":"625-639"},"PeriodicalIF":3.5,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12335342/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143515866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MR and Ultrasound for Liver Fat Assessment in Children: Techniques and Supporting Evidence.","authors":"Suraj D Serai, Manish Dhyani, Saubhagya Srivastava, Jonathan R Dillman","doi":"10.1002/jmri.29756","DOIUrl":"10.1002/jmri.29756","url":null,"abstract":"<p><p>Hepatic steatosis is a common imaging finding that can be a sign of chronic liver disease, most often associated with metabolic dysfunction-associated steatotic liver disease (MASLD). Imaging techniques for evaluating steatosis range from basic qualitative assessments to advanced and highly accurate quantitative metrics. Among these, MRI-based proton density fat fraction (PDFF) is widely regarded as a reliable and precise imaging biomarker for quantifying liver steatosis. Additionally, multiple ultrasound platforms now offer quantitative assessments of hepatic steatosis. These methods include attenuation coefficient, speed of sound, backscatter, or other multiparametric approaches such as ultrasound-derived fat fraction (UDFF) which combines attenuation and backscatter quantification. Newer and upcoming quantitative ultrasound methods include acoustic structure quantification (ASQ) and tissue scatter distribution imaging (TSI). Therefore, ultrasound-based liver fat measurements could potentially serve as an effective screening tool in certain clinical settings, such as suspected MASLD. In this review, we describe how, why, and when to use MRI- and ultrasound-based fat quantification techniques for assessing liver steatosis in children. We discuss practical strategies for adapting and optimizing these methods in pediatric settings, considering clinical indications, patient preparation, equipment needs, acquisition techniques, potential pitfalls, and confounding factors. Additionally, guidance is provided for interpretation and reporting, along with illustrative case examples. Evidence Level: N/A Technical Efficacy: Stage 5.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":"691-706"},"PeriodicalIF":3.5,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12335346/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143557111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}