Journal of Magnetic Resonance Imaging最新文献

{"title":"Assessment of Small Vessel Density Changes in Cerebral Autosomal Dominant Arteriopathy With Subcortical Infarcts and Leukoencephalophy (CADASIL) by High-Resolution Black-Blood MRI.","authors":"Zidong Yang, Fanhua Guo, Steve Mendoza, Ziyang Huang, Yingying Li, Yunqing Ying, Xin Cheng, Qi Yang, Yonggang Shi, Danny J J Wang","doi":"10.1002/jmri.70096","DOIUrl":"10.1002/jmri.70096","url":null,"abstract":"<p><strong>Background: </strong>Direct assessments of cerebral small vessels in Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL) remain a challenge.</p><p><strong>Purpose: </strong>To investigate changes of cerebral small vessels in CADASIL using iso-0.5 mm black-blood MRI.</p><p><strong>Study type: </strong>Case control study.</p><p><strong>Population: </strong>Thirty-six genetically confirmed CADASIL patients (23 female, 43 ± 12.48 years) and 35 matched healthy controls (27 female, 40 ± 11.57 years).</p><p><strong>Field strength/sequence: </strong>3T using a T1-weighted turbo spin-echo with variable flip angles sequence.</p><p><strong>Assessment: </strong>Vessel density images (VDIs) were derived from black-blood MRI by using a semi-automatic pipeline with a Jerman filter. The differences in VDI were assessed between CADASIL and control groups. The relationships between changes in VDI and cognitive performance and disease burden were studied in the CADASIL group.</p><p><strong>Statistical tests: </strong>Two-tailed independent samples t-tests were employed to assess the difference in VDI between CADASIL and control groups. Generalized linear mixed-effect models were used to assess the associations of VDI with cognitive performance and disease burden. Voxel-wise analyses were performed to further explore the associations of regional VDI with cognitive performance and disease burden after FDR correction.</p><p><strong>Results: </strong>Reduced mean VDI was found in gray matter of CADASIL patients (1.31 ± 0.06) compared to controls (1.35 ± 0.03), which was significantly associated with lower MoCA scores (β = 52.89, SE = 12.99, 95% CI [26.38, 79.40]), and higher cerebral small vessel disease (cSVD) burden scores (β = -14.34, SE = 3.22, 95% CI [-20.91, -7.76]) in CADASIL patients. Voxel-wise analyses revealed reduced regional VDI in regions of the temporal pole, insula, cingulate cortex, and orbitofrontal cortex in CADASIL patients.</p><p><strong>Data conclusion: </strong>The VDI technique based on high-resolution black-blood MRI demonstrated changes in regional VDI in CADASIL patients and offers a noninvasive imaging tool to advance the understanding of the mechanisms underlying cSVD.</p><p><strong>Evidence level: </strong>3.</p><p><strong>Technical efficiency: </strong>Stage 2.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12462767/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144957191","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":"Adaptive MRI With AI-Guided Triage in Breast Cancer Screening: Clarifying the Terminology, Methodology, and Clinical Relevance.","authors":"Deniz Esin Tekcan Sanli, Ahmet Necati Sanli","doi":"10.1002/jmri.70099","DOIUrl":"https://doi.org/10.1002/jmri.70099","url":null,"abstract":"","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144957239","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":"Saturated Multi-Delay Renal Arterial Spin Labeling Technique at 5 T MR: A Comparative Study With 3 T.","authors":"Xinyu Tong, Chen Chen, Zihan Ning, Rui Shen, Ne Yang, Shuheng Zhang, Shuo Chen, Zuo-Xiang He, Xihai Zhao","doi":"10.1002/jmri.70079","DOIUrl":"https://doi.org/10.1002/jmri.70079","url":null,"abstract":"<p><strong>Background: </strong>The feasibility of renal multi-delay arterial spin labeling (ASL) imaging at 5 T remains unclear.</p><p><strong>Purpose: </strong>To evaluate the feasibility of the saturated multi-delay renal ASL (SAMURAI) sequence at 5 T by comparing image quality and perfusion quantification with 3 T.</p><p><strong>Study type: </strong>Prospective, cross-sectional.</p><p><strong>Population: </strong>Twenty healthy volunteers (28.6 ± 7.8 years, 9 males) for primary comparison; 6 volunteers (24.2 ± 1.5 years, 5 males) for reproducibility study at 5 T.</p><p><strong>Field strength/sequence: </strong>SAMURAI sequence at 3 T and 5 T.</p><p><strong>Assessment: </strong>The SAMURAI sequence was optimized at 5 T with renal-specific B1 shimming and an optimized saturation scheme by numerical simulation. Each participant underwent 3 T and 5 T scans in randomized order. Cortical T1 value, renal blood flow (RBF), arterial and tissue bolus arrival times were measured. The signal-to-noise ratio (SNR) and cortico-medullary contrast-to-noise ratio (CNR) were calculated from perfusion-weighted images. Short-term repeatability (n = 20) and reproducibility (n = 6) tests of quantitative parameters were performed at 5 T.</p><p><strong>Statistical tests: </strong>Differences and agreement between 3 T and 5 T were analyzed using the Wilcoxon signed-rank test, intraclass correlation coefficients (ICC) and linear correlation analysis (R²). The repeatability at 5 T was assessed by ICC. A p < 0.05 was considered statistically significant.</p><p><strong>Results: </strong>Renal cortical T1 values were significantly higher at 5 T than 3 T (1417.9 ± 75.7 ms vs. 1184.2 ± 84.4 ms), with R² = 0.509. Cortical RBF showed an insignificant difference between 5 T and 3 T: 324.4 (interquartile range [IQR]: 310.1-366.4) vs. 329.7 (IQR: 309.5-368.1) [mL/100 g/min] (p = 0.333), with R² = 0.914. 5 T showed significantly higher mean SNR (4.6 vs. 3.9) and CNR (3.2 vs. 2.0) than 3 T across all inversion times, with excellent repeatability and reproducibility of quantitative parameters (ICC = 0.855-0.973).</p><p><strong>Data conclusions: </strong>Renal quantitative imaging with SAMURAI sequence at 5 T is feasible and repeatable, with significantly higher SNR and CNR than 3 T and strong interfield agreement of cortical RBF measurements.</p><p><strong>Level of evidence: 2: </strong></p><p><strong>Technical efficacy stage: </strong>1.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144957249","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":"Resilience and Brain Changes in Long-Term Ayahuasca Users: Insights From Psychometric and fMRI Pattern Recognition.","authors":"Lucas Rego Ramos, Orlando Fernandes, Tiago Arruda Sanchez","doi":"10.1002/jmri.70063","DOIUrl":"https://doi.org/10.1002/jmri.70063","url":null,"abstract":"<p><strong>Background: </strong>Ayahuasca is an Amazonian psychedelic brew that contains dimethyltryptamine (DMT) and beta carbolines. Prolonged use has shown changes in cognitive-behavioral tasks, and in humans, there is evidence of changes in cortical thickness and an increase in neuroplasticity factors that could lead to modifications in functional neural circuits.</p><p><strong>Purpose: </strong>To investigate the long-term effects of Ayahuasca usage through psychometric scales and fMRI data related to emotional processing using artificial intelligence tools.</p><p><strong>Study type: </strong>Retrospective Cross-sectional, case-control study.</p><p><strong>Subjects: </strong>38 healthy male participants (19 long-term Ayahuasca users and 19 non-user controls).</p><p><strong>Field strength/sequence: </strong>1.5 Tesla; gradient-echo T2*-weighted echo-planar imaging sequence during an implicit emotion processing task.</p><p><strong>Assessment: </strong>Participants completed standardized psychometric scales including the Ego Resilience Scale (ER89). During fMRI, participants performed a gender judgment task using faces with neutral or aversive (disgust/fear) expressions. Whole-brain fMRI data were analyzed using multivariate pattern recognition.</p><p><strong>Statistical tests: </strong>Group comparisons of psychometric scores were performed using Student's t-tests or Mann-Whitney U tests based on normality. Multivariate pattern classification and regression were performed using machine learning algorithms: Multiple Kernel Learning (MKL), Support Vector Machine (SVM), and Gaussian Process Classification/Regression (GPC/GPR), with k-fold cross-validation and permutation testing (n = 100-1000) to assess model significance (α = 0.05).</p><p><strong>Results: </strong>Ayahuasca users (mean = 43.89; SD = 5.64) showed significantly higher resilience scores compared to controls (mean = 39.05; SD = 5.34). The MKL classifier distinguished users from controls with 75% accuracy (p = 0.005). The GPR model significantly predicted individual resilience scores (r = 0.69).</p><p><strong>Data conclusion: </strong>Long-term Ayahuasca use may be associated with altered emotional brain reactivity and increased psychological resilience. These findings support a neural patterns consistent with long-term adaptations of Ayahuasca detectable via fMRI and machine learning-based pattern analysis.</p><p><strong>Evidence level: </strong>4.</p><p><strong>Technical efficacy: </strong>Stage 1.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144957266","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":"Reply to “Letter to Editor by Dr. Steckner Regarding ‘Induction of Extremely Severe Nausea via Vestibular Activation on a 7 Tesla MRI Scanner’ by Fagan et al.”","authors":"Andrew J. Fagan","doi":"10.1002/jmri.70085","DOIUrl":"10.1002/jmri.70085","url":null,"abstract":"","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":"62 4","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144957254","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":"Assessing the Diagnostic Value of MRI T1rho Mapping in Predicting Molecular Prognostic Biomarkers and Subtypes of Breast Cancer.","authors":"Lanqing Yang, Yi Zeng, Sixian Hu, Yi Xiao, Xiaoyong Zhang, Xiaoxiao Zhang, Chunchao Xia","doi":"10.1002/jmri.70070","DOIUrl":"10.1002/jmri.70070","url":null,"abstract":"<p><strong>Background: </strong>Prognostic factors and molecular subtypes are important in treatment planning and predicting response to therapy in breast cancer, and the exploration of noninvasive imaging methods to characterize breast cancer has been ongoing.</p><p><strong>Purpose: </strong>To evaluate the use of T1rho mapping in predicting the status of prognostic biomarkers and molecular subtypes of breast cancer.</p><p><strong>Study type: </strong>Prospective.</p><p><strong>Subjects: </strong>Ninety One women with breast tumors.</p><p><strong>Field strength/sequence: </strong>3T, T1 rho prepared balanced turbo field echo sequence.</p><p><strong>Assessment: </strong>Mean T1rho values were compared between positive and negative status of prognostic biomarkers [estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and proliferation index (Ki-67)] and molecular subtypes.</p><p><strong>Statistical tests: </strong>Independent t test, one-way analysis of variance, Kruskal-Wallis test, chi-square test, Fisher exact test, and receiver operating characteristic (ROC) analysis.</p><p><strong>Results: </strong>Mean T1rho values were significantly higher in ER-negative compared to ER-positive tumors (70 ± 6.769 vs. 55 ± 10.791 ms), in PR-negative compared to PR-positive tumors (68.48 ± 9.563 vs. 60.46 ± 10.099 ms), and in high Ki-67 proliferation compared to low Ki-67 proliferation tumors (66.59 ± 8.994 vs. 57.77 ± 11.501 ms). Significant negative correlations were observed between ER and PR statuses and T1rho values (r_s = 0.416 and 0.392, respectively). The Ki-67 status was significantly positively correlated with T1rho values (r_s = 0.369). The Luminal A subtype had a significantly lower T1rho value than other subtypes (56.46 ± 10.553 vs. 66.58 ± 9.204 ms). The Luminal B subtype had significantly lower T1rho values than the triple-negative (TN) subtype (63.957 ± 9.794 vs. 72.237 ± 8.229 ms). The TN subtype had a significantly higher T1rho value than luminal subtypes (72.237 ± 8.229 vs. 62.903 ± 10.289 ms). The T1rho values had good diagnostic performance in identifying Luminal A and TN breast cancers with areas under the ROC curve of 0.767 and 0.776.</p><p><strong>Data conclusion: </strong>T1rho mapping has the potential to be a non-invasive imaging biomarker for evaluating the prognostic biomarkers and molecular subtypes of breast cancer.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144882927","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":"Development and Validation of a Preoperative MRI Habitat Radiomics Model to Predict Variant Histology in Bladder Cancer.","authors":"Lingmin Kong, Yanjin Qin, Hui Li, Qian Cai, Keyi Zhang, Jianqiu Huang, Jianpeng Li, Yong Li, Yan Guo, Huanjun Wang","doi":"10.1002/jmri.70069","DOIUrl":"10.1002/jmri.70069","url":null,"abstract":"<p><strong>Background: </strong>Bladder cancer (BCa) with variant histology (VH) is aggressive, leading to poor prognosis and resistance to neoadjuvant treatment (NAT). Preoperative identification of VH may be important for informing treatment options.</p><p><strong>Purpose: </strong>To develop and validate a multiparametric MRI-based ensemble model to identify VH in BCa and explore its association with disease-free survival (DFS) and NAT response.</p><p><strong>Study type: </strong>Retrospective.</p><p><strong>Subjects: </strong>Six hundred twenty patients with pathologically confirmed BCa (median age, 65 years [IQR: 56, 73], 145 female) from four centers who underwent preoperative MRI, were divided into a training (n = 311), internal validation (n = 54) from Center 1, and three external validation datasets (n = 85, 68, and 102, respectively). Two additional cohorts, DFS (n = 75) and NAT (n = 69) cohorts, were collected from Center 1 to evaluate prognosis.</p><p><strong>Field strength/sequence: </strong>3T, non-fat suppressed T2-weighted imaging using fast spin echo, diffusion-weighted imaging using single-shot echo planar imaging, and T1-weighted dynamic contrast-enhanced sequence using 3D gradient echo sequence.</p><p><strong>Assessment: </strong>Habitat, radiomic, clinical, clinical-radiomic based, and the VHRisk Score (VHRiS) models were constructed for evaluating VH. The prognostic value of VHRiS for DFS and pathological complete response (pCR) rate was further evaluated.</p><p><strong>Statistical tests: </strong>Mann-Whitney U test, t-test, ROC analysis (AUC), Kaplan-Meier curves, log-rank test, and SHapley Additive exPlanations (SHAP) analysis.</p><p><strong>Results: </strong>The VHRiS model demonstrated favorable accuracy (AUCs: training, 0.971; internal validation, 0.895; external validation, 0.898-0.974). Low-risk patients (VHRiS ≥ 0.863) exhibited significantly longer DFS than high-risk patients (4.20 months vs. 3.08 months) in the DFS cohort (median follow-up period: 13.19 months [IQR: 6.54, 31.91]). They also showed a higher pCR rate than high-risk patients (64% vs. 33%) in the NAT cohort.</p><p><strong>Data conclusions: </strong>The VHRiS model may be a robust tool for identifying VH, and may offer a potential method for risk stratification and prognosis prediction in patients with BCa.</p><p><strong>Levels of evidence: </strong>4.</p><p><strong>Technical efficacy stage: </strong>2.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144882931","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":"Editorial for \"Tumor Habitats Based on Multiparametric MRI Distinguish Atypical Glioblastoma From Primary Central Nervous System Lymphoma: Imaging-Pathologic Correlation\".","authors":"Shanshan Liu, Qiang Fang","doi":"10.1002/jmri.70092","DOIUrl":"https://doi.org/10.1002/jmri.70092","url":null,"abstract":"","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144957188","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":"Time-Dependent Diffusion MRI-Based Microstructural Mapping for Characterizing HER2-Zero, -Low, -Ultra-Low, and -Positive Breast Cancer.","authors":"Xiaoxia Wang, Yao Huang, Ying Cao, Huifang Chen, Xueqin Gong, Xiaosong Lan, Jiuquan Zhang, Zhaoxiang Ye","doi":"10.1002/jmri.70074","DOIUrl":"10.1002/jmri.70074","url":null,"abstract":"<p><strong>Background: </strong>With breast cancer treatment advances, accurate non-invasive methods are needed to distinguish its human epidermal growth factor receptor 2 (HER2) subtypes. Recently developed time-dependent diffusion MRI (t_d-dMRI) has potential in characterizing cellular tissue microstructures in breast cancer. However, its role in identifying HER2 subtypes is unknown.</p><p><strong>Purpose: </strong>To investigate the feasibility of t_d-dMRI-based microstructural histogram parameters for characterizing properties of four HER2 subtypes in breast cancer.</p><p><strong>Study type: </strong>Prospective.</p><p><strong>Population: </strong>Four hundred ninety-five participants with invasive breast cancer (18 HER2-zero, 49 -ultralow, 243 -low and 185 -positive).</p><p><strong>Field strength/sequence: </strong>3-T, oscillating gradient spin-echo (OGSE) and pulsed gradient spin-echo (PGSE) sequences for t_d-dMRI.</p><p><strong>Assessment: </strong>The HER2 status was categorized as HER2-zero, -ultralow, -low, or -positive by immunohistochemistry and fluorescence in situ hybridization. The t_d-dMRI data were fitted using the IMPULSED method. Tumors were identified on dynamic contrast-enhanced MRI and delineated on the PGSE image (b = 0 s/mm²). Forty-nine histogram parameters were extracted from the tumor, including four microstructural maps (diameter, intracellular fraction, extracellular diffusivity, cellularity) and three apparent diffusion coefficient maps.</p><p><strong>Statistical tests: </strong>Histogram parameters were analyzed via one-way analysis of variance followed by pairwise t tests with Bonferroni correction. The Boruta method selected the significant parameters for each HER2 subtype. The predictive performance was assessed through area under the curve (AUC). A p value < 0.05 was considered statistically significant.</p><p><strong>Results: </strong>Thirty-two histogram parameters showed significant differences among the four HER2 subgroups. Four models were constructed, which achieved high performance for distinguishing HER2-positive versus negative (AUC of 0.85), HER2-positive versus low (AUC of 0.87), and HER2-low versus immunohistochemistry 0 (AUC of 0.81), along with moderate performance for distinguishing HER2-zero versus -ultralow (AUC of 0.77).</p><p><strong>Data conclusion: </strong>Selected t_d-dMRI-derived histogram parameters may be applicable for identifying HER2 subtypes in breast cancer.</p><p><strong>Level of evidence: 1: </strong></p><p><strong>Technical efficacy stage: </strong>2.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144882935","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":"MR Electrical Properties Tomography Acquisitions: A Guideline From the ISMRM Electro-Magnetic Tissue Properties Study Group.","authors":"Stefano Mandija, Cornelis A T van den Berg, Ilias Giannakopoulos, Zhongzheng He, Yusuf Ziya Ider, Kyu-Jin Jung, Nitish Katoch, Dong-Hyun Kim, Riccardo Lattanzi, Paul Soullié, Ulrich Katscher","doi":"10.1002/jmri.70057","DOIUrl":"10.1002/jmri.70057","url":null,"abstract":"","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144882933","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}