Journal of Magnetic Resonance Imaging最新文献

{"title":"Association Between the Systemic Immune-Inflammation Index and Aneurysmal Wall Enhancement on High-Resolution Magnetic Resonance Vessel Wall Imaging in Unruptured Intracranial Aneurysms.","authors":"Jiwan Huang, Runze Ge, Caihong Li, Yuxin Li, Zhuohua Wen, Chi Huang, Anqi Xu, Mengshi Huang, Jiancheng Lin, Hao Yuan, Hongyu Shi, Can Li, Lele Dai, Wenxin Chen, Xiru Zhang, Yi Tu, Canzhao Liu, Shuyin Liang, Yiming Bi, Wenchao Liu, Shixing Su, Xin Zhang, Xifeng Li, ZhiBo Wen, Chuanzhi Duan, Xin Feng","doi":"10.1002/jmri.70307","DOIUrl":"https://doi.org/10.1002/jmri.70307","url":null,"abstract":"<p><strong>Background: </strong>Inflammation is a critical driver of intracranial aneurysm (IA) instability. The systemic immune-inflammation index (SII), a novel composite inflammatory biomarker, may reflect the local mural changes observed on vessel wall imaging (VWI).</p><p><strong>Purpose/hypothesis: </strong>To investigate the association between the SII and aneurysmal wall enhancement (AWE) on high-resolution vessel wall imaging (HRVWI), and to evaluate SII as a potential biomarker for aneurysm instability.</p><p><strong>Study type: </strong>Prospective cross-sectional study.</p><p><strong>Population: </strong>Four hundred and eighteen intracranial aneurysms in 311 patients (65.3% female, median age 58.0 years) underwent HRVWI. A sub-cohort of 67 patients with 84 aneurysms was included for longitudinal analysis of aneurysm growth (median follow-up 7.0 months).</p><p><strong>Field strength/sequence: </strong>Field strength/sequence: A 3.0T MR scanner; 3D time-of-flight magnetic resonance angiography (TOF-MRA); 3D black-blood T1-weighted volumetric turbo spin echo acquisition (T1-VISTA); and post-contrast vessel wall imaging using a 3D fast field echo sequence.</p><p><strong>Assessment: </strong>AWE defined as aneurysm-to-pituitary stalk contrast ratio (CR_stalk) ≥ 0.60. SII was calculated from admission blood counts as (platelet count * neutrophil count)/(lymphocyte count * 1000).</p><p><strong>Statistical tests: </strong>Multivariable logistic regression and propensity score matching evaluated the association between SII and AWE. Longitudinal analysis was performed using Firth's logistic regression. Subgroup analyses were stratified by clinical and aneurysmal characteristics. p < 0.05 was considered significant.</p><p><strong>Results: </strong>AWE was present in 142/418 (34.0%) aneurysms. In multivariable analysis, elevated SII was independently associated with AWE (odds ratio [OR] = 1.93). This association remained significant after PSM (median SII: 0.60 in AWE group vs. 0.42 in non-AWE group). SII was also independently associated with aneurysm growth in the longitudinal sub-cohort (OR = 20.519). Subgroup analysis showed a significant interaction with aneurysm location, with the strongest association in the internal carotid artery (OR = 3.55; 95% CI: 1.63-7.71).</p><p><strong>Data conclusion: </strong>Elevated SII is independently associated with the presence of AWE and aneurysm growth.</p><p><strong>Evidence level: </strong>3.</p><p><strong>Technical efficacy: </strong>Stage 2.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147580959","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 \"Association Between the Systemic Immune-Inflammation Index and Aneurysmal Wall Enhancement on High-Resolution Magnetic Resonance Vessel Wall Imaging in Unruptured Intracranial Aneurysms\".","authors":"Lei Wu, Shiqi Huang, Chengcheng Zhu","doi":"10.1002/jmri.70311","DOIUrl":"https://doi.org/10.1002/jmri.70311","url":null,"abstract":"","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147581256","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":"Comparison of Myeloarchitectonic Feature Recognition of the Primary Visual Cortex at 7 T Relative to 3 T MRI.","authors":"Sergio Valencia, Emil Barkovich, Fedel Machado-Rivas, Phillip L Pearl, Simon K Warfield, Onur Afacan, Camilo Jaimes","doi":"10.1002/jmri.70312","DOIUrl":"https://doi.org/10.1002/jmri.70312","url":null,"abstract":"<p><strong>Background: </strong>The stria of Gennari (SoG) is a densely myelinated band within layer IVb of the primary visual cortex (V1) and represents the only cortical laminar structure visible macroscopically in vivo. Ultrahigh-field MRI may improve its detection and conspicuity.</p><p><strong>Purpose: </strong>To quantitatively and qualitatively compare the in vivo appearance of the SoG at 3 versus 7 T using matched high-resolution T₂-weighted fast spin-echo MRI.</p><p><strong>Study type: </strong>Prospective.</p><p><strong>Population: </strong>A total of 12 subjects (6 female, 6 male; median age, 17 years; range, 15-24 years) with pediatric-onset epilepsy.</p><p><strong>Field strength/sequence: </strong>3 and 7 T MRI, T₂-weighted fast spin-echo, acquired within 1 month of each other.</p><p><strong>Assessment: </strong>Cortical line profiles per subject were extracted orthogonally to the calcarine sulcus in V1. Quantitative metrics included peak-valley distance, Δ-signal (peak-valley difference), and contrast ratio (CR). Two blinded neuroradiologists and a radiologist independently rated SoG conspicuity using a 5-point Likert scale.</p><p><strong>Statistical tests: </strong>McNemar's test compared detection rates; paired t-tests or Wilcoxon signed-rank tests compared quantitative metrics; reader preferences were analyzed using Wilcoxon tests; inter-reader agreement was assessed using weighted Cohen's κ. No multiple-comparison correction was applied (α = 0.05).</p><p><strong>Results: </strong>SoG-consistent valleys were detected in 31% of profiles at 3 T and 65% at 7 T, significantly. Peak-valley distance remained stable across field strengths (0.45 ± 0.06 depth units; p = 0.37). Mean Δ-signal (33.5 vs. 36.1; p = 0.81) and contrast ratio (0.013 vs. 0.000; p = 0.54) did not differ significantly. Both readers demonstrated a strong preference for 7 T images (pseudo-median +1 to +1.5; significant), with fair inter-reader agreement (κ = 0.36).</p><p><strong>Data conclusion: </strong>The SoG can be visualized in vivo at both 3 and 7 T, with higher detection frequency and greater subjective conspicuity at 7 T. Quantitative laminar metrics remained stable across field strengths, suggesting that improved detectability at 7 T likely reflects enhanced spatial definition rather than measurable changes in signal contrast.</p><p><strong>Level of evidence: 2: </strong></p><p><strong>Technical efficacy: </strong>Stage 2.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147581059","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 Comparative Study of IVIM-MRI Fitting Techniques in Glioma Grading: Conventional, Bayesian, and Voxel-Wise and Spatially-Aware Deep Learning Approaches.","authors":"Misha P T Kaandorp, Andras Jakab, Christian Federau, Peter T While","doi":"10.1002/jmri.70301","DOIUrl":"https://doi.org/10.1002/jmri.70301","url":null,"abstract":"<p><strong>Background: </strong>Intravoxel incoherent motion (IVIM) analysis of diffusion-weighted MRI (DWI) provides microvascular perfusion and diffusion information. However, parameter estimation is limited by noise sensitivity, variability across fitting methods, and lack of standardization. Deep-learning (DL)-based approaches, particularly spatially-aware transformers, may improve robustness, but their clinical utility remains unexplored.</p><p><strong>Purpose: </strong>To evaluate conventional, Bayesian, and DL-based IVIM fitting methods in glioma patients, focusing on tumor grading accuracy.</p><p><strong>Study type: </strong>Retrospective.</p><p><strong>Population: </strong>Fractal-noise-based simulations and preoperative DWI from 20 glioma patients (5 Grade-2, 3 Grade-3, 12 Grade-4).</p><p><strong>Sequence: </strong>Spin-echo echo-planar DWI, 16 b values (0-900 s/mm²), three orthogonal directions, 3 T.</p><p><strong>Assessment: </strong>IVIM parameter maps were compared across least squares (LSQ), segmented (SEG), Bayesian shrinkage (BSP), and spatial-homogeneity (FBM) priors, and DL-based methods, including IVIM-NET, novel spatially-aware transformers (NATTEN-17), and a refined version (SA-17). Simulation accuracy was evaluated using median absolute percentage error (MDAPE) and bias using median percentage error. In vivo data were visually assessed by the authors for noise suppression and structural preservation. Whole-tumor diffusion coefficient (D), pseudo-diffusion coefficient (D*), and signal fraction (f) values were evaluated across tumor grades and for differentiating Grade-4 from Grade-2/3 tumors.</p><p><strong>Statistical tests: </strong>Mann-Whitney U tests for group comparisons; tumor grading performance using receiver operating characteristic-area under the curve (ROC-AUC), and pairwise AUC differences using the DeLong test.</p><p><strong>Significance: </strong>p < 0.05.</p><p><strong>Results: </strong>Transformer-based methods achieved superior simulation accuracy, with significantly lower MDAPE for f and D* than all other approaches: NATTEN-17 (5.91%, 13.31%), SA-17 (7.73%, 13.66%), LSQ (21.95%, 54.34%), SEG (17.10%, 21.27%), BSP (12.35%, 22.79%), FBM (16.32%, 20.67%). In vivo, they provided superior visual quality and tumor delineation in f and D* maps, producing seemingly denoised versions of LSQ, while preserving tumor heterogeneity. The spatially-aware transformers yielded consistently the highest ROC-AUC values, particularly for D* (SA-17: 0.78), significantly outperforming LSQ (0.62), SEG (0.58), FBM (0.62), and IVIM-NET (0.71).</p><p><strong>Data conclusion: </strong>Transformer-based model fitting has the potential to provide clinically valuable IVIM parameter estimates and improved tumor grading accuracy.</p><p><strong>Evidence level: </strong>3.</p><p><strong>Technical efficacy: </strong>Stage 2.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147581514","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 \"Benchmarking Hybrid CNN-Transformer vs. Pure Transformer Architectures for Accelerated Hyperpolarized 129Xe MRI Reconstruction\".","authors":"Michael L Wood, Brandon Zanette, Giles Santyr","doi":"10.1002/jmri.70321","DOIUrl":"https://doi.org/10.1002/jmri.70321","url":null,"abstract":"","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147581220","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":"Exploring White Matter Microstructural Abnormalities Using MRI in Women With Premenstrual Dysphoric Disorder via Brain Connectome.","authors":"Shuxian Niu, Tao Gong, Yifan Niu, Dongmei Gao, Xiaoqin Liu, Mingzhou Gao, Meijin Lin, Guangbin Wang","doi":"10.1002/jmri.70318","DOIUrl":"https://doi.org/10.1002/jmri.70318","url":null,"abstract":"<p><strong>Background: </strong>The neurostructural underpinnings of premenstrual dysphoric disorder (PMDD), particularly integrated white matter and network alteration, remain unclear.</p><p><strong>Purpose: </strong>To identify a core structural network in PMDD by integrating multiple diffusion tensor imaging (DTI)-derived metrics and to develop a predictive model.</p><p><strong>Study type: </strong>Prospective case-control study.</p><p><strong>Subjects: </strong>Forty-two PMDD patients (age: 23.86 ± 1.32 years), diagnosed according to the American Psychiatric Association DSM-5, and 42 healthy controls (age: 23.79 ± 1.72 years).</p><p><strong>Field strength/sequence: </strong>3.0 T, T1-weighted three-dimensional gradient-echo and echo planar imaging DTI sequences.</p><p><strong>Assessment: </strong>Microstructural and connectivity features were extracted from DTI using tract-based spatial statistics (TBSS), network-based statistics (NBS), and graph theory analyses. A combined predictive model was constructed by integrating the most stable features from the three single-modality models via least absolute shrinkage and selection operator (LASSO) regression.</p><p><strong>Statistical tests: </strong>Group comparisons were performed using two-sample t-tests or Mann-Whitney U tests, with false discovery rate correction. Features were selected using LASSO and integrated to construct a combined model. Model performance was evaluated by the area under the receiver operating characteristic curve (AUC) using leave-one-out cross-validation. p < 0.05 was considered significant.</p><p><strong>Results: </strong>PMDD patients exhibited widespread microstructural and connectivity alterations, including elevated axial diffusivity in the right posterior limb of the internal capsule, enhanced edge connectivity, and altered network topology. The combined model achieved significantly superior predictive performance (AUC = 0.855) compared with the TBSS-based model (AUC = 0.699) and the network-based model (AUC = 0.727), and a higher AUC than the graph-based model (AUC = 0.790). Key predictive features included two enhanced edges originating from the left inferior frontal gyrus and reduced degree centrality of the left inferior occipital gyrus and sulcus.</p><p><strong>Data conclusion: </strong>Our DTI-based predictive model showed alterations in brain connections and network properties in the left inferior frontal and inferior occipital regions of PMDD patients.</p><p><strong>Level of evidence: 2: </strong></p><p><strong>Technical efficacy: </strong>Stage 2.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147581348","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 \"Clinical Feasibility of Deep Learning Contrast Synthesis From MR Fingerprinting in Knee Osteoarthritis\".","authors":"Tamotsu Kamishima","doi":"10.1002/jmri.70305","DOIUrl":"https://doi.org/10.1002/jmri.70305","url":null,"abstract":"","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147574272","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 MR Fingerprinting Development Kit for Quantitative 3D Brain Imaging.","authors":"Rasim Boyacioglu, Thomas Kluge, Guido Buonincontri, Wei-Ching Lo, Stephan Kannengiesser, Mathias Nittka, Arashdeep Kaur, Andrew Dupuis, Dan Ma, Chaitra Badve, Mark A Griswold, Yong Chen","doi":"10.1002/jmri.70320","DOIUrl":"10.1002/jmri.70320","url":null,"abstract":"<p><strong>Background: </strong>Magnetic resonance fingerprinting (MRF) is an emerging quantitative imaging technique that enables multiparametric tissue characterization, but its adoption has been hindered by the complexity of data acquisition and post-processing. These technical and implementation challenges have limited its broader clinical deployment.</p><p><strong>Purpose: </strong>To develop a modular MRF Development Kit (MRFDK) that enables efficient sequence design, streamlined implementation, and real-time image reconstruction.</p><p><strong>Study type: </strong>Prospective.</p><p><strong>Population: </strong>T₁ and T₂ relaxation phantom, nine volunteers (seven males and two females), five metastatic brain cancer patients.</p><p><strong>Field strength/sequence: </strong>3 T, MR Fingerprinting.</p><p><strong>Assessment: </strong>Accuracy of T₁ and T₂ quantification was estimated from phantom experiments. Manual ROIs were drawn on brain lesions and contralateral white matter for metastatic cancer patients.</p><p><strong>Statistical tests: </strong>t-test, in vivo repeatability was calculated with Bland-Altman analysis on healthy volunteer scan-rescan data, significance level p < 0.01.</p><p><strong>Results: </strong>Phantom results showed high accuracy in T₁ and T₂ assessment, with absolute percentage differences of 3% for T₁ and 5% for T₂ compared to offline MATLAB reconstruction. In vivo scans of eight healthy subjects further demonstrated excellent repeatability (bias and agreement: 0.95% ± 1.85% for T₁; 1.78% ± 5.08% for T₂). In patients, metastatic lesions showed significantly higher T₁ and T₂ values (T₁, 1474 ms; T₂, 61 ms) compared to normal white matter (T₁, 913 ms; T₂, 38 ms). With integrated B₁ correction, all T₁ and T₂ maps were available for visualization within 1 min post-MRF scan, enabling immediate image assessment.</p><p><strong>Data conclusion: </strong>A modular MRF development package enabling efficient 3D acquisition and rapid inline reconstruction was developed and evaluated in this study.</p><p><strong>Level of evidence: 1: </strong></p><p><strong>Technical efficacy: </strong>Stage 2.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13122508/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147574331","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":"Intracranial Plaque Characteristics and Extracranial Carotid Plaque-RADS Associated With Stroke Recurrence: A High-Resolution Vessel Wall Imaging Study.","authors":"Wenqiao Zheng, Yichun Qu, Fanyu Du, Zhichang Fan, Yan Li, Bin Wang, Yongfang Wang, Le Wang, Xiaochun Wang","doi":"10.1002/jmri.70313","DOIUrl":"https://doi.org/10.1002/jmri.70313","url":null,"abstract":"<p><strong>Background: </strong>In addition to intracranial plaques, extracranial carotid plaques have also been linked to stroke recurrence. However, the association of combined intracranial and extracranial plaque characteristics with stroke recurrence remains unclear.</p><p><strong>Purpose: </strong>To evaluate the association between intracranial plaque features and extracranial carotid Plaque Reporting and Data System (Plaque-RADS) with stroke recurrence utilizing high-resolution vessel wall imaging (HR-VWI).</p><p><strong>Study type: </strong>Retrospective.</p><p><strong>Population: </strong>The 388 intracranial atherosclerotic ischemic stroke patients (mean age, 57.3 ± 11.5 years, 274 males).</p><p><strong>Field strength/sequence: </strong>3T, three-dimensional T1 weighted 3D fast spin echo.</p><p><strong>Assessment: </strong>HR-VWI was performed in all patients within 7 days of the stroke onset. The imaging features assessed included intracranial plaque characteristics (degree of stenosis, plaque burden, enhancement ratio, remodeling index, and intraplaque hemorrhage [IPH]) and extracranial carotid Plaque-RADS. Patients enrolled between May 2022 and July 2024 were included in the study. All patients were followed for a minimum of 12 months.</p><p><strong>Statistical tests: </strong>Mann-Whitney U test or χ² test, univariate and multivariate Cox regression analyses, time-dependent ROC and AUC curves, and Kaplan-Meier survival curves. p-values less than 0.05 were regarded as statistically significant.</p><p><strong>Results: </strong>During a median follow-up period of 24 months, 55 patients experienced recurrent stroke. Intracranial plaque enhancement ratio (HR, 1.62; 95% CI, 1.11-2.38), IPH (HR, 2.55; 95% CI, 1.47-4.40), and extracranial carotid Plaque-RADS (HR, 2.23; 95% CI, 1.29-3.86) were significantly associated with stroke recurrence. Time-dependent ROC indicated that the maximum AUCs for enhancement ratio, IPH, and Plaque-RADS were 0.75, 0.69, and 0.68, respectively, while the Cox model including all three reached a maximum AUC of 0.79.</p><p><strong>Data conclusion: </strong>The combination of intracranial plaque characteristics and extracranial carotid Plaque-RADS can be used to assess ischemic stroke recurrence.</p><p><strong>Evidence level: </strong>3.</p><p><strong>Technical efficacy: </strong>Stage 2.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147529709","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":"Incremental Prognostic Value of Pericardial Adipose Tissue Radiomic Phenotype Based on Cardiac MRI in Patients With End-Stage Renal Disease.","authors":"Tian-Yi Zhang, Youqi Liu, Shuai-Zheng Chen, Lian-Ming Wu, Jun Pu, Yao Xu, Xiao-Qian Yang, Qisheng Lin, Binghua Chen, Qin Wang, Wei Fang, Renhua Lu, Hong Cai, Jiayi Yan, Haijiao Jin, Chaolu Feng, Dong-Aolei An, Shan Mou","doi":"10.1002/jmri.70303","DOIUrl":"https://doi.org/10.1002/jmri.70303","url":null,"abstract":"<p><strong>Background: </strong>While pericardial adipose tissue (PEAT) volume is linked to cardiac risk, the prognostic value of its radiomic features for major adverse cardiac events (MACE: a composite of cardiac death, myocardial infarction, heart failure hospitalization, or stroke) in end-stage renal disease (ESRD) patients is unknown.</p><p><strong>Purpose: </strong>To evaluate the association of PEAT radiomics with MACE in patients with ESRD.</p><p><strong>Study type: </strong>Retrospective.</p><p><strong>Population: </strong>Two hundred forty-eight ESRD patients (160 males) from three centers were included and divided into development (198 patients) and validation cohorts (50 patients) by centers.</p><p><strong>Field strength/sequence: </strong>3.0 T/cine imaging, T2 and T2* mappings, all gradient echo.</p><p><strong>Assessment: </strong>A triple-stage Unet model (3SUnet) was used for the segmentation of PEAT in cine images. Myocardial T2 and T2* values were extracted from native T2 and T2* images. Demographic and laboratory data were collected within 1 week of the MRI scan. Participants were followed up from the MRI scanning every 2 weeks until July 2023 until MACE occurred.</p><p><strong>Statistical tests: </strong>Principal component analysis (PCA) was used to reduce radiomic features to principal radiomics (PrPEAT-rads). Cox regression analyses were used to investigate the prognostic value of extracted PrPEAT-rads. p-value ≤ 0.05 was considered statistically significant.</p><p><strong>Results: </strong>During a median follow-up time of 35.6 months, 63 patients (25.4% of 248; 15 in the external validation cohort) experienced MACE. The combined use of selected PrPEAT-rads with conventional MRI risk scores significantly improved risk stratification of MACE in both the internal (C-index: 0.715 vs. 0.768; integrated Brier score [IBS]: 0.095 vs. 0.090) and the external validation cohort (C-index: 0.737 vs. 0.774; IBS: 0.130 vs. 0.070). PrPEAT-rad1 was a significant independent factor associated with MACE after adjusting for both clinical (HR: 0.937) and MRI (HR: 0.916) covariates.</p><p><strong>Data conclusion: </strong>The cardiac MRI cine-based PEAT radiomics features in ESRD patients demonstrated a stronger association with MACE compared to conventional clinical and MRI parameters.</p><p><strong>Evidence level: </strong>3.</p><p><strong>Stage of technology efficacy: </strong>Stage 2.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147529996","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}