Magnetic resonance imaging最新文献

{"title":"Association of white matter hyperintensities with cognitive impairment.","authors":"Wen-Jun Feng, Yu-Meng Gu, Xiao-Shuang Xia, Xin Li","doi":"10.1016/j.mri.2025.110464","DOIUrl":"10.1016/j.mri.2025.110464","url":null,"abstract":"<p><strong>Objective: </strong>This study aimed to examine the characteristics of cognitive impairment in individuals with white matter hyperintensities (WMH) and to compare differences in cognitive dysfunction across varying levels of WMH severity.</p><p><strong>Methods: </strong>A total of 100 participants were randomly recruited from inpatient and outpatient departments of a hospital between November 2018 and December 2022. The cohort included 55 patients with cerebral small vessel disease (CSVD) and 45 control participants without CSVD. Among the CSVD group, 37 individuals had WMH. Cognitive function assessments were conducted for both the WMH and control groups to evaluate the characteristics of WMH-related cognitive dysfunction. Furthermore, cognitive scale scores and fractional anisotropy (FA) values obtained from diffusion tensor imaging (DTI) were compared among patients with varying WMH severity levels to analyze variations in cognitive performance and lesion characteristics across multiple brain regions.</p><p><strong>Results: </strong>Statistically significant differences were observed between the control and CSVD groups in age, hypertension, diabetes, coronary heart disease, smoking, and physical activity (P < 0.05). The WMH and control groups demonstrated significant differences in the Montreal Cognitive Assessment (MoCA) total score, Digit Span Test (DST)-forward, DST-backward, Color Trail Test (CTT)-A, and CTT-B scores (p < 0.05). Significant differences were also identified between the mild and severe WMH groups (p < 0.05). Analysis of moderate and severe WMH groups indicated significant differences in FA values of the anterior horn of the lateral ventricle (p < 0.05), along with significant differences in age, DST-forward, and CTT-B scores (p < 0.05).</p><p><strong>Conclusion: </strong>Cognitive impairment in individuals with WMH is predominantly characterized by marked declines in executive function and attention, while memory and language impairments are less pronounced. Severe WMH is associated with greater damage to the anterior horn of the lateral ventricle.</p>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":" ","pages":"110464"},"PeriodicalIF":2.0,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144760490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A study of magnetic resonance diffusion tensor imaging in the prognostic assessment of severe craniocerebral trauma.","authors":"Xiangzhen Meng","doi":"10.1016/j.mri.2025.110481","DOIUrl":"10.1016/j.mri.2025.110481","url":null,"abstract":"<p><strong>Background: </strong>Magnetic resonance diffusion tensor imaging (DTI) is recognized for its diagnostic capabilities in severe craniocerebral trauma but is less explored for its prognostic utility. This study assesses the prognostic value of DTI in predicting outcomes for patients with severe craniocerebral trauma.</p><p><strong>Methods: </strong>We conducted a retrospective analysis of 125 patients who sustained severe craniocerebral injuries between March 2021 and September 2022. Patients were evaluated 90 days post-injury using the Glasgow Outcome Scale (GOS) and categorized into good (GOS 4-5, n = 74) and poor (GOS 1-3, n = 51) prognosis groups. DTI parameters were analyzed using logistic regression and Receiver Operating Characteristic (ROC) curves to identify prognostic indicators.</p><p><strong>Results: </strong>No significant demographic differences were observed (P > 0.05); however, significant variances were noted in DTI parameters like ADC and FA, correlating with patient outcomes. Multifactorial analysis highlighted GCS ≤ 4, midline shift ≥5 mm, and ADC ≤ 2.7 × 10^-3 mm²/s as key predictors of poor prognosis.</p><p><strong>Discussion: </strong>DTI provides valuable insights into the structural impacts of severe craniocerebral trauma, with ADC and FA serving as reliable indicators of prognosis. Identifying these parameters early can guide clinical interventions and potentially improve outcomes, underscoring the need for integrating DTI into routine prognostic assessments.</p>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":" ","pages":"110481"},"PeriodicalIF":2.0,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144794871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"4D flow MRI of aortic blood flow parameters in healthy volunteers: Sex- and age-specific analysis.","authors":"Gyu-Han Lee, Hojin Ha, Kyung Jin Park, Hyun Jung Koo, June-Goo Lee, Hyun Seo Lee, Jong Eun Lee, Dong Hyun Yang, Dae-Hee Kim","doi":"10.1016/j.mri.2025.110482","DOIUrl":"10.1016/j.mri.2025.110482","url":null,"abstract":"<p><strong>Purpose: </strong>Four-dimensional (4D) flow MRI enables comprehensive assessment of aortic hemodynamics, but normative values remain limited, especially for Asian populations. This study aimed to establish age- and sex-specific normative values for flow-related parameters in healthy Korean adults.</p><p><strong>Methods: </strong>Seventy-seven healthy volunteers (aged 20-79 years) underwent 4D flow MRI. Hemodynamic parameters-velocity, viscous energy loss, normalized vorticity, and helicity-were quantified in the ascending aorta (AAo), aortic arch (AoA), and descending aorta (DAo).</p><p><strong>Results: </strong>Significant sex differences were found for velocity in the AAo (p < 0.001) and viscous energy loss across all segments (p < 0.05), while normalized vorticity and helicity showed no sex-related differences. In viscous energy loss, males had higher values than females in the AAo (2.84 ± 1.05 vs 2.22 ± 0.60 mW, p = 0.017), AoA (0.74 ± 0.37 vs 0.42 ± 0.19 mW, p = 0.001), and DAo (4.78 ± 1.82 vs 3.32 ± 1.55 mW, p = 0.002). Most parameters demonstrated age-related declines, especially in the DAo. Strongest correlations with age were seen for velocity (r = -0.725, p < 0.001) and viscous energy loss (r = -0.745, p < 0.001). Positive helicity showed sex-specific aging trends, with the strongest correlations in the DAo for men and the AoA for women. Negative helicity showed the strongest correlation in the DAo in both sexes.</p><p><strong>Conclusions: </strong>This study established age- and sex-specific normative values for aortic hemodynamic parameters in healthy Korean adults using 4D flow MRI. While sex differences were limited, most flow parameters declined with age.</p>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":" ","pages":"110482"},"PeriodicalIF":2.0,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144799546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigating microbleeds and white matter hyperintensities in TBI at a tract-level: A DTI study","authors":"Zalán Petneházy ,&nbsp;Dávid Bognár ,&nbsp;Péter Laar ,&nbsp;Tamás Dóczi ,&nbsp;Attila Schwarcz ,&nbsp;Bálint S. Környei ,&nbsp;Arnold Tóth","doi":"10.1016/j.mri.2025.110541","DOIUrl":"10.1016/j.mri.2025.110541","url":null,"abstract":"<div><h3>Objectives</h3><div>This study aimed to determine whether focal MRI lesions such as microbleeds (MBs) and focal white matter hyperintensities (FWMHs) serve as reliable and specific markers for tract-level white matter injury in traumatic brain injury (TBI).</div></div><div><h3>Materials &amp; methods</h3><div>Twenty-two patients with moderate-to-severe TBI and 22 age-matched healthy controls underwent MRI on a 3 T Siemens Prisma scanner. Imaging included susceptibility-weighted imaging (SWI), fluid-attenuated inversion recovery (FLAIR), and diffusion tensor imaging (DTI). Focal lesions were manually identified on SWI and FLAIR and mapped onto tractography reconstructions. Diffusion metrics—fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were compared between lesion-affected tracts, contralateral normal-appearing white matter (NAWM), and corresponding control tracts. Statistical analyses were performed using repeated measures ANOVA with Greenhouse-Geisser correction and Bonferroni-adjusted post hoc tests for FA. Friedman tests were conducted for MD, AD, and RD, followed by Bonferroni-corrected Wilcoxon post hoc comparisons.</div></div><div><h3>Results</h3><div>In this study, we identified 27 MBs and 66 FWMHs intersecting white matter tracts. We observed notable differences in diffusion metrics when comparing lesion-affected tracts to healthy controls. In MB-affected tracts, fractional anisotropy (FA) differed significantly (<em>p</em> = 0.002), while mean diffusivity (MD) also showed a significant alteration (p = 0.002), along with radial diffusivity (RD) (<em>p</em> &lt; 0.001). Similarly, in FWMH-affected tracts, significant differences were observed in FA (<em>p</em> &lt; 0.001), MD (p &lt; 0.001), axial diffusivity (AD) (p &lt; 0.001), and RD (p &lt; 0.001). However, we did not find any significant differences between lesion-affected tracts and the contralateral normal-appearing white matter (NAWM).</div></div><div><h3>Conclusion</h3><div>MBs and FWMHs do not co-localize with axonal injury at the tract level but indicate a global white matter damage.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"125 ","pages":"Article 110541"},"PeriodicalIF":2.0,"publicationDate":"2025-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145329540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Total tumor apparent diffusion coefficient histogram analysis of whole-body DWI-MRI for prognostic stratification in patients with R-ISS stage II multiple myeloma.","authors":"Junde Zhou, Qin Wang, Yanting Liu, Lu Zhang, Jiao Li, Shuo Li, Dong Liu, Jinxia Zhu, Robert Grimm, Alto Stemmer, Shuang Xia, Wenyang Huang, Sheng Xie, Haibo Zhang, Jian Li, Huadan Xue, Zhengyu Jin","doi":"10.1016/j.mri.2025.110536","DOIUrl":"https://doi.org/10.1016/j.mri.2025.110536","url":null,"abstract":"<p><strong>Purpose: </strong>This study aimed to explore the utility of total tumor apparent diffusion coefficient (ttADC) histogram analysis based on whole-body diffusion-weighted magnetic resonance imaging (DWI-MRI) for prognostic stratification in patients with Revised International Staging System stage II (R-ISS II) multiple myeloma (MM).</p><p><strong>Methods: </strong>Patients with R-ISS II MM who underwent baseline whole-body MRI prior to treatment were retrospectively enrolled. The ttADC histogram parameters of the whole-body DWI-MRI were obtained using MR Total Tumor Load software (Siemens Healthcare, Erlangen, Germany). The overall survival (OS) and the progression-free survival (PFS) of the cohort was recorded. Cox regression analyses were used to evaluate the clinical features and ttADC histogram parameters for their association with OS and PFS.</p><p><strong>Results: </strong>A total of 61 R-ISS II MM patients were retrospectively included. During a mean follow-up period of 80 months, 27 patients died, 4 patients lost follow-up for OS, and 4 patients lost follow-up for PFS. Multivariate analysis revealed that increased median ttADC (≥0.620 × 10^-3 mm²/s) [hazard ratio (HR) = 2.291, P = 0.046, 95 % confidence interval (CI): 1.014-5.175] was independently associated with OS in R-ISS II MM patients. No significant association was observed between the ttADC histogram parameters and PFS.</p><p><strong>Conclusion: </strong>The median ttADC of whole-body DWI-MRI is an independent predictor of OS in R-ISS II MM patients, suggesting its potential role in further prognostic stratification in this patients' subgroup.</p>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":" ","pages":"110536"},"PeriodicalIF":2.0,"publicationDate":"2025-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145308715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Combination of clinicopathological and MRI based radiomics features in predicting homologous recombination repair genes mutations in prostate cancer","authors":"Ruchuan Chen ,&nbsp;Guoqing Hu ,&nbsp;Bingni Zhou ,&nbsp;Hualei Gan ,&nbsp;Xiaofeng Liu ,&nbsp;Lin Deng ,&nbsp;Liangping Zhou ,&nbsp;Yajia Gu ,&nbsp;Xiaohang Liu","doi":"10.1016/j.mri.2025.110534","DOIUrl":"10.1016/j.mri.2025.110534","url":null,"abstract":"<div><h3>Purpose</h3><div>To develop Homologous Recombination Repair (HRR) Genes mutations prediction models for prostate cancer using MRI radiomics and clinicopathological features.</div></div><div><h3>Methods</h3><div>Totally 353 prostate cancer patients (102 with HRR genes mutations) from three centers (center 1: training and internal test cohorts, center 2 and 3: external test cohorts) underwent multiparametric MRI. Each patient's index tumor lesion was delineated on T2-weighted imaging (T2WI), dynamic contrast enhancement (DCE) MRI, diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) images to obtain 428 radiomics features. Features associated with mutations were selected from clinicopathological features using Mann-Whitney U and Logistic regression (LR) test, radiomics features using Least Absolute Shrinkage and Selection Operator. Clinicopathological model was constructed with selected clinicopathological features. Logistic regression (LR), support vector machine (SVM) and linear discriminant analysis (LDA) classifiers were used to construct Radiomics and combined clinicopathological-radiomics models. Predictive efficiencies of models were compared using areas under the receiver operating characteristic curve (AUC).</div></div><div><h3>Results</h3><div>One clinicopathological and six radiomics features were selected. Radiomics with SVM, LR, LDA and Clinicopathological models achieved AUCs of 0.76, 0.76, 0.76, 0.68 and 0.75, 0.76, 0.67, 0.73 in internal and external test cohort. AUCs of combined clinicopathological-radiomics models with LDA in internal and external test cohort (0.83 and 0.82) were slightly higher than combined models with LR (0.81 and 0.79) and SVM (both 0.80) (<em>P</em> &gt; 0.05), but were significantly higher than radiomics and clinicopathological models in both cohorts (<em>P</em> &lt; 0.05).</div></div><div><h3>Conclusion</h3><div>LDA classifier incorporating radiomics and clinicopathological features predicting could effectively predict HRR genes mutations in prostate cancer.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"124 ","pages":"Article 110534"},"PeriodicalIF":2.0,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145275099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Bayesian CAIPIVAT approach with through-plane acceleration to enhance efficiency of simultaneously encoded slice acquisition in FMRI","authors":"Ke Xu,&nbsp;Daniel B. Rowe","doi":"10.1016/j.mri.2025.110540","DOIUrl":"10.1016/j.mri.2025.110540","url":null,"abstract":"<div><div>FMRI has been a safe medical imaging tool to study brain function by demonstrating the spatial and temporal changes in brain metabolism in recent decades. To capture brain functionality more efficiently, efforts focus on accelerating image acquisition acquired per unit of time that create each volume image without losing full anatomical structure. The Simultaneous Multi-Slice (SMS) technique provides a reconstruction method where multiple slices are acquired and aliased concurrently. Traditional imaging techniques such as SENSE and GRAPPA can reconstruct an image from less measured data but have their drawbacks. The Controlled Aliasing in Parallel Imaging (CAIPI) and view angle tilting (VAT) techniques achieve slice-wise image shift to decrease the influence of the geometry factor (<em>g</em>-factor) of coil sensitivities and prevent the singular problem of the design matrix. In this paper, a Bayesian CAIPIVAT approach for multi-coil separation of parallel encoded complex-valued slices (mSPECS-CAIPIVAT) with a novel SMS approach is presented and combined with the Hadamard phase-encoding method for image separation. Our proposed approach was applied to simulation and experimental studies showing a decrease in the influence of the <em>g</em>-factor while increasing the brain activation detection rate. The signal-to-noise ratio and the contrast-to-noise ratio are also improved by our approach.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"124 ","pages":"Article 110540"},"PeriodicalIF":2.0,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145258594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correcting unwanted diffusion weighting in diffusion-weighted-STEAM sequence for time-dependent diffusion kurtosis imaging","authors":"Qinfeng Zhu ,&nbsp;Ruicheng Ba ,&nbsp;Zuozhen Cao ,&nbsp;Yao Shen ,&nbsp;Haotian Li ,&nbsp;Yi-Cheng Hsu ,&nbsp;Xu Yan ,&nbsp;Dan Wu","doi":"10.1016/j.mri.2025.110535","DOIUrl":"10.1016/j.mri.2025.110535","url":null,"abstract":"<div><h3>Purpose</h3><div>This study proposes an optimized acquisition protocol to minimize the unwanted diffusion weighting in DW-STEAM and facilitate time-dependent diffusion kurtosis imaging (tDKI).</div></div><div><h3>Methods</h3><div>We first corrected the diffusion-direction-dependent shift by optimizing the diffusion gradient amplitude. We then proposed to use low-b-value in the reference image, instead of the conventional non-diffusion-weighted (b0) acquisition, and removed the crusher gradients. The tDKI measurements from the proposed strategy were compared with conventional DWIs that included crushers in the b0 image, in a water phantom and in healthy adults (<em>n</em> = 8) on 3 T, and the water exchange time (<em>τ</em>_<em>ex</em>) was calculated from the tDKI measurements. The optimal strategy was tested in five <em>ex vivo</em> human brains, and the results were compared with <em>in vivo</em> data.</div></div><div><h3>Results</h3><div>Neglecting the diffusion weighting in b0 images introduced an artificial time dependence in the apparent diffusivity of the water phantom, and resulted in elevated estimates of water exchange time (<em>τ</em>_<em>ex</em>) in in the <em>in vivo</em> data. Additionally, the AIC indicated that, even when diffusion weighting in the b0 images was accounted for, the kurtosis estimation remained less stable in the <em>in vivo</em> than with the crusher-free approach. In contrast, using low-b-value images as reference measurements yielded reasonable tDKI estimates, with <em>τ</em>_<em>ex</em> ranging from 15 to 40 ms for gray matter <em>in vivo</em> and from 20 to 60 ms for gray matter <em>ex vivo</em>.</div></div><div><h3>Conclusions</h3><div>The optimized DW-STEAM acquisition eliminated artificial diffusion-time dependence, enabling the acquisition of accurate tDKI data for mapping structural morphology and transmembrane permeability.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"124 ","pages":"Article 110535"},"PeriodicalIF":2.0,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145267178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sensitivity of quantitative diffusion MRI tractography and microstructure to anisotropic spatial sampling","authors":"Elyssa M. McMaster ,&nbsp;Nancy R. Newlin ,&nbsp;Chloe Cho ,&nbsp;Gaurav Rudravaram ,&nbsp;Adam M. Saunders ,&nbsp;Aravind R. Krishnan ,&nbsp;Lucas W. Remedios ,&nbsp;Michael E. Kim ,&nbsp;Hanliang Xu ,&nbsp;Kurt G. Schilling ,&nbsp;François Rheault ,&nbsp;Laurie E. Cutting ,&nbsp;Bennett A. Landman","doi":"10.1016/j.mri.2025.110539","DOIUrl":"10.1016/j.mri.2025.110539","url":null,"abstract":"<div><h3>Purpose</h3><div>Diffusion weighted MRI (dMRI) and its models of neural structure provide insight into human brain organization and variations in white matter. A recent study by McMaster, et al. showed that complex graph measures of the connectome, the graphical representation of a tractogram, vary with spatial sampling changes, but biases introduced by anisotropic voxels in the process have not been well characterized. This study uses microstructural measures (fractional anisotropy and mean diffusivity) and white matter bundle properties (bundle volume, length, and surface area) to further understand the effect of anisotropic voxels on microstructure and tractography.</div></div><div><h3>Methods</h3><div>The statistical significance of the selected measures derived from dMRI data were assessed by comparing three white matter bundles at different spatial resolutions with 44 subjects from the Human Connectome Project – Young Adult dataset scan/rescan data using the Wilcoxon Signed-Rank test. The original isotropic resolution (1.25 mm isotropic) was explored with 6 anisotropic resolutions with 0.25 mm incremental steps in the <em>z</em> dimension. Then, all generated resolutions were upsampled to 1.25 mm isotropic and 1 mm isotropic.</div></div><div><h3>Results</h3><div>There were statistically significant differences between at least one microstructural and one bundle measure at every resolution (<span><math><mi>p</mi><mo>≤</mo><mn>0.05</mn></math></span>, corrected for multiple comparisons). Cohen's <span><math><mi>d</mi></math></span> coefficient evaluated the effect size of anisotropic voxels on microstructure and tractography.</div></div><div><h3>Conclusion</h3><div>Fractional anisotropy and mean diffusivity cannot be recovered with basic up-sampling from low quality data with gold-standard data with the methods selected for this study. However, the bundle measures across our selected regions of interest become more repeatable when voxels are resampled to 1 mm isotropic.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"124 ","pages":"Article 110539"},"PeriodicalIF":2.0,"publicationDate":"2025-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145244670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Role of large language models for etiological classification of brain stroke based on MRI brain reports: a feasibility study","authors":"Jorge Escartín ,&nbsp;Pilar López-Úbeda ,&nbsp;Teodoro Martín-Noguerol ,&nbsp;Antonio Luna","doi":"10.1016/j.mri.2025.110538","DOIUrl":"10.1016/j.mri.2025.110538","url":null,"abstract":"<div><h3>Purpose</h3><div>Ischemic stroke, a leading cause of global disability and mortality, demands precise etiological classification for effective management. The variability in the use of existing stroke classification systems, along with the challenges in manual etiological labeling from brain MRI radiological reports, calls for an innovative approach. This study aims to develop and evaluate a Natural Language Processing (NLP) algorithm using transformer-based models for the extraction and classification of ischemic stroke types from MRI reports, enhancing diagnostic efficiency and stroke management.</div></div><div><h3>Methods</h3><div>We built a dataset comprising 635 brain MRI reports, annotated for four distinct ischemic stroke types. All were clinically consistent with focal neurologic impairment due to stroke. The study involved evaluating two pre-trained models BERT (Bert clinical and Beto) and two models RoBERTa (Roberta clinical trials and Roberta biomedical), focusing on their ability to accurately classify stroke subtypes.</div></div><div><h3>Results</h3><div>The Roberta biomedical model emerged as the most effective, demonstrating superior performance with an accuracy of 76.7 % with statistically significant results. This model also achieved the highest precision, recall, and F1 scores across all stroke types, indicating its robustness in stroke subtype classification.</div></div><div><h3>Conclusion</h3><div>The study highlights the potential of NLP algorithms in automating stroke classification from MRI reports, which could significantly aid in diagnostic processes and streamline stroke management strategies.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"124 ","pages":"Article 110538"},"PeriodicalIF":2.0,"publicationDate":"2025-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145244717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}