Magnetic Resonance Materials in Physics, Biology and Medicine最新文献

{"title":"Deep learning synthesis of Restriction Spectrum Imaging cellularity maps from conventional MRI in post-treatment glioblastoma.","authors":"Yiğit Hasan Arı","doi":"10.1007/s10334-026-01422-y","DOIUrl":"https://doi.org/10.1007/s10334-026-01422-y","url":null,"abstract":"<p><strong>Objective: </strong>The feasibility of synthesizing Restriction Spectrum Imaging (RSI) cellularity maps from routinely acquired post-treatment MRI in glioblastoma was evaluated using a deep learning framework.</p><p><strong>Materials and methods: </strong>A SwinUNETR model was trained on post-contrast T1-weighted, FLAIR, and ADC images from 184 imaging timepoints of 136 patients in the publicly available UCSD-PTGBM dataset, using five-fold patient-level cross-validation. Synthesis performance was assessed using tumor-ROI Pearson correlation as the primary endpoint, alongside secondary clinical agreement, hotspot localization, and scanner-stratified analyses.</p><p><strong>Results: </strong>Mean per-visit tumor-ROI Pearson correlation was 0.635 ± 0.164 (95% CI 0.608-0.662) and voxel-level intratumoral rank-agreement AUC for high-cellularity voxels was 0.800 (95% CI 0.785-0.814). SwinUNETR outperformed a 3D U-Net baseline across prespecified agreement and error metrics (all p < 0.001). A systematic negative bias of - 0.058 (95% limits-of-agreement width: 0.428) was observed within the tumor ROI, and hotspot Dice was 0.155 (95% CI 0.144-0.166), indicating limited focal localization. No significant difference was observed between scanner models for primary agreement metrics.</p><p><strong>Discussion: </strong>Conventional post-treatment MRI approximates average RSI-derived cellularity but not the high-cellularity subregions with spatial precision. The approach may support screening where dedicated RSI is unavailable but cannot substitute for acquired RSI in quantitative or treatment-guiding applications.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148912628","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":"ESMRMB 2026 focus topic: future of MR in clinical practice.","authors":"Roy Haast, Martina Callaghan, Andreea Hertanu, Alexandros Kallifatidis, Allison McGee, Emer Kenny, Francesco Santini, Petra J Van Houdt","doi":"10.1007/s10334-026-01415-x","DOIUrl":"https://doi.org/10.1007/s10334-026-01415-x","url":null,"abstract":"","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148912667","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":"ESMRMB 2026 focus topic: future of MR machines.","authors":"Rita Schmidt, Roberto Cannella, Beatrice Lena, Pinar S Özbay, Nikos Priovoulos, Martin Uecker, Moritz Zaiss","doi":"10.1007/s10334-026-01414-y","DOIUrl":"https://doi.org/10.1007/s10334-026-01414-y","url":null,"abstract":"","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148912689","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":"Age-dependent macromolecule signals in the human motor cortex and thalamus: implications for metabolites quantification at 7 T.","authors":"Xinyu Liu, Gianna Nossa, Ying Xiao, Selin Scherrer, Sven Egger, Benedikt Lauber, Wolfgang Taube, Ulrike Dydak, Lijing Xin","doi":"10.1007/s10334-026-01419-7","DOIUrl":"https://doi.org/10.1007/s10334-026-01419-7","url":null,"abstract":"<p><strong>Objective: </strong>Macromolecular (MM) signals overlap with metabolite signals, but MM content differences across age and brain region and their influences on brain metabolites quantification have remained elusive. While most studies assume universal MM content when assessing neurochemical levels, region- and age-related MM differences could result in inaccurate quantification of metabolites. This study assesses MM differences linked to specific brain regions and age by analyzing their influence on metabolite signal quantification in the primary motor cortex (M1) and thalamus.</p><p><strong>Materials and methods: </strong>We created age- and region-specific MM basis sets measured using an inversion-recovery protocol at 7 T. In addition, we acquired short echo time (TE) spectra from M1 and thalamus in a separate cohort, and differences in the metabolite quantification results that arose from using age- or region-matched and unmatched basis sets were evaluated. Comparisons were made between a young group (22-34 years) and an elderly group (64-79 years) and across M1 or thalamus.</p><p><strong>Results: </strong>We found significant differences in metabolite signals when using basis sets created from matched versus unmatched macromolecule spectra by age or region. Specifically, in M1, substituting the alternate same-region basis set significantly changed 7/12 metabolite signals in elderly spectra and 6/12 in young spectra. The effect was more evident when fitting young thalamic spectra with the elderly thalamic basis, where 11/12 metabolites signals changed. When the thalamic MM basis set was applied to M1 spectra, 11/12 metabolites signals shifted significantly in the young-M1 and 7/12 in the elderly-M1.</p><p><strong>Discussion: </strong>Our study demonstrated the importance of age-specific and region-specific MM basis sets for accurate metabolite quantification.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148887875","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":"An FA-based hybrid DTI-mixture model for multi-fiber reconstruction in diffusion MRI.","authors":"Ashishi Puri, Sanjeev Kumar","doi":"10.1007/s10334-026-01411-1","DOIUrl":"https://doi.org/10.1007/s10334-026-01411-1","url":null,"abstract":"<p><strong>Objective: </strong>This study proposes a hybrid diffusion MRI reconstruction framework combining Diffusion Tensor Imaging (DTI) and the multi-compartment non-central Wishart (MNCW) mixture model. The proposed framework uses an empirically selected fractional anisotropy (FA) threshold of 0.75 as a heuristic to distinguish between single- and multi-fiber voxels, enabling adaptive selection of the most appropriate reconstruction model for each voxel.</p><p><strong>Materials and methods: </strong>Synthetic diffusion MRI datasets containing single-, two-, and three-fiber configurations were generated using 82 diffusion-sensitizing gradient directions with Rician noise. Voxels with FA <math><mo>≥</mo></math> 0.75 were reconstructed using DTI, while voxels with FA < 0.75 were analyzed using the MNCW model. Angular error and clustering behavior were evaluated under different thresholds. The method was further validated using rat optic chiasm and human brain datasets.</p><p><strong>Results: </strong>The proposed framework reduced incorrect single-fiber detections and produced fewer disoriented voxels in complex fiber configurations compared with the conventional mixture model. A clustering threshold of 17 <math><mmultiscripts><mrow></mrow> <mrow></mrow> <mo>∘</mo></mmultiscripts> </math> provided stable reconstruction without merging distinct fibers. Real data experiments demonstrated anatomically consistent reconstruction of white matter structures.</p><p><strong>Discussion: </strong>The hybrid framework improves orientation estimation by selectively applying mixture modeling only in voxels likely to contain multiple fibers, reducing over-segmentation, improving stability, and lowering computational complexity.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148887822","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":"Lost in k-space: an open-source MR-physics escape room.","authors":"Sabine Melanie Räuber, Marta Brigid Maggioni, Francesco Santini","doi":"10.1007/s10334-026-01421-z","DOIUrl":"https://doi.org/10.1007/s10334-026-01421-z","url":null,"abstract":"<p><strong>Introduction: </strong>Operating an MR scanner for technical and clinical research requires multidisciplinary competencies beyond MR physics, including safety management and teamwork. Gamification, particularly educational escape rooms, has been associated with improved motivation, engagement and knowledge retention in health professional education.</p><p><strong>Materials and methods: </strong>We developed an MR-physics-themed educational escape room for the 41st Annual Meeting of the ESMRMB. Designed for teams of four with a time limit of 25 min, the room reproduced the atmosphere of an MR control room. The five puzzles covered the Larmor equation, sequence composition, MR safety and acoustical identification of MR sequences. Custom ESP32 electronics allowed the puzzles to communicate in real time with each other and with the game master.</p><p><strong>Results: </strong>The room ran without technical interruptions and was played by 39 teams (approximately 160 participants); 12 solved it (escape rate 31%), with a median solution time of 21 min and 53 s. Early-career researchers acted as game masters.</p><p><strong>Discussion: </strong>The escape rate aligns with comparable activities targeting scientific audiences. Difficulty can be tuned by adjusting puzzle obscurity, component availability, required prior knowledge and mental leaps. A modified version could usefully supplement mandatory MR safety training. Code, schematics, machining files and documentation are released as open source.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148887836","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":"Book of Abstracts ESMRMB 2026 42nd Annual Scientific Meeting September 30th-October 3rd 2026.","authors":"","doi":"10.1007/s10334-026-01395-y","DOIUrl":"https://doi.org/10.1007/s10334-026-01395-y","url":null,"abstract":"","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":"39 Suppl 1","pages":"1-671"},"PeriodicalIF":3.1,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149030763","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":"Motion-induced fields near an idealized actively shielded MRI magnet: a reproducible reduced-order framework for scaling and sensitivity from 1.5 to 7 T.","authors":"Hassan Vafapour","doi":"10.1007/s10334-026-01412-0","DOIUrl":"https://doi.org/10.1007/s10334-026-01412-0","url":null,"abstract":"<p><strong>Purpose: </strong>To present a transparent reduced-order electromagnetic framework for examining how an explicitly specified magnet geometry, movement trajectory, and body-conversion model affect movement-induced field estimates near MRI systems. The framework distinguishes dependencies imposed by the equations from spatial and sensitivity results computed from the field map.</p><p><strong>Methods: </strong>An idealized actively shielded magnet was represented by primary and opposing coaxial solenoids. A 7-T reference system was calibrated at two axial points; 1.5 T and 3 T cases were then generated by matched-geometry ampere-turn scaling as a controlled thought experiment. Movement-induced dB/dt was calculated from the directional derivative v·∇|B|. The primary whole-trunk screening estimate used an ellipsoidal conversion coefficient of 0.16 V m^-1 (T s^-1)^-1, whereas a 0.15-m-radius circular-loop estimate, corresponding to 0.075 V m^-1 (T s^-1)^-1, was evaluated as a sensitivity case. Additional analyses varied active-shield geometry, movement-field alignment, and hypothetical 10 T and 14 T matched-geometry cases.</p><p><strong>Results: </strong>Along the specified axial path, the peak dB/dt at 1.5 m s^-1 was 3.17, 6.33, and 14.78 T/s for the matched-geometry 1.5 T, 3 T, and 7 T cases. The corresponding ellipsoidal trunk estimates were 0.51, 1.01, and 2.36 V m^-1; circular-loop estimates were 0.24, 0.48, and 1.11 V m^-1. At 7 T, varying the idealized active-shield geometry changed peak dB/dt from 13.12 to 16.70 T/s, and the directional term could range from the worst-case envelope to zero for locally orthogonal motion. A heart-specific E99 context, where E99 denotes the 99th-percentile induced electric-field magnitude in the myocardium in published anatomical simulations, was 0.42-1.23 V m^-1 for the 7 T brisk-motion case; this was not interpreted as a cardiac stimulation prediction. A conceptual minimax schedule reduced the modeled peak by 77%, but is presented only as a mathematical demonstration.</p><p><strong>Conclusion: </strong>This reproducible reduced-order framework quantifies how active-shield geometry, movement direction, and body-conversion assumptions shape motion-induced field estimates near an idealized MRI magnet. The calculations expose substantial sensitivity to the body model, shield geometry, and trajectory, providing a transparent basis for education, model verification, and the design of scanner-specific dosimetric studies. Translation to regulatory compliance or operational guidance requires measured or vendor-provided fringe-field maps, anatomically resolved dosimetry, waveform analysis, and local safety procedures.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148840706","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":"Recent advances in arterial spin labeling MRI for imaging brain tumors.","authors":"Gabriel Hoffmann, Matthias J P van Osch","doi":"10.1007/s10334-026-01408-w","DOIUrl":"https://doi.org/10.1007/s10334-026-01408-w","url":null,"abstract":"<p><p>Perfusion MRI plays an important role in brain tumor assessment, especially for tumor grading and differentiation of tumor progression from pseudoprogression. Arterial spin labeling (ASL) MRI is a non-invasive method for measuring cerebral blood flow (CBF) using blood water as an endogenous tracer, which has great clinical potential for brain tumor imaging and might help to lower the use of gadolinium-based contrast agents. In this review, we discuss recent advances of the ASL method with a special focus on brain tumors, including multi-time point ASL which not only allows more accurate CBF quantification, but also yields arterial transit time (ATT) maps. Another method to reduce dependency on ATT is velocity-selective ASL, for which labeling is directly performed in the imaging volume. By performing a physiological challenge, like a hypercapnia breathing challenge, the reactivity of the tumor's neovasculature can be determined. More recent advances in ASL allow probing the blood-brain barrier (BBB) integrity by measuring the rate of water transport across the BBB (BBB-ASL). By labeling only a single artery, selective ASL sequences can help to identify what part of the tumor is fed by which artery. In conclusion, we see the future potential of ASL MRI not only in replacing contrast agents for perfusion assessment but also in providing additional information to the MRI exam, such as BBB integrity or the architecture of the vascular feeders.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148840686","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":"Clinical evaluation of nnU-Net-based segmentation for enhanced MRCP maximum intensity projection visualization.","authors":"Jinho Kim, Sebastian Werner, Saif Afat, Marcel D Nickel, Florian Knoll","doi":"10.1007/s10334-026-01407-x","DOIUrl":"https://doi.org/10.1007/s10334-026-01407-x","url":null,"abstract":"<p><strong>Purpose: </strong>To evaluate whether deep learning-based segmentation can improve visualization and diagnostic interpretation of MR cholangiopancreatography (MRCP) maximum intensity projections (MIP) by suppressing overlapping high-intensity anatomy while preserving the pancreatobiliary system.</p><p><strong>Methods: </strong>A total of 322 3D MRCP datasets from 162 patients were included. The training set comprised 265 cases from 127 patients, allowing multiple acquisitions per patient, whereas the evaluation set consisted of 35 cases with a single acquisition per patient. A deep learning-based segmentation model was trained using manual annotations with three distinct labels: background, primary structures, and secondary structures. Conservative safety margins were applied to reduce segmentation omissions. Two board-certified radiologists independently rated processed and original MIP images using 4-point Likert scales (1 = poor, 4 = excellent). Two-sided Wilcoxon signed-rank tests with Benjamini-Hochberg correction were used, and inter-reader agreement was assessed using linearly weighted Cohen's <math><mi>κ</mi></math> .</p><p><strong>Results: </strong>Segmentation suppressed obscuring structures and improved biliary visualization. After correction for multiple comparisons, processed images showed significantly improved structure overlap scores compared with original images (3.5 ± 0.9 vs. 2.5 ± 0.6) and higher diagnostic confidence (3.4 ± 0.7 vs. 3.2 ± 0.7).</p><p><strong>Conclusions: </strong>Deep learning-based segmentation improves MRCP MIP visualization by reducing anatomical overlap while preserving clinically relevant pancreatobiliary anatomy.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148818901","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}