Magnetic Resonance in Medicine最新文献

{"title":"RECENet: A Dual-Stream Contrast-Aware Attention Network With Bidirectional Pyramid Consistency for CEST Image Registration.","authors":"Yu Meng, Zhekai Chen, Yang Zhou, Lin Chen","doi":"10.1002/mrm.70542","DOIUrl":"10.1002/mrm.70542","url":null,"abstract":"<p><strong>Purpose: </strong>To develop and evaluate a deep learning framework for deformable registration of CEST MRI that achieves accurate alignment under substantial interoffset contrast variations.</p><p><strong>Methods: </strong>A deep learning architecture, termed Registration CEST Network (RECENet), was developed for deformable registration of CEST images. The framework employed a dual-stream multiscale encoder to independently extract hierarchical features from image pairs acquired at different frequency offsets, preserving contrast-specific information while enabling interoffset correspondence learning. A multilevel contrast-aware attention fusion module was integrated at the bottleneck to recalibrate spatial and channel representations, enhancing alignment under heterogeneous contrast conditions. A bidirectional pyramid decoder progressively estimated forward and backward deformation fields in a coarse-to-fine manner, with inverse-consistency constraints to ensure physically plausible deformations.</p><p><strong>Results: </strong>RECENet was evaluated on multiorgan CEST datasets, including brain, lower extremity, and abdominal imaging, acquired on multiple scanners and field strengths under both synthetic and real deformations. Quantitative comparisons with conventional and deep learning-based methods showed that RECENet achieved higher Dice coefficients, local normalized cross-correlation, mutual information, and structural similarity index, as well as lower root mean square error. Improved spatial alignment enhanced Z-spectrum fidelity and increased metabolite quantification accuracy.</p><p><strong>Conclusion: </strong>RECENet provides a robust and generalizable solution for contrast-invariant deformable registration of CEST MRI, improving spatial alignment and quantitative accuracy.</p>","PeriodicalId":18065,"journal":{"name":"Magnetic Resonance in Medicine","volume":" ","pages":"2950-2966"},"PeriodicalIF":3.2,"publicationDate":"2026-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148630786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep Learning Improves Robustness of Voxelwise Kinetic Modeling for Hyperpolarized Carbon-13 MRI.","authors":"Kofi Deh, Yeona Kang, Tsang-Wei Tu, Rania Jones, Curtiland Deville, Rao Khan","doi":"10.1002/mrm.70549","DOIUrl":"10.1002/mrm.70549","url":null,"abstract":"<p><strong>Purpose: </strong>To evaluate whether deep learning improves the robustness of voxelwise kinetic parameter estimation from hyperpolarized (HP) ¹³C MRI compared with nonlinear least-squares (NLLS) fitting.</p><p><strong>Methods: </strong>A hybrid neural network (NN) was trained on synthetic pyruvate/lactate time courses generated from an open-system two-compartment HP ¹³C signal model to estimate the pyruvate-to-lactate conversion rate ( <math> <mrow><msub><mi>k</mi> <mi>PL</mi></msub> </mrow> </math> ), vascular-extravascular exchange rate ( <math> <mrow><msub><mi>k</mi> <mi>VE</mi></msub> </mrow> </math> ), and vascular volume fraction ( <math> <mrow><msub><mi>v</mi> <mi>B</mi></msub> </mrow> </math> ). NN performance was compared with NLLS across flip-angle schemes, SNR levels, perturbations in acquisition parameters, and in vivo. Matched-ratio simulations tested whether model-estimated ( <math> <mrow><msub><mi>k</mi> <mi>PL</mi></msub> </mrow> </math> ) retained information beyond the Lac/Pyr area-under-the-curve ratio, <math> <mrow><msub><mi>AUC</mi> <mrow><mi>Lac</mi> <mo>/</mo> <mi>Pyr</mi></mrow> </msub> <mo>=</mo> <msub><mi>AUC</mi> <mi>Lac</mi></msub> <mo>/</mo> <msub><mi>AUC</mi> <mi>Pyr</mi></msub> </mrow> </math> .</p><p><strong>Results: </strong>In simulations, NLLS and NN performance were comparable for <math> <mrow><msub><mi>k</mi> <mi>PL</mi></msub> </mrow> </math> estimation at high SNR, whereas the NN outperformed NLLS at low SNR and for the weakly identifiable parameters <math> <mrow><msub><mi>k</mi> <mi>VE</mi></msub> </mrow> </math> and <math> <mrow><msub><mi>v</mi> <mi>B</mi></msub> </mrow> </math> . In vivo, NN maps were more spatially coherent than NLLS maps: <math> <mrow><msub><mi>k</mi> <mi>PL</mi></msub> </mrow> </math> corresponded with <math> <mrow><msub><mi>AUC</mi> <mrow><mi>Lac</mi> <mo>/</mo> <mi>Pyr</mi></mrow> </msub> </mrow> </math> , while <math> <mrow><msub><mi>k</mi> <mi>VE</mi></msub> </mrow> </math> and <math> <mrow><msub><mi>v</mi> <mi>B</mi></msub> </mrow> </math> corresponded with pyruvate AUC. In matched-ratio simulations, NLLS-derived <math> <mrow><msub><mi>k</mi> <mi>PL</mi></msub> </mrow> </math> discriminated the metabolic classes better than NN-derived <math> <mrow><msub><mi>k</mi> <mi>PL</mi></msub> </mrow> </math> , although both model-based estimates retained discriminatory information.</p><p><strong>Conclusion: </strong>NLLS is effective for <math> <mrow><msub><mi>k</mi> <mi>PL</mi></msub> </mrow> </math> estimation under ideal model-matched conditions, whereas the NN provides more stable voxelwise maps, especially for weakly identifiable parameters and under low-SNR or in vivo conditions. Prospective biological or repeatability validation is needed to establish quantitative accuracy.</p>","PeriodicalId":18065,"journal":{"name":"Magnetic Resonance in Medicine","volume":" ","pages":"2857-2869"},"PeriodicalIF":3.2,"publicationDate":"2026-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13619905/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148673679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-Vendor and Multi-Site Characterization of ¹³C Coils for Clinical Studies.","authors":"Emil S Christensen, Andreas Clemmensen, Esben S S Hansen, Jonathan Birchall, Mary A McLean, Christoffer Laustsen, Andreas Kjaer, Thomas L Andersen","doi":"10.1002/mrm.70560","DOIUrl":"10.1002/mrm.70560","url":null,"abstract":"<p><strong>Purpose: </strong>Due to the inherently low signal-to-noise ratio (SNR) domain for ¹³C imaging, optimal coil performance is essential to maximize data quality. Quality control (QC) for ¹³C coils employed in magnetic resonance spectroscopy (MRS) is of paramount importance. This study presents a gradient-recalled echo (GRE) sequence alongside an image-based analysis for SNR estimation and QC of ¹³C coils.</p><p><strong>Methods: </strong>The proposed GRE sequence (slice selective RF pulse, slice thickness 100 mm, 16 averages, 64 × 64 matrix size, 400 × 400 mm FOV, 60 Hz/px BW, 50° FA, 80 ms TR, 14 ms TE, cartesian acquisition trajectory) was comprehensively evaluated on four clinical 3 T systems, across three sites and two vendors. Thirteen coils were evaluated, including multiple surface coils (transmit/receive and receive only) and volume coils for different body parts. The GRE sequence was compared with a previously described chemical shift imaging (CSI) technique for QC of ¹³C coils. The GRE sequence is widely available and built into all MR systems. In contrast, the CSI sequence is more specialized and is not available for all imaging systems.</p><p><strong>Results: </strong>A Passing-Bablok regression and a Spearman correlation of 0.78 demonstrated good agreement of the two methods. The GRE approach offers reduced acquisition time and simplified analysis with SNR trends demonstrating reproducible coil performance across all sites and vendors.</p><p><strong>Conclusion: </strong>This standardization aims to strengthen multi-center trials by ensuring data comparability and reliability, advancing the clinical translation of ¹³C MRS methodologies. The results and analysis pipeline is made publicly available to facilitate implementation and coil comparisons across institutions.</p>","PeriodicalId":18065,"journal":{"name":"Magnetic Resonance in Medicine","volume":" ","pages":"2885-2893"},"PeriodicalIF":3.2,"publicationDate":"2026-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13619849/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148795179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optical Detuning Strategies for Shielded Loop Resonators.","authors":"Jakob Gerlach, Reza Aghabagheri, Zining Liu, Shuai Liu, Morteza Teymoori, Çağlar Ataman, Michael Bock, Ali Caglar Özen","doi":"10.1002/mrm.70556","DOIUrl":"10.1002/mrm.70556","url":null,"abstract":"<p><strong>Purpose: </strong>To compare detuning performance and evaluate power requirements of optical detuning methods and to demonstrate feasibility of an optically-detuned 4-channel receive array.</p><p><strong>Methods: </strong>Four optical detuning methods were compared in simulations, bench tests, and phantom measurements at 3T against conventional galvanic detuning. Passive detuning was also tested as an additional wireless detuning option. Optical power requirements for the detuning networks were investigated, and a flexible optically-detuned 4-channel shielded loop resonator (SLR) array was constructed and tested in vivo.</p><p><strong>Results: </strong>A photodiode-PIN diode combination exhibited the highest unloaded Q (68.6) and Q ratio (1.9), with detuning performance and signal-to-noise ratio comparable to that of galvanic detuning at an optical power of 10 mW. Using this detuning strategy, in vivo images of the knee and brain were successfully acquired with a 4-channel flexible array.</p><p><strong>Conclusion: </strong>Optical detuning is a practical alternative to conventional galvanic detuning in flexible SLR arrays. With developments in optical signal and power transmission, optimizing optical detuning while meeting manageable power requirements is an important step toward fully optical receive coil arrays. This study provides a reference point for the total optical power required for active detuning in such optical coil systems.</p>","PeriodicalId":18065,"journal":{"name":"Magnetic Resonance in Medicine","volume":" ","pages":"3011-3020"},"PeriodicalIF":3.2,"publicationDate":"2026-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13619850/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148669958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Placental Blood-Flow Velocity Quantification From Diffusion MRI.","authors":"ZhuangJian Yang, Diana Cruz De Oliveira, Leevi Kerkelä, Marco Palombo, Elizabeth Powell, Christopher S Parker, Daniel Cromb, Lisa Story, Serena J Counsell, Kelly Payette, Joseph V Hajnal, Jana Hutter, Rebecca J Shipley, Daniel C Alexander, Paddy J Slator","doi":"10.1002/mrm.70551","DOIUrl":"10.1002/mrm.70551","url":null,"abstract":"<p><strong>Purpose: </strong>Altered placental capillary blood flow is closely linked to obstetric complications, yet quantifying capillary-scale blood velocity remains challenging with existing imaging methods. This is partially because capillary networks form disordered microvascular beds at the voxel scale, rather than coherent, directional vessels. Here, we combine Monte Carlo (MC) simulations with machine learning to estimate placental capillary blood velocity directly from diffusion MRI (dMRI) data.</p><p><strong>Methods: </strong>MC simulations incorporating perfusion and diffusion were performed to generate signal dictionaries for supervised machine learning regressors (random forest [RF] and multilayer perceptron [MLP]) to estimate velocity, perfusion fraction and diffusivity. The trained regressors were applied to simulated and in vivo dMRI data, with intravoxel incoherent motion (IVIM)-based estimates as baselines for comparison.</p><p><strong>Results: </strong>Our approach outperformed IVIM-based methods on simulated test data in recovering ground-truth parameters. Among the evaluated models, the MC-based MLP approach produced physiologically reasonable estimates of velocity in in vivo placentas, in agreement with previously reported measures and exhibited greater sensitivity than IVIM-generated methods.</p><p><strong>Conclusion: </strong>This study presents an approach to characterize capillary perfusion that alternates conventional IVIM models, particularly in organs such as the placenta, where pseudo-diffusion coefficient can be similar to tissue diffusion coefficient, limiting reliable IVIM parameter separation. Our method could enable detection of capillary blood-flow alterations, which could help identify pathological placental blood-flow conditions and potentially diagnosis relevant diseases, such as preeclampsia and fetal growth restriction. More broadly, the approach may translate to other organs where microscale blood-flow changes are key indicators of underlying pathologies.</p>","PeriodicalId":18065,"journal":{"name":"Magnetic Resonance in Medicine","volume":" ","pages":"2967-2977"},"PeriodicalIF":3.2,"publicationDate":"2026-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13619870/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148706933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Low-Cost, Microcontroller-Based Gas Delivery System for Respiratory Stimuli in MRI Studies.","authors":"Nicholas P Blockley, Ahlam A Alzaidi, Colette C Milbourn, Daniel P Bulte, Andrew Rudgewick-Brown, Sebastian W Rieger","doi":"10.1002/mrm.70543","DOIUrl":"10.1002/mrm.70543","url":null,"abstract":"<p><strong>Purpose: </strong>The design and validation of a low-cost, microcontroller-based gas delivery system that automates fixed inspired respiratory stimuli for MRI experiments.</p><p><strong>Methods: </strong>The system uses three solenoid valves controlled by an Arduino-based circuit to switch between premixed medical gases according to predefined timings. By using the MRI scanner external timing signal, gas delivery can be synchronized with image acquisition. The system was constructed using commercial components, with a material cost ∼£650 GBP (∼$880 USD). The system was integrated with a single-use breathing circuit and evaluated using hypercapnic and hyperoxic stimuli. End-tidal oxygen (O₂) and carbon dioxide (CO₂) were measured using a respiratory gas analyzer and physiological responses were assessed using BOLD MRI at 3 T.</p><p><strong>Results: </strong>The system delivered reliable, repeatable gas transitions during MRI-triggered protocols. During hypercapnia (elevated carbon dioxide level, 5% CO₂) (n = 15), the mean increase in end-tidal CO₂ was 8.7 ± 1.8 mmHg from a baseline of 32.2 ± 3.1 mmHg, producing a mean gray matter BOLD signal increase of 3.2% ± 1.7%. During hyperoxia (elevated oxygen level, 60.5% O₂) (n = 15), the mean increase in end-tidal O₂ was 292.3 ± 59.0 mmHg from a baseline of 114.5 ± 10.7 mmHg, with an associated BOLD signal change of 1.2% ± 1.7%. Across both protocols, respiratory and BOLD responses were consistent across participants.</p><p><strong>Conclusion: </strong>This microcontroller-based system provides an inexpensive and reliable method for administering fixed inspired respiratory stimuli with automated MRI synchronization. It offers an intermediate option between manual systems and commercial gas blenders, making it well suited for technical and methodological studies in cerebrovascular reactivity, hyperoxia-BOLD, and related applications.</p>","PeriodicalId":18065,"journal":{"name":"Magnetic Resonance in Medicine","volume":" ","pages":"2907-2913"},"PeriodicalIF":3.2,"publicationDate":"2026-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148727805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ArteryX: A Reliable End-To-End Toolbox for Standardized Intracranial Artery Feature Extraction From 3D TOF-MRA.","authors":"Abrar Faiyaz, Nhat Hoang, Giovanni Schifitto, Md Nasir Uddin","doi":"10.1002/mrm.70564","DOIUrl":"10.1002/mrm.70564","url":null,"abstract":"<p><p>Cerebrovascular research heavily relies on quantitative analysis of intracranial arteries from time-of-flight magnetic resonance angiography (TOF-MRA), yet existing processing pipelines remain limited by inconsistent artery labeling and a high manual correction burden. We present ArteryX, a toolbox for extracting artery features that standardizes artery classification across proximal and distal vascular territories. ArteryX integrates segmentation handling, isotropic geometric processing, vessel-fused graph construction, and constrained landmark-based classification within a unified artery-specific feature reporting and reproducible workflow. The toolbox extracts artery-level morphological, topological, and complexity features including total length, mean radius, volume, surface area, branch count, tortuosity, and fractal dimensionality for standardized artery segments. Test and validation were performed using two complementary datasets: (1) publicly available TopBrain-Challenge benchmarking with annotated arteries, (2) synthetic known-reference validation. Another dataset with and without cerebral small vessel disease (CSVD) was used for exploratory in vivo analysis. In TopBrain data analyses, ArteryX with supervised nnUnet segmentation showed minimal bias, while iCafe showed larger bias and a large limit of agreement. ArteryX demonstrated robust downstream quantification performance across segmentation sources (unsupervised/supervised). Agreement analyses showed minimal bias for radius and good sensitivity of extent-dependent metrics throughout the noisier segmentations compared to the state-of-the-art iCafe toolbox. Furthermore, a stage-wise human-in-the-loop protocol required less manual intervention than iCafe in the reported setup. In an exploratory in vivo cohort (48 CSVD+, 20 CSVD-), ArteryX-derived distal and territory-level features showed group-level differences that were not observed with iCafe. To facilitate adoption and reproducibility, ArteryX is designed as a community-oriented toolbox with versioned builds, tutorials, and documentation.</p>","PeriodicalId":18065,"journal":{"name":"Magnetic Resonance in Medicine","volume":" ","pages":"2914-2924"},"PeriodicalIF":3.2,"publicationDate":"2026-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148713012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"<ArticleTitle xmlns:ns0=\"http://www.w3.org/1998/Math/MathML\">Incomplete Spoiling Correction for 3D <ns0:math> <ns0:mrow><ns0:msub><ns0:mi>T</ns0:mi> <ns0:mn>1</ns0:mn></ns0:msub> </ns0:mrow> </ns0:math> Mapping.","authors":"Gabriela Belsley, Damian J Tyler, Matthew D Robson, Elizabeth M Tunnicliffe","doi":"10.1002/mrm.70559","DOIUrl":"10.1002/mrm.70559","url":null,"abstract":"<p><strong>Purpose: </strong>Assess the impact of incomplete spoiling and spatial saturation on <math> <mrow><msub><mi>T</mi> <mn>1</mn></msub> </mrow> </math> mapping using the variable flip angle (VFA) spoiled gradient recalled echo sequence (SPGR). Develop a correction for incomplete spoiling that results in an accurate estimate of <math> <mrow><msub><mi>T</mi> <mn>1</mn></msub> </mrow> </math> , essential for quantitative MRI applications.</p><p><strong>Methods: </strong>A correction factor, derived from extended phase graph simulations, was applied to the measured SPGR signal to account for deviations from the theoretical steady-state signal. An iterative fitting process was used, refining the incomplete spoiling correction factor at each step based on the updated <math> <mrow><msub><mi>T</mi> <mn>1</mn></msub> </mrow> </math> estimate. The incomplete spoiling correction method was validated against inversion recovery spin echo in phantom experiments and applied to in vivo data at 3T. Additionally, the hypothesis that spatial saturation disrupts the steady-state was also tested and validated in a phantom.</p><p><strong>Results: </strong>Without a correction, the median <math> <mrow><msub><mi>T</mi> <mn>1</mn></msub> </mrow> </math> error was +7.4% (IQR [4.4, 9.6]%) in both simulations and phantom experiments. After applying the correction, the median <math> <mrow><msub><mi>T</mi> <mn>1</mn></msub> </mrow> </math> error decreased to -0.3% (IQR [-2.5, 2.1]%). In vivo, incomplete spoiling caused <math> <mrow><msub><mi>T</mi> <mn>1</mn></msub> </mrow> </math> overestimation of 10-50 ms depending on <math> <mrow><msubsup><mi>B</mi> <mn>1</mn> <mo>+</mo></msubsup> </mrow> </math> inhomogeneity. Spatial saturation induced on average a -10% <math> <mrow><msub><mi>T</mi> <mn>1</mn></msub> </mrow> </math> bias.</p><p><strong>Conclusion: </strong>A correction for incomplete spoiling is essential to achieve an accurate measure of <math> <mrow><msub><mi>T</mi> <mn>1</mn></msub> </mrow> </math> using the VFA SPGR method, addressing systematic <math> <mrow><msub><mi>T</mi> <mn>1</mn></msub> </mrow> </math> overestimation when using this <math> <mrow><msub><mi>T</mi> <mn>1</mn></msub> </mrow> </math> mapping technique. Furthermore, other mechanisms that may disrupt the steady-state signal, such as spatial saturation, should be considered.</p>","PeriodicalId":18065,"journal":{"name":"Magnetic Resonance in Medicine","volume":" ","pages":"2848-2856"},"PeriodicalIF":3.2,"publicationDate":"2026-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13619879/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148723475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"3D Printing of Subject-Specific Passive Shims for In Vivo Small-Animal Magnetic Resonance Imaging.","authors":"An Vanduffel, Cesar Parra-Cabrera, Hanne Vanduffel, Quentin Goudard, Kasia Błażejczyk, Shannon Helsper, Uwe Himmelreich, Dimitrios Sakellariou, Rob Ameloot","doi":"10.1002/mrm.70520","DOIUrl":"10.1002/mrm.70520","url":null,"abstract":"<p><strong>Purpose: </strong>Magnetic resonance imaging (MRI) is a non-invasive method that relies on a highly homogeneous B₀ magnetic field to generate high-quality images. However, subject-specific inhomogeneities, induced by magnetic susceptibility differences, can degrade image quality and cause artifacts and are often inadequately corrected by traditional active or passive shimming methods. This work aims to create a new passive shimming method to overcome these problems.</p><p><strong>Method: </strong>This study introduces an innovative approach to developing custom, subject-specific passive shims 3D-printed with a binder and a ferromagnetic ink. The optimal spatial distribution and concentration of ferromagnetic material within the shim are calculated using a custom algorithm that minimizes the magnetic field standard deviation.</p><p><strong>Results: </strong>The shim design and fabrication process is demonstrated for in vivo passive shimming of a rat brain, yielding a 21% improvement in magnetic field homogeneity and improved image quality in spin-echo echo-planar imaging scans, with a 65% increase in the Dice-Sørensen similarity coefficient.</p><p><strong>Conclusion: </strong>This approach highlights the potential of combining computational optimization with additive manufacturing for effective, subject-specific passive shimming in MRI.</p>","PeriodicalId":18065,"journal":{"name":"Magnetic Resonance in Medicine","volume":" ","pages":"2978-2987"},"PeriodicalIF":3.2,"publicationDate":"2026-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148456232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Voxel-Wise T2 Distribution Framework for Lesion Severity Stratification and Treatment-Response Assessment in Stroke: Insights Into Suberoylanilide Hydroxamic Acid-Induced Neuroprotection.","authors":"Andrea Díaz-Pérez, Clara Penas, Francesc Jiménez-Altayó, Silvia Lope-Piedrafita","doi":"10.1002/mrm.70552","DOIUrl":"10.1002/mrm.70552","url":null,"abstract":"<p><strong>Purpose: </strong>To evaluate lesion severity distribution in ischaemic brain lesions in spontaneously hypertensive rats (SHR) subjected to 90-min transient middle cerebral artery occlusion (tMCAO), and to determine whether epigenetically based neuroprotection modifies lesion severity profiles using a voxel-wise T2 distribution framework.</p><p><strong>Theory and methods: </strong>Stroke treatments are commonly evaluated by quantifying infarct size using histology or MRI, approaches that average across lesions and may obscure heterogeneous tissue responses. SHR underwent 90-min intraluminal MCAO and received suberoylanilide hydroxamic acid (SAHA) 4 h after reperfusion. Quantitative T2 maps were acquired at Days 1 and 8 postocclusion. Voxel-wise histogram analysis defined severity thresholds (T2 < 70 ms mild; 70-90 ms moderate; > 90 ms severe). Region-stratified RT-qPCR assessing neuronal, inflammatory, and apoptotic markers provided complementary biological context for interpreting region- and severity-resolved MRI patterns.</p><p><strong>Results: </strong>Severity-bin stratification of voxel-wise T2 values quantified how lesion composition redistributed from severe toward moderate/mild classes across time and regions (cortex vs. subcortex) in association with SAHA treatment. Cortical molecular markers corroborated imaging-defined tissue preservation but did not resolve subcortical differences detected by voxel-wise MRI. Untreated animals exhibited partial spontaneous attenuation of extreme subcortical T2 abnormalities. Histogram descriptors correlated with behavioral outcomes.</p><p><strong>Conclusion: </strong>Voxel-wise T2 distribution analysis provides a complementary, severity-stratified description of lesion composition and its evolution over time, alongside conventional endpoints such as infarct volume and mean/median T2. The approach is readily applicable in preclinical MRI and is potentially translatable, warranting further validation across broader imaging settings.</p>","PeriodicalId":18065,"journal":{"name":"Magnetic Resonance in Medicine","volume":" ","pages":"2870-2884"},"PeriodicalIF":3.2,"publicationDate":"2026-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13619855/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148679131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}