NMR in Biomedicine最新文献

{"title":"Cerebral Hemodynamic Changes During Cardiac Surgery: A Feasibility MR Study in Piglets.","authors":"Dominik T Schulte, Ruth O'Gorman Tuura, Henning Richter, Michael Hofmann, Francesca Del Chicca, Tobias Aigner, Christoph Loeschmann, Martina Lentini, Manuela Wieser, Frauke Seehusen, Rima Bektas, Melanie Zeilinger, Martin O Schmiady, Marianne Schmid Daners","doi":"10.1002/nbm.70284","DOIUrl":"10.1002/nbm.70284","url":null,"abstract":"<p><p>Congenital heart disease often requires early surgical intervention. Cardiopulmonary bypass (CPB) is a standard procedure, but infants undergoing CPB show an increased risk of postoperative white matter injury. These injuries are associated with adverse neurodevelopmental outcomes, yet the underlying mechanisms remain poorly understood. MR imaging offers unique opportunities to study cerebral perfusion and metabolism in vivo but has not previously been feasible during CPB with a heart-lung machine (HLM) in close proximity to the patient and the MR scanner, respectively, because conventional HLMs interfere with scanner operation. To address this limitation, we developed an MR-conditional HLM and evaluated it in an in vivo piglet model, which closely mimics the neonatal brain and circulation. Unlike conventional systems, our MR-conditional roller pump can be positioned directly inside the scanner bore without compromising imaging quality or pump performance. Four trials were conducted, in which piglets were cannulated and maintained on CPB inside the MR scanner. During CPB, cooling, rewarming, and unilateral carotid clamping were performed while repeatedly acquiring MR data on flow, diffusion, perfusion, and metabolism. Crucial brain structures-including the basal ganglia, hippocampus, and internal capsule-were consistently visualized without artifacts, and no disturbances occurred in pump operation or monitoring signals. The MR scans revealed flow-related changes and a progressive increase in lactate, suggesting the onset of metabolic stress under hypoperfusion. These results demonstrate the technical feasibility of performing CPB within the MR scanner using an MR-conditional HLM. Although not sufficient to identify specific mechanisms of brain injury, this platform provides a unique foundation for mechanistic studies in relevant large-animal models. In the future, such an approach could help identify early markers of cerebral vulnerability, improve the safety of pediatric cardiac surgery, and inform the development of neuroprotective strategies for CPB and extracorporeal membrane oxygenation patients.</p>","PeriodicalId":19309,"journal":{"name":"NMR in Biomedicine","volume":"39 5","pages":"e70284"},"PeriodicalIF":2.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13050816/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147623543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep Learning Reconstruction Enables Diagnostic-Quality 0.4T Knee and Spine MRI in One-Third of the Time.","authors":"Daisy M van den Berg, Rosario Varriale, Fabrizio Ferrando, Paolo Traverso, Luca Balbi, Giacomo Belgiorno, Kerensa Beekman, Laura Kox, Gustav J Strijkers, Matthan W A Caan","doi":"10.1002/nbm.70274","DOIUrl":"10.1002/nbm.70274","url":null,"abstract":"<p><p>There has been a growing interest in low-field MRI due to its lower costs, enabling an increase in accessibility of MRI worldwide. Long scan times are currently needed to obtain high-quality images. The aim of our study was to accelerate low-field 0.4T musculoskeletal MRI using deep learning and evaluate maximum acceleration via assessment by two expert radiologists. A cascades of independently recurrent inference machines (CIRIM) model was trained using knee and spine 2D multislice scans, retrospectively undersampled in k-space. The heterogeneous dataset included varied contrasts, orientations, and matrix sizes. To determine the maximum possible acceleration factor, the undersampling pattern and loss function of the CIRIM were optimized using the knee dataset. Models were trained for acceleration factors 1.5-4. The different acceleration factors were evaluated quantitatively and clinically, with radiologist scores compared using Kendall's Tau and Cohen's Kappa. To assess the model's generalizability, two prospectively undersampled scans were evaluated, and the knee-trained models were tested on spine data. CIRIM accurately reconstructed all data, with slight metric degradation at higher accelerations. Combining L1, structural similarity index measure (SSIM), and perceptual loss improved sharpness, while undersampling pattern differences were minimal. Clinical scores from both radiologists declined with acceleration, reflected in Kendall's Tau values of 0.64, 0.64, 0.54, and 0.55 for image quality, sharpness, anatomical conspicuity, and artifacts. Inter-observer agreement was low (Cohen's kappa: 0.227-0.299). The model generalized well, reconstructing spine data with a knee-trained model at comparable quality and successfully handling prospectively undersampled scans. CIRIM consistently delivered high-quality reconstructions, demonstrating excellent robustness to variations in contrast, orientation, matrix size, and anatomy. Its ability to generalize across anatomies and handle prospectively undersampled scans highlights its practical utility. The differences in reading for higher accelerations between radiologists suggest that the optimal acceleration factor is context-dependent and should be tailored to the specific diagnostic task.</p>","PeriodicalId":19309,"journal":{"name":"NMR in Biomedicine","volume":"39 5","pages":"e70274"},"PeriodicalIF":2.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13006165/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147499613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Accelerating PREFUL MRI: Comparison of Registration Methods and Impact of Time Series Reduction.","authors":"A Voskrebenzev, G H Pöhler, F Klimeš, M M Klein, R A Müller, F Wacker, J M Hohlfeld, J Vogel-Claussen","doi":"10.1002/nbm.70283","DOIUrl":"10.1002/nbm.70283","url":null,"abstract":"<p><p>The purpose of this study is to evaluate whether accelerated registration and reduced acquisition times preserve the robustness of phase-resolved functional lung (PREFUL) MRI, thereby improving clinical feasibility by facilitating integration into tight time slots and enabling faster turnaround of results. PREFUL MRI at 1.5 T was retrospectively analyzed in 28 patients with chronic obstructive pulmonary disease (COPD) and 56 healthy volunteers. Image registration was performed using Advanced Normalization Tools (ANTs) and Forsberg. Time series (TS) were truncated from 55 to 45, 30, and 15 s per slice. The 55-s variant was evaluated twice to assess potential nondeterministic effects; the first served as the reference. PREFUL parameters, including regional ventilation, quantified perfusion (QQ), flow volume loop correlation metric (FVL-CM) and corresponding defect percentages, were compared across registration methods and TS lengths using Wilcoxon tests, Pearson correlations, intraclass correlation coefficients (ICC), and regional overlap analysis. Forsberg reduced computation time by ~20-fold (3 vs. 58 min per slice) while maintaining trends and repeatability. Although functional values were slightly lower and defect scores higher, correlations between registrations exceeded 90% for most parameters, with regional overlap ≥ 97% in healthy volunteers and ≥ 80% in COPD patients. Shortening the TS to 30 s introduced minor deviations but preserved overlap (≥ 79%) and strong correlations (≥ 77%) compared with 55 s, except for QQ. Larger deviations occurred primarily at 15 s. Repeatability remained moderate to high (ICC ≥ 68%) for all parameters, except QQ, down to 30 s, with the FVL-CM, perfusion defect percentage and amount of nondefect regions in COPD being most stable (ICC ≥ 72%). Forsberg provides results comparable to ANTs at a fraction of the processing time, enabling PREFUL analysis within a practical timeframe. Acquisition for each slice may be reduced to 30 s without compromising robustness, supporting more efficient protocols, although caution is warranted for QQ.</p>","PeriodicalId":19309,"journal":{"name":"NMR in Biomedicine","volume":"39 5","pages":"e70283"},"PeriodicalIF":2.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13066768/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147645900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the Role of Vascular Factors and Tissue Properties in Pulsatile Brain Deformation.","authors":"Marius Burman Ingeberg, Elijah Van Houten, Andrej Shoykhet, Jaco J M Zwanenburg","doi":"10.1002/nbm.70282","DOIUrl":"10.1002/nbm.70282","url":null,"abstract":"<p><p>Strain tensor imaging (STI) provides precise measurements of brain tissue deformation caused by cerebral arterial pulsations (CAPs). This CAP-related brain tissue deformation is expressed in rotation-invariant strain metrics, such as volumetric strain and octahedral shear strain, which hold promise as quantitative markers of the (mechanical) properties of both the intracerebral vasculature and the intervascular tissue components. However, the extent to which these strain metrics can be specifically linked to the underlying anatomical, vascular, and tissue properties remains largely unknown. This study aims to explore the relationship between STI metrics and independent markers of pulse pressure (arterial transit time, ATT), vascular function (cerebral blood volume, CBV; cerebral blood flow, CBF; mean transit time, MTT), and tissue properties (shear stiffness). Volumetric and octahedral shear strain were computed from previously obtained 7T displacement data (approximately 2-mm isotropic resolution) of eight healthy subjects (27 ± 7 years). Shear stiffness maps were generated from the same displacement data set using poroviscoelastic intrinsic MR elastography. Regional values of CBV, CBF, MTT, and ATT were obtained from standard-space atlases. Linear mixed-effects models were used to investigate potential regional relationships between specific strain metrics and the corresponding tissue, pulse pressure, or vascular markers. Volumetric strain showed significant positive correlations with CBV (globally and in cortical gray and white matters) and significant negative correlations with ATT (globally and in cortical gray and white matters), but not with shear stiffness. Octahedral shear strain showed a significant negative correlation with shear stiffness (globally and in subcortical gray and white matters) and also with ATT (globally and in cortical gray matter). Volumetric strain reflects mainly vascular properties (pulse pressure and blood volume), whereas octahedral shear strain is more sensitive to tissue properties. These findings provide a foundation for future studies that investigate the physiological characteristics reflected by these strain metrics and their intricate interplay.</p>","PeriodicalId":19309,"journal":{"name":"NMR in Biomedicine","volume":"39 5","pages":"e70282"},"PeriodicalIF":2.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13036297/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147581792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Optimised Multishot EPI Protocol for Ex Vivo Mouse Brain Diffusion MRI With Gd-DOTA Contrast Enhancement.","authors":"Elise Cosenza, Nadège Corbin, Emeline J Ribot, Arnaud Boré, Maxime Descoteaux, Sylvain Miraux, Laurent Petit","doi":"10.1002/nbm.70270","DOIUrl":"10.1002/nbm.70270","url":null,"abstract":"<p><p>Diffusion-weighted magnetic resonance imaging (dMRI) in small animal models is often limited by long acquisition times, low signal-to-noise ratio (SNR) and magnetic susceptibility artefacts. We developed and optimised a 3D spin-echo multishot EPI (SE-msEPI) protocol combined with Gd-DOTA administration to enable efficient, high-quality ex vivo diffusion imaging of the mouse brain. Systematic testing demonstrated that 12 EPI shots provided the optimal trade-off between artefact reduction, SNR and acquisition duration. Gd-DOTA incubation at 3 mM for 7 days allowed the TR to be reduced from 1500 to 400 ms without compromising diffusion metrics, yielding more than threefold SNR increase. This optimisation enabled whole-brain acquisitions at 100-μm isotropic resolution with 60 directions (b = 3000 s/mm²) in ~11 h, a fourfold acceleration compared to standard long-TR protocols. Fractional anisotropy values in Gd-DOTA-enhanced acquisitions closely matched those of the long-TR reference, while low-SNR short-TR baseline and postwashout acquisitions exhibited systematic FA underestimation. Residual error analysis and tractography performance metrics further demonstrated the improved image quality and anatomically plausible reconstruction of white matter pathways under Gd-DOTA-enhanced conditions. Beyond these technical gains, the optimised protocol provides a reproducible framework for high-throughput ex vivo diffusion MRI, enabling connectomics and microstructural studies in mouse models with greater efficiency, increased reuse of tissue sample and reduced animal use.</p>","PeriodicalId":19309,"journal":{"name":"NMR in Biomedicine","volume":"39 4","pages":"e70270"},"PeriodicalIF":2.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147458889","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":"Deep Learning Myocardial Segmentation in 3D Whole-Heart Joint T1/T2 Mapping: Comparison of nnU-Net and MA-SAM.","authors":"G Carlota Rivera, Alina Hua, René M Botnar, Claudia Prieto","doi":"10.1002/nbm.70252","DOIUrl":"10.1002/nbm.70252","url":null,"abstract":"<p><p>This study compares two advanced deep learning models, nnU-Net and MA-SAM, for automatic segmentation of the left ventricle (LV) myocardium using 3D whole-heart T1 and T2 mapping, with the goal of evaluating their performance in terms of segmentation metrics and computational efficiency. The dataset consisted of 3D whole-heart joint T1/T2 maps from 55 subjects (15 healthy and 40 with suspected cardiovascular disease), with manual segmentations performed by an experienced clinical reader. For model development, 45 subjects were used for training, while five subjects were used for validation in each run. A cross-validation strategy with 10 independent training runs was employed, such that all subjects were used for validation across different folds. An independent hold-out test set of five subjects, which were never used during training or validation, was reserved for final testing. The fourth interleaved volume, which provided the highest myocardial-blood contrast, was used in both networks. Segmentation performance was assessed using Dice similarity score, intersection over union (IoU), and Hausdorff distance at 95%. T1 and T2 maps were generated by matching water images to a simulated dictionary and compared to manual segmentations. Both models achieved comparable segmentation performance, with nnU-Net obtaining a Dice score (DSC) of 0.91 compared to 0.90 for MA-SAM, and IoU values of 0.83 and 0.82, respectively. Regarding boundary accuracy, nnU-Net achieved a lower Hausdorff distance (HD95) of 1.64 mm, compared to 1.77 mm for MA-SAM. In addition, nnU-Net demonstrated markedly greater computational efficiency, requiring significantly less training time (5 h vs. 9 h for MA-SAM) and shorter inference time (3.67 s vs. 76.67 s), underscoring its suitability for clinical applications.</p>","PeriodicalId":19309,"journal":{"name":"NMR in Biomedicine","volume":"39 4","pages":"e70252"},"PeriodicalIF":2.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147365863","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":"Therapeutic Effects Assessment in Acute Lung Injury Using Hyperpolarized ¹²⁹Xe Magnetic Resonance.","authors":"Yu Zheng, Haidong Li, Ming Zhang, Xiaoling Liu, Hongchuang Li, Mingyan Yu, Wenjie Wang, Jiawei Zhu, Xiuchao Zhao, Haofeng Li, Siya Wei, Yeqing Han, Xin Zhou","doi":"10.1002/nbm.70254","DOIUrl":"10.1002/nbm.70254","url":null,"abstract":"<p><p>Therapeutic effects in acute lung injury (ALI) vary considerably among individuals, presenting a significant clinical challenge in optimizing treatment strategies-particularly with agents such as glucocorticoids. Non-invasive techniques capable of quantifying pulmonary physiological changes in the lung are essential for evaluating treatment efficacy and elucidating underlying mechanisms. Herein, we investigated the feasibility of hyperpolarized ¹²⁹Xe magnetic resonance (MR) for assessing the effects of dexamethasone treatment in a rat model of ALI. Fifteen Wistar rats were randomly assigned to three groups (n = 5 each): a treatment group with lipopolysaccharide (LPS)-induced ALI treated with dexamethasone (DEX), an ALI group subjected to the same LPS induction but treated with normal saline, and a control group receiving only normal saline. All rats underwent ¹²⁹Xe MR, pulmonary function tests (PFTs), computed tomography (CT), and histological analysis. Quantitative results from ¹²⁹Xe MR were analyzed using Kruskal-Wallis tests followed by Conover-Iman multiple comparison tests. Correlations among MRI, PFTs, and CT findings were evaluated. The ratio of ¹²⁹Xe signal in red blood cells to pulmonary Membrane (RBC/Mem) was reduced in the ALI group compared with the control group (median, 0.356 [IQR,0.035] vs. 0.607 [IQR,0.086], p < 0.001) and partially recovered in the treatment group (p < 0.001). Notably, persistent functional impairment in the treatment group was not detected by PFTs or CT imaging. The RBC/Mem correlated well with forced vital capacity (FVC) and mean lung density (MLD) (both p < 0.05). Additionally, hematocrit (Hct) increased in the treatment group compared to the ALI group (Hct: median, 0.242 [IQR, 0.031] vs. 0.216 [IQR, 0.019], p < 0.001). These findings demonstrate the potential of hyperpolarized ¹²⁹Xe MR as a non-invasive and highly sensitive modality for detecting subtle or residual gas-exchange abnormalities, supporting its further application in interventional studies of acute lung injury.</p>","PeriodicalId":19309,"journal":{"name":"NMR in Biomedicine","volume":"39 4","pages":"e70254"},"PeriodicalIF":2.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147365942","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":"Anomaly Detection for Structural and Functional Connectivity in Glioma Patients.","authors":"Maria Colpo, Ryan Pollitt, Alexander Leemans, Diego Cecchin, Maurizio Corbetta, Alessandra Bertoldo, Alberto De Luca","doi":"10.1002/nbm.70238","DOIUrl":"10.1002/nbm.70238","url":null,"abstract":"<p><p>Brain connectivity, quantified with diffusion MRI (structural connectivity, SC) and resting-state functional MRI (functional connectivity, FC), can offer crucial insights into glioma-brain network interactions. Currently, no standardized approach exists to integrate information from FC and SC and to identify potential tumor-induced abnormalities at the single-patient level. Variational autoencoders (VAEs) have been shown to be promising for learning the distribution of features representing a healthy brain and deviations thereof and can naturally be applicable to multiple modalities. This study explores the potential of VAE to integrate FC and SC and detect multimodal anomalies in brain connectivity in glioma patients. The VAE is trained on concatenated FC-SC healthy data to learn how to reconstruct normative connectivity patterns. After ad hoc transfer learning, the model parameters are applied to the oncological dataset, to obtain the healthy version of the pathological matrices. Given the healthy, pathological, and reconstructed matrices, a statistic is developed with the goal of identifying specific alterations in SC, FC, and their FC + SC integration in glioma patients. SC, FC, and FC + SC abnormalities are compared with each other to explore their interplay and their link with tumor and surrounding brain tissues. Results show that FC is more sensitive to alterations distant from the tumor, while SC is more affected in its vicinity. Then, the alterations identified by FC are generally more in agreement with the alterations identified by FC + SC compared with those highlighted by SC. Moreover, SC abnormalities never overlap with FC + SC out of the tumor, and FC and SC single impairments partially overlap within the tumor core and never overlie in other brain tissues. This information could facilitate patient stratification, prognostic modeling, and personalized treatment planning.</p>","PeriodicalId":19309,"journal":{"name":"NMR in Biomedicine","volume":"39 4","pages":"e70238"},"PeriodicalIF":2.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12973340/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147390699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial Coefficient of Variation (sCOV) From ASL MRI Reveals Global Cerebrovascular Dysfunction in Long COVID.","authors":"Sol A Cataldo, Silvina G Horovitz, Laura Margulis, Andrea Micciulli, Florencia Sarmiento, Melisa Monteleone, Marcela Brocco, Martín A Belzunce","doi":"10.1002/nbm.70264","DOIUrl":"10.1002/nbm.70264","url":null,"abstract":"<p><p>Long COVID is increasingly associated with persistent neurological and cognitive symptoms, yet its underlying mechanisms remain unclear. Vascular dysregulation, endothelial dysfunction, and microvascular injury have been proposed as potential contributors. Arterial spin labeling (ASL) MRI allows noninvasive quantification of cerebral blood flow (CBF) and assessment of vascular function. Previous studies have reported hypoperfusion in long COVID patients, but few have accounted for delayed arterial transit time, which can affect ASL quantification. The spatial coefficient of variation (sCOV) has been previously used as a proxy of arterial transit time, providing a noninvasive marker of global cerebrovascular function. We examined 186 adults from an Argentine cohort (145 long COVID and 41 controls), approximately 2 years postinfection. Three-dimensional pulsed ASL data were processed with ExploreASL to quantify CBF and sCOV in gray matter and lobar regions. Group comparisons were performed using multivariate models adjusted for age, sex, and white matter hyperintensity (WMH) volume. Long COVID participants showed significantly higher global gray matter sCOV compared with controls (p = 0.02), with consistent regional trends across the frontal (L: p = 0.05; R: p = 0.07), temporal (L: p = 0.05; R: p = 0.08), parietal (L: p = 0.07; R: p = 0.06), occipital (L: p = 0.08; R: p = 0.05), and insular (L: p = 0.01; R: p = 0.15) lobes after FDR correction. Mean global, lobar, and regional gray matter CBF and WMH volumes did not differ significantly between groups. Increased sCOV, reflecting delayed arterial transit and reduced vascular efficiency, indicates widespread cerebrovascular dysfunction in the absence of perfusion deficits and not associated with white matter hyperintensities. These findings provide evidence of global vascular impairment in long COVID and support sCOV as a sensitive, noninvasive biomarker of cerebrovascular health.</p>","PeriodicalId":19309,"journal":{"name":"NMR in Biomedicine","volume":"39 4","pages":"e70264"},"PeriodicalIF":2.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147458898","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":"Highly Accelerated 3D MRI of Brain Tumors Using Deep Modular Reconstruction Networks.","authors":"Anthony Mekhanik, Joseph N Stember, Onur Yildirim, Muhammad A Naveed, Zhigang Zhang, Robert J Young, Ricardo Otazo","doi":"10.1002/nbm.70260","DOIUrl":"10.1002/nbm.70260","url":null,"abstract":"<p><p>Post-contrast 3D T1-weighted MRI is a time consuming component of cancer neuroimaing protocols. The goal of this study is to accelerate the acquisition of 3D MRI using deep learning reconstruction of undersampled k-space data beyond clinically-available acceleration techniques. A two-stage deep learning framework called Accelerated Deep Modular Image REconstruction (ADMIRE) was developed to first remove aliasing artifacts in the accelerated coronal orientation (unaliasing network) and subsequently enhance magnitude images in axial orientation (enhancement network). The two networks were trained independently using data from two 3D T1-weighted sequences on GE Healthcare scanners: BRAVO and MPRAGE (N_total = 136; N_BRAVO = 47; N_MPRAGE = 89). 3D MPRAGE k-space data with eightfold acceleration (4 × 2 k_y-k_z undersampling) were acquired on 15 patients with enhancing brain lesions and reconstructed with ADMIRE to test feasibility. Validation was performed quantitatively against data-driven and unrolled deep learning methods and against the clinical acquisition that uses a lower acceleration factor using a qualitative reader study performed by three radiologists. Composite and individual one-sided Wilcoxon signed-rank tests were utilized to assess noninferiority of the proposed deep learning approach. Quantitative and qualitative evaluation, scoring and statistical testing revealed that ADMIRE displays better image quality than both data-driven and unrolled methods and was noninferior compared to the clinical standard, despite 32%-46% reductions in acquisition time, in terms of overall quality (summing all metric scores and using a composite noninferiority margin of 8, p-value < 0.001) and diagnostic confidence specifically (using an individual noninferiority margin of 2, p-value = 0.004). ADMIRE further increases the current clinical acceleration of T1-weighted 3D MRI by enabling higher k-space undersampling factors. The use of a clinical sequence and the fast computation speed facilitate clinical translation of ADMIRE.</p>","PeriodicalId":19309,"journal":{"name":"NMR in Biomedicine","volume":"39 4","pages":"e70260"},"PeriodicalIF":2.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147369884","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}