Magnetic resonance imaging最新文献

{"title":"Large gains in SNR through the application of Shinnar-Le Roux RF pulse design to short-TR spin-echo fMRI acquisitions at 7 T","authors":"Mukund Balasubramanian ,&nbsp;Robert V. Mulkern ,&nbsp;William A. Grissom ,&nbsp;Jonathan R. Polimeni","doi":"10.1016/j.mri.2026.110639","DOIUrl":"10.1016/j.mri.2026.110639","url":null,"abstract":"<div><h3>Purpose</h3><div>The optimal excitation flip angle (FA) for short-TR spin-echo acquisitions can be well above 90°, far beyond the small FAs suited for commonly-used sinc RF pulses. The goal of this study was to characterize the benefits of Shinnar-Le Roux (SLR) over sinc pulses for these acquisitions, which may lead to improvements in the temporal and spatial specificity of fMRI.</div></div><div><h3>Methods</h3><div>Slice profiles were obtained either through Bloch simulation or from scans of an oil phantom at 7 T (T₁/TR = 1500/300 ms). Spatial integrals of the slice profiles were used as measures of the resulting (relative) SNR. We also measured the spatial profile of spin-echo “linescan” acquisitions, which are of increasing interest for in vivo studies of cortical layers.</div></div><div><h3>Results</h3><div>For 2D acquisitions with the parameter values used here, the high-quality slice profiles provided by the SLR pulses resulted in an SNR gain of ∼100% relative to sinc pulses. For 1D linescan acquisitions, the SNR gains were even higher: ∼150%.</div></div><div><h3>Conclusions</h3><div>The large gains in SNR described here should enhance any studies using short-TR spin-echo acquisitions; in particular, we anticipate application of these SLR pulses to fMRI studies that target the microvasculature with both high spatial and high temporal resolution. Potential limitations, due to high SAR or B₁⁺ inhomogeneity, should however be kept in mind, especially at ultra-high field strengths.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"129 ","pages":"Article 110639"},"PeriodicalIF":2.0,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146143003","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":"Multi-modality conditioned variational U-net for field-of-view extension in brain diffusion MRI","authors":"Zhiyuan Li ,&nbsp;Chenyu Gao ,&nbsp;Praitayini Kanakaraj ,&nbsp;Shunxing Bao ,&nbsp;Lianrui Zuo ,&nbsp;Michael E. Kim ,&nbsp;Nancy R. Newlin ,&nbsp;Gaurav Rudravaram ,&nbsp;Nazirah M. Khairi ,&nbsp;Yuankai Huo ,&nbsp;Kurt G. Schilling ,&nbsp;Walter A. Kukull ,&nbsp;Arthur W. Toga ,&nbsp;Derek B. Archer ,&nbsp;Timothy J. Hohman ,&nbsp;Bennett A. Landman ,&nbsp;for the Alzheimer's Disease Neuroimaging Initiative","doi":"10.1016/j.mri.2026.110617","DOIUrl":"10.1016/j.mri.2026.110617","url":null,"abstract":"<div><div>An incomplete field-of-view (FOV) in diffusion magnetic resonance imaging (dMRI) can severely hinder the volumetric and bundle analyses of whole-brain white matter connectivity. Although existing works have investigated imputing the missing regions using deep generative models, it remains unclear how to specifically utilize additional information from paired multi-modality data and whether this can enhance the imputation quality and be useful for downstream tractography. To fill this gap, we propose a novel framework for imputing dMRI scans in the incomplete part of the FOV by integrating the learned diffusion features in the acquired part of the FOV to the complete brain anatomical structure. We hypothesize that by this design the proposed framework can enhance the imputation performance of the dMRI scans and therefore be useful for repairing whole-brain tractography in corrupted dMRI scans with incomplete FOV. We tested our framework on two cohorts from different sites with a total of 96 subjects and compared it with a baseline imputation method that treats the information from T1w and dMRI scans equally. The proposed framework achieved significant improvements in imputation performance, as demonstrated by angular correlation coefficient (<em>p</em> &lt; 1E-5), and in downstream tractography accuracy, as demonstrated by Dice score (<em>p</em> &lt; 0.01). Results suggest that the proposed framework improved imputation performance in dMRI scans by specifically utilizing additional information from paired multi-modality data, compared with the baseline method. The imputation achieved by the proposed framework enhances whole brain tractography, and therefore reduces the uncertainty when analyzing bundles associated with neurodegenerative.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"129 ","pages":"Article 110617"},"PeriodicalIF":2.0,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145952368","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":"Toward safe deployment of deep learning in MRI: A physics-driven uncertainty framework for automated quality control and risk Tiering in virtual fat suppression.","authors":"Rong Liu, ZengHan Zhou, YingYing Song, ZongYan Jiang, YuanFeng Liu","doi":"10.1016/j.mri.2026.110700","DOIUrl":"https://doi.org/10.1016/j.mri.2026.110700","url":null,"abstract":"<p><strong>Purpose: </strong>Deep generative models in MRI are hindered by \"hallucinations\" and a lack of safety mechanisms. This study introduces a physics-driven framework for trustworthy Virtual Fat Suppression (VFS), enabling automated quality control and active risk tiering.</p><p><strong>Methods: </strong>A differentiable Bloch layer was embedded into an RRDB-RaGAN architecture to enforce physics-based signal consistency during synthesis. An uncertainty-guided training strategy with artifact-enriched supervision was further introduced to support a three-tier risk model for auto-pass, human review, and rejection. The framework was evaluated using quantitative fidelity metrics, real-world severe artifact detection, and blinded clinical reader assessment.</p><p><strong>Results: </strong>In real-world severe artifact detection, the image-level uncertainty score achieved an AUC of 0.9053 and a recall of 81.82% at a false-positive rate of 4.69%. In blinded clinical evaluation, agreement between AI-predicted and reader-mapped risk tiers was substantial (quadratic weighted Cohen's κ = 0.7938), and images assigned to the Low-Risk tier achieved a mean Likert score of 4.70 ± 0.61.</p><p><strong>Conclusion: </strong>By coupling physics-constrained synthesis with uncertainty-based risk governance, the proposed framework provides a practical and auditable safety layer for virtual fat suppression in clinical MRI workflows.</p>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":" ","pages":"110700"},"PeriodicalIF":2.0,"publicationDate":"2026-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147856578","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":"Efficient B1+ modeling for fast quantification of PDFF and two-compartment T1, T2* relaxation times in abdominal MRI of steatotic patients at 1.5 T","authors":"Kouame Ferdinand Kouakou ,&nbsp;Anita Paisant ,&nbsp;Laurent Arnould ,&nbsp;Christophe Aube ,&nbsp;Hervé Saint-Jalmes","doi":"10.1016/j.mri.2026.110622","DOIUrl":"10.1016/j.mri.2026.110622","url":null,"abstract":"<div><h3>Purpose</h3><div>To propose and preliminarily evaluate a rapid method with potential clinical applicability for correcting the B1+ spatial variation in quantitative abdominal MRI.</div></div><div><h3>Materials and methods</h3><div>The 3D VFA method allows rapid quantification of the T1 relaxation time and is particularly suitable for abdominal imaging, but requires mapping of the B1+ field throughout the 3D volume, which is often not available on clinical MRI scanners. The proposed method, called B1MM, combines a rapid 2D mapping of the B1+ field with modelling of the excitation coil properties to generate a B1+ mapping over a large 3D volume. The method was first validated on phantoms and a healthy volunteer against reference T1-mapping techniques. The method was then applied to simultaneously estimate PDFF, T1, and T2* in the liver, abdominal muscles, and fat of six patients with steatosis using a VFA-based two-compartment model. The six patients were scanned on a 1.5 T clinical MRI (Magnetom Sola, Siemens Healthineers, Erlangen) with a total protocol duration of 25 s. A comparison of the results with and without angle correction and with the literature was performed.</div></div><div><h3>Results</h3><div>In both phantoms and the volunteer, angle correction brought T1 values close to the reference. In the six patients, as expected, angle correction had no effect on PDFF or T2*, but it markedly reduced T1 variability and improved T1 measurement accuracy. In addition, the total acquisition time is considerably reduced, which improves patient comfort.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"128 ","pages":"Article 110622"},"PeriodicalIF":2.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146030174","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":"Comparing orientation-dependent transverse relaxation at 3 T and 7 T: Deciphering anisotropic relaxation mechanisms in white matter","authors":"Yuxi Pang,&nbsp;Rajikha Raja,&nbsp;Wilburn E. Reddick","doi":"10.1016/j.mri.2026.110616","DOIUrl":"10.1016/j.mri.2026.110616","url":null,"abstract":"<div><div>Orientation-dependent transverse relaxation in human brain white matter (WM) has been widely reported, yet its biophysical origins remain debated. This study investigates the relative contributions of the magic angle effect (MAE) and susceptibility-based mechanisms at 3 T and 7 T. Publicly available diffusion tensor imaging (DTI) datasets from 25 young adults in the Human Connectome Project, acquired with <em>b</em>-values of [0,1000] and [0,2000] s/mm², were analyzed. Using a cone-based framework that incorporates a generalized MAE model, the magnitudes of orientation-dependent transverse relaxation rates (<span><math><msubsup><mi>R</mi><mn>2</mn><mi>a</mi></msubsup></math></span>) were derived from <em>T₂</em>-weighted images (<em>b</em> = 0) and compared across the two field strengths. Additionally, <span><math><msubsup><mi>R</mi><mn>2</mn><mi>a</mi></msubsup></math></span> values obtained from gradient-echo (GRE) signals reported in previous literature were evaluated at both 3 T and 7 T. Classical relaxation theory predicts a ratio η = <em>R₂^a(7 T)</em> / <em>R₂^a(3 T)</em> ≃ 1 if MAE dominates, or approximately η = 5.4 if susceptibility effects prevail. Model parameters were consistent across DTI datasets with different non-zero <em>b</em>-values. For <em>b</em> = 1000 s/mm², <span><math><msubsup><mi>R</mi><mn>2</mn><mi>a</mi></msubsup></math></span> increased from 4.0 ± 1.1 s⁻¹ at 3 T to 5.6 ± 1.6 s⁻¹ at 7 T, yielding a ratio η &lt; 1.5. This increase suggests a partial contribution of susceptibility effects to the measured <span><math><msubsup><mi>R</mi><mn>2</mn><mi>a</mi></msubsup></math></span>, estimated at 8.3 ± 10.2% at 3 T and 34.5 ± 42.2% at 7 T. In contrast, GRE-based η values were close to unity. These findings suggest that MAE is the predominant mechanism underlying orientation-dependent transverse relaxation in WM at 3 T, offering a revised interpretation that contrasts with prior susceptibility-based explanations.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"128 ","pages":"Article 110616"},"PeriodicalIF":2.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145989948","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":"Pediatric coronary MR angiography with a two-minute scan using de-aliasing regularization based compressed sensing","authors":"Zhihao Xue ,&nbsp;Guanke Cai ,&nbsp;Xuanhong Liu ,&nbsp;Yan Zheng ,&nbsp;Junpu Hu ,&nbsp;Xihong Hu ,&nbsp;Chenxi Hu","doi":"10.1016/j.mri.2026.110627","DOIUrl":"10.1016/j.mri.2026.110627","url":null,"abstract":"<div><h3>Background</h3><div>Long acquisition time limits the clinical utility of coronary magnetic resonance angiography (CMRA) in pediatric populations. While deep learning-based reconstruction methods such as De-Aliasing Regularization-based Compressed Sensing (DARCS) hold promise for accelerating CMRA, its clinical feasibility in pediatric populations remains unexplored.</div></div><div><h3>Purpose</h3><div>This study aims to reduce scan time and evaluate the image quality and diagnostic performance of DARCS-accelerated CMRA in pediatric coronary imaging, with a focus on coronary artery aneurysms (CAAs) detection.</div></div><div><h3>Study design</h3><div>A two-phase study including retrospective technique development and prospective clinical validation was performed.</div></div><div><h3>Methods</h3><div>CMRA was performed using a 3.0 T scanner with a three-dimensional diaphragm-navigated, T2 prepared gradient echo sequence. In the Phase I, pediatric CMRA k-space data were retrospectively undersampled to train and test DARCS reconstruction, with comparison to SENSE, patch-based reconstruction (PROST), and hybrid deep-learning iterative reconstruction (hybrid DL-IR). In Phase II, patients prospectively underwent both conventional 3× accelerated CMRA and 8× DARCS-CMRA. Images were assessed using quantitative image metrics (peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM)), coronary artery assessments (vessel lengths, sharpness, and visual scores). Diagnostic performance for CAA detection was evaluated at both patient and vessel levels.</div></div><div><h3>Results</h3><div>A total of 123 pediatric patients were included for final analysis, including 96 for the retrospective phase and 27 for the prospective phase. DARCS outperformed the second highest-performance reconstruction method in PSNR (31.74 ± 2.17 vs. 30.69 ± 2.12, <em>P</em> &lt; 0.001 at 8× acceleration), improved vessel length (LAD: 75.86 ± 20.17 mm vs. 72.23 ± 20.80 mm, P &lt; 0.001; RCA: 84.94 ± 20.36 mm vs. 80.12 ± 20.54 mm, P &lt; 0.001), and improved subjective scoring (LAD: 3.22 ± 0.83 vs. 3.11 ± 0.89, <em>P</em> = 0.102 &gt; 0.05; RCA: 3.53 ± 0.81 vs. 3.42 ± 0.81, <em>P</em> = 0.046 &lt; 0.05). In the prospective phase, DARCS-CMRA achieved a 100% sensitivity and specificity in detection of CAA at both patient and vessel levels, with conventional CMRA as the reference, despite a significantly shorter scan time (92.4 ± 19.1 s vs. 208.8 ± 52.0 s).</div></div><div><h3>Conclusion</h3><div>DARCS offers improved reconstruction quality for accelerated CMRA compared to conventional methods, enabling preservation of CAA diagnostic accuracy despite a two-minute scan.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"128 ","pages":"Article 110627"},"PeriodicalIF":2.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146119368","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 detection and correction for MR imaging using a structured light optical motion tracking system (SLOMO)","authors":"Chunyao Wang ,&nbsp;Tianqi Huang ,&nbsp;Yuze Li ,&nbsp;Yajie Wang ,&nbsp;Sisi Li ,&nbsp;Yi Xiao ,&nbsp;Chen Zhang ,&nbsp;Yishi Wang ,&nbsp;Hua Guo ,&nbsp;Huijun Chen","doi":"10.1016/j.mri.2026.110619","DOIUrl":"10.1016/j.mri.2026.110619","url":null,"abstract":"<div><h3>Purpose</h3><div>To develop a markerless structured light system (SLOMO) for both rigid (brain) and non-rigid (liver) motion correction in MR imaging.</div></div><div><h3>Methods</h3><div>The Structured Light Optical MOtion Tracking System (SLOMO) consisted of an MR- compatible camera and a parallel-line projector. The accuracy and precision of the SLOMO were evaluated by phantom experiments. The SLOMO was validated on five volunteers via brain imaging, in which the rigid motion of the head was extracted by registering the SLOMO-measured 3D face point clouds and used to correct the acquired k-space data. Additionally, the capability of SLOMO in non-rigid motion detection was evaluated in liver imaging of three volunteers. During each scan, the respiratory curve was extracted from 3D neck surface changes and then used to divide the acquired data into four respiratory bins; data of each bin was finally reconstructed into images, respectively. For comparison, bellow-based binning and sequential- binning served as references.</div></div><div><h3>Results</h3><div>The tracking accuracy (evaluated via phantom image registration) and precision (evaluated via static phantom tracking) of the SLOMO were 0.38 mm/0.25°and 0.0048 mm/0.0019°, respectively. In brain imaging, SLOMO-corrected images had significantly higher image quality scores than uncorrected images (<em>P</em> &lt; 0.001). In liver imaging, the correlation coefficient (r) between the respiratory curves extracted from the SLOMO and the bellow was 0.92 ± 0.04; images reconstructed from the bellow- bins and the SLOMO-bins showed comparable image quality (<em>P</em> = 0.38), while both were significantly higher than those from sequential-bins.</div></div><div><h3>Conclusion</h3><div>The proposed SLOMO demonstrated its capability in rigid and non-rigid motion detection and correction for MR brain and liver imaging.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"128 ","pages":"Article 110619"},"PeriodicalIF":2.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145966438","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":"Associations of MRI indirect derived glymphatic system impairment with acute carbon monoxide poisoning and delayed neurological sequelae","authors":"Siying Chen ,&nbsp;Shijun Yang ,&nbsp;Jinlan Li ,&nbsp;Xiaoling Deng ,&nbsp;Min Jia ,&nbsp;Congping Wang ,&nbsp;Minghui Tan ,&nbsp;Feng Duan ,&nbsp;Qunhui Liu","doi":"10.1016/j.mri.2026.110615","DOIUrl":"10.1016/j.mri.2026.110615","url":null,"abstract":"<div><h3>Objective</h3><div>To assess the glymphatic function utilizing diffusion tensor imaging along the perivascular space (DTI-ALPS) indices in acute carbon monoxide poisoning (ACOP) and subsequent delayed neurological sequelae (DNS).</div></div><div><h3>Methods</h3><div>A total of 76 participants were included and categorized into ACOP (<em>n</em> = 51) and healthy controls (HCs, <em>n</em> = 25), and the ACOP groups were further divided into DNS (<em>n</em> = 26) and non-DNS (n = 25) subgroups. Demographic and clinical variables were included. Group differences were analyzed, and correlations between the DTI-ALPS index and clinical parameters were assessed. Multivariate logistic regression was performed to evaluate the predictive value of sex, age, blood lactate, CO exposure time, COHb, and DTI-ALPS index in classifying DNS patients.</div></div><div><h3>Results</h3><div>Significant differences in left DTI-ALPS, right DTI-ALPS and mean DTI-ALPS index were observed between the ACOP and HC groups (d = −0.18 [−0.32, −0.10], FWE-corrected <em>p</em> &lt; 0.001), and between the non-DNS and DNS groups (d = −0.17 [−0.21, −0.05], FWE-corrected <em>p</em> &lt; 0.01). The logistic regression model showed that CO exposure time, lactic acid, left DTI-ALPS, right DTI-ALPS, and mean DTI-ALPS were associated with a higher occurrence of DNS (<em>p</em> = 0.018, <em>p</em> = 0.019, <em>p</em> = 0.032, <em>p</em> = 0.038, <em>p</em> = 0.026, respectively), with an area under the curve of 0.98, sensitivity of 0.96, specificity of 0.92, positive predictive value of 0.92, and negative predictive value of 0.92. Additionally, CO exposure time, COHb levels, and blood lactate levels were significantly negatively correlated with DTI-ALPS indices</div></div><div><h3>Conclusions</h3><div>The DTI-ALPS index serves as a potential imaging biomarker for brain damage associated with ACOP and DNS, indicating the involvement of glymphatic dysfunction in the pathophysiology of these conditions.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"128 ","pages":"Article 110615"},"PeriodicalIF":2.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980348","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":"Evaluation of the diagnostic value of DCE-MRI radiomics features and K-trans parameters in differentiating endometrial cancer from submucosal uterine fibroids","authors":"LiJian Su ,&nbsp;KeWu Wang ,&nbsp;ShengXiang Xiao ,&nbsp;LiuYan Xu ,&nbsp;JiBo Hu","doi":"10.1016/j.mri.2026.110625","DOIUrl":"10.1016/j.mri.2026.110625","url":null,"abstract":"<div><h3>Objective</h3><div>To explore the diagnostic value of Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) radiomics features and qualitative parameters for the differential diagnosis of endometrial cancer (EC) and submucosal uterine fibroidsuterine fibroids.</div></div><div><h3>Methods</h3><div>This retrospective study included 70 cases of endometrial cancer patients collected from our hospital between October 2022 and October 2024, assigned to the EC group, and another 35 cases of uterine leiomyoma patients during the same period were collected as the benign group according to the 2:1 matching principle. Baseline data, DCE-MRI parameters [rate constant (Kep), volume transport constant (Ktrans), and volume fraction of extracellular space (Ve)] and radiomics characteristics were compared between the two groups. The influencing factors of DCE-MRI parameters and radiomics features on EC were analyzed, as well as their diagnostic value in differentiation, and external validation of the diagnostic value in differentiation was conducted.</div></div><div><h3>Results</h3><div>Ktrans and Kep in EC group were higher than those in benign group, while Ve was lower (<em>P</em> &lt; 0.05). The radiomic score of the EC group was higher than that of the benign group (<em>P</em> &lt; 0.05). Logistic regression analysis found that Ktrans, Kep, Ve, and radiomic score were factors affecting EC (<em>P</em> &lt; 0.05). The AUC values for the DCE-MRI model, radiomics model, and combined model in predicting the differential diagnosis of EC were 0.695, 0.775, and 0.867, respectively. Among them, the combined model demonstrated the highest predictive value, significantly surpassing that of the DCE-MRI and radiomics models (<em>P</em> &lt; 0.05). The decision curve indicated that the clinical positive benefit achieved by the combined model in differential diagnosis of EC surpassed that of the DCE-MRI and radiomics models (<em>P</em> &lt; 0.05). The calibration curve showed that the calibration curve for differential diagnosis of EC fitted well with the ideal curve. The external validation results demonstrated that the combined diagnostic model exhibited good predictive value.</div></div><div><h3>Conclusion</h3><div>The combination of DCE-MRI parameters and radiomics features can be used for the differential diagnosis of EC, demonstrating good predictive efficacy and clinical applicability, providing a reliable imaging diagnostic method for clinical diagnosis of EC.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"128 ","pages":"Article 110625"},"PeriodicalIF":2.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146046898","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":"Paramagnetic susceptibility versus QSM for estimating OEF: A comparative study in cerebral small vessel disease","authors":"Wenyu Zhou ,&nbsp;Dan Luo ,&nbsp;Hao Chen ,&nbsp;Meiling Wang ,&nbsp;Yongmei Li","doi":"10.1016/j.mri.2026.110623","DOIUrl":"10.1016/j.mri.2026.110623","url":null,"abstract":"<div><h3>Background</h3><div>The oxygen extraction fraction (OEF) is a key parameter of cerebral metabolism and a potential biomarker for cerebral small vessel disease (SVD). Quantitative susceptibility mapping (QSM) allows non-invasive OEF mapping but is confounded by the opposing magnetic susceptibilities of deoxyhemoglobin and oxyhemoglobin. We evaluated a novel method that separates the paramagnetic susceptibility component for OEF estimation and compared it with conventional QSM in SVD patients and healthy controls (HC).</div></div><div><h3>Methods</h3><div>27 SVD patients and 23 HC underwent multi-echo GRE MRI for QSM reconstruction. The paramagnetic susceptibility was separated using APART-QSM. The straight sinus (SS) and superior sagittal sinus (SSS) were segmented for regional OEF calculation using both conventional QSM and paramagnetic susceptibility. Statistical comparisons were performed using Welch's <em>t</em>-test.</div></div><div><h3>Results</h3><div>Paramagnetic susceptibility was significantly higher than total QSM (<em>p</em> &lt; 0.05), while OEF derived from paramagnetic susceptibility was significantly lower (<em>p</em> &lt; 0.05). OEF values derived from paramagnetic susceptibility (HC: 22.5 ± 4.8% in SS, 19.3 ± 4.6% in SSS; SVD: 23.4 ± 5.1% in SS, 19.0 ± 4.5% in SSS) were significantly lower (p &lt; 0.05) than those obtained via conventional QSM (HC: 29.0 ± 3.5% in SS, 26.8 ± 3.3% in SSS; SVD: 29.8 ± 3.8% in SS, 26.5 ± 3.2% in SSS). No significant OEF differences were found between HC and SVD cohorts in the analyzed venous regions.</div></div><div><h3>Conclusion</h3><div>This study demonstrates the feasibility of separating the paramagnetic susceptibility component via APART-QSM for quantitative OEF estimation. While the derived OEF values were lower than those from conventional QSM, the method theoretically offers improved specificity by disentangling deoxygenation-driven susceptibility from diamagnetic confounds, highlighting its potential as a refined biomarker for cerebral oxygen metabolism subject to further optimization.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"128 ","pages":"Article 110623"},"PeriodicalIF":2.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146041010","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}