Magnetic resonance imaging最新文献_第4页

Coronary artery black-blood imaging via T2-prepared phase-sensitive inversion-recovery steady-state free precession in Kawasaki disease 冠状动脉黑血成像的t2制备相敏反转恢复稳态自由进动川崎病。

IF 2 4区医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Magnetic resonance imaging

Pub Date : 2025-12-06 DOI: 10.1016/j.mri.2025.110589

Koji Matsumoto , Hajime Yokota , Hiroki Mukai , Ryota Ebata , Kentaro Okunushi , Hiromichi Hamada , Hiroyuki Takaoka , Masami Yoneyama , Takashi Namiki , Takashi Iimori , Takashi Uno

Purpose

This study aimed to evaluate, qualitatively and quantitatively, cross-sectional black-blood images obtained using T₂-prepared phase-sensitive inversion-recovery steady-state free precession (T₂PSIR-SSFP), in comparison with conventional double inversion recovery turbo spin-echo (DIR-TSE), in patients with Kawasaki disease (KD), and to assess the feasibility of T₂PSIR-SSFP imaging.

Materials and methods

Nine patients (three female and six male; median age, 6.2 years; range, 8 months–14 years) were enrolled. Black-blood imaging was separately analyzed in aneurysmal and regressed aneurysmal regions. Lumen and outer wall boundary image quality was visually graded using a four-point scale. Lumen area (LA) reproducibility measurements were determined using intraclass correlation coefficients (ICCs) between T₂PSIR-SSFP and coronary magnetic resonance angiography (MRA) images, as well as between DIR-TSE and MRA. Agreement between T₂PSIR-SSFP and MRA was further examined using Bland–Altman analysis.

Results

A total of 22 coronary regions (11 aneurysmal and 11 regressed aneurysmal) were assessed. T₂PSIR-SSFP exhibited excellent reproducibility with MRA in both aneurysmal and regressed aneurysmal regions (ICCs = 0.99 and 1.00, respectively). DIR-TSE showed high reproducibility in regressed aneurysmal regions (ICC = 0.93) but poor agreement in aneurysmal regions (ICC = 0.43). Bland–Altman analysis revealed strong agreement between T₂PSIR-SSFP and MRA, with no fixed or proportional bias in either region (P > 0.1).

Conclusions

Flow-independent coronary black-blood imaging using T₂PSIR-SSFP provided values within the expected range in patients with KD. T₂PSIR-SSFP imaging appears suitable for KD follow-up because it can provide accurate cross-sectional images and reproducibility of LA measurements.

目的：本研究旨在定性和定量地评价利用t2制备的相敏反转恢复稳态自由进动（T2PSIR-SSFP）与常规双反转恢复涡轮自旋回波（DIR-TSE）在川崎病（KD）患者中获得的黑血横截面图像，并评估T2PSIR-SSFP成像的可行性。材料和方法：纳入9例患者，其中女性3例，男性6例，中位年龄6.2 岁，范围8 个月-14 岁。分别分析动脉瘤区和退化动脉瘤区的黑血显像。使用四分制对流明和外墙边界图像质量进行视觉分级。利用T2PSIR-SSFP与冠状动脉磁共振血管造影（MRA）图像之间以及ir - tse与MRA之间的类内相关系数（ICCs）来确定管腔面积（LA）的可重复性测量。采用Bland-Altman分析进一步检验T2PSIR-SSFP与MRA之间的一致性。结果：共检查了22个冠状动脉区域（11个动脉瘤区和11个退化动脉瘤区）。T2PSIR-SSFP在动脉瘤区和退化动脉瘤区均表现出良好的MRA再现性（ICCs分别为 = 0.99和1.00）。DIR-TSE在回归动脉瘤区域显示高重复性（ICC = 0.93），但在动脉瘤区域一致性较差（ICC = 0.43）。Bland-Altman分析显示T2PSIR-SSFP和MRA之间有很强的一致性，在任何地区都没有固定或比例偏差（P > 0.1）。结论：T2PSIR-SSFP不依赖血流的冠状动脉黑血造影对KD患者的价值在预期范围内。T2PSIR-SSFP成像似乎适合KD随访，因为它可以提供准确的横截面图像和LA测量的再现性。

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引用次数: 0

Adaptive regularization weight selection for compressed sensing MRI reconstruction 压缩感知MRI重构的自适应正则化权重选择。

IF 2 4区医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Magnetic resonance imaging

Pub Date : 2025-12-01 DOI: 10.1016/j.mri.2025.110579

Yuan Lian, Yuancheng Jiang, Hua Guo

Purpose

Proper regularization weights are crucial for the reconstruction quality of compressed sensing (CS) MRI. This work aims to develop an automatic and adaptive regularization weights selection method for CS reconstruction

Methods

A statistical model based on Bayesian theory is designed, incorporating prior information about the Gaussian distribution of incoherent noise and the Laplacian distribution of wavelet coefficients in the wavelet transform domain. Using the variance of coefficients and noise, the adaptive regularization weight for achieving optimal reconstruction quality in each iteration step is obtained through a maximum a posteriori estimator. The adaptive regularization weights vary across different subjects, slices, iterations, and wavelet sub-bands

Results

The efficacy of the proposed method was demonstrated through retrospective and prospective studies. Compared to reconstruction results using optimal fixed regularization weights and sparsity-adaptive composite recovery method (SCoRe), the proposed method successfully reduces reconstruction errors and effectively recovers original signals from noise-like incoherent artifacts in the wavelet transform domain. It also saves weight selection time when searching for optimal fixed regularization weights

Conclusion

We propose an adaptive regularization weights selection method for CS-MRI reconstruction. It provides optimal regularization weights for different subjects, slices, and iterations without requiring manual intervention

目的：适当的正则化权值对压缩感知（CS） MRI的重建质量至关重要。方法：基于贝叶斯理论，结合非相干噪声高斯分布的先验信息和小波变换域小波系数的拉普拉斯分布，设计了一个统计模型。利用系数和噪声的方差，通过极大后验估计得到每个迭代步骤中实现最优重构质量的自适应正则化权值。结果：通过回顾性和前瞻性研究验证了该方法的有效性。与最优固定正则化权值和稀疏自适应复合恢复方法（SCoRe）的重构结果相比，该方法成功地减小了重构误差，并在小波变换域内有效地从类噪声非相干伪影中恢复原始信号。结论：提出了一种适用于CS-MRI重构的自适应正则化权值选择方法。它为不同的主题、切片和迭代提供了最优的正则化权重，而不需要人工干预。

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引用次数: 0

Tumor stiffness as an imaging biomarker of tyrosine kinase inhibitor response: A preclinical study 肿瘤硬度作为酪氨酸激酶抑制剂反应的成像生物标志物：临床前研究。

IF 2 4区医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Magnetic resonance imaging

Pub Date : 2025-11-27 DOI: 10.1016/j.mri.2025.110577

Baihe Luo , Aoran Yang , Jialin Li , Chen Pan, Chunli Li, Minghui Zhou, Zhiying Wang, Chengli Gu, Xiaoli Yin, Yun Zhao, Yu Shi

Objective

Tyrosine kinase inhibitors (TKIs), such as sorafenib, are standard therapies for advanced hepatocellular carcinoma (HCC), but their biomechanical impact and the role of magnetic resonance elastography (MRE) in treatment evaluation remain unclear. This study explored whether TKIs reduce tumor stiffness by inhibiting malignant behavior and whether MRE can detect such changes early.

Methods

A prospective animal study was performed using subcutaneous SK-HEP-1 HCC xenografts in 50 nude rats. Forty tumor-bearing rats were randomized to control or sorafenib-treated groups (n = 20 each). Multiparametric 3.0 T MRI included T1- and T2-weighted imaging, T1/T2/T2* mapping, and MRE at 200 Hz and 100 Hz. Imaging was conducted at baseline (∼2 cm³ tumor volume) and on days 1, 2, and 3 post-intervention. Histology involved H&E and immunohistochemistry for VEGFR-1, BRAF, Ki67, and TUNEL. Ex vivo stiffness was measured by atomic force microscopy. Cell behavior was assessed by EdU, Transwell, CCK-8, and Western blot. Statistical analysis included ICC, Bland–Altman, Mann–Whitney U, repeated measures ANOVA, Spearman correlation, and multivariate regression.

Results

TKIs reduced tumor stiffness at cellular (P = 0.02) and tissue (P = 0.004) levels. Stiffness decreased by day 2 at 200 Hz and day 3 at both frequencies. Treated tumors showed reduced cellularity, lower Ki67, and increased apoptosis. Stiffness correlated with cellularity (r = 0.527) and Ki67 (r = 0.623), both predicting MRE stiffness (R² = 0.537).

Conclusion

TKIs reduce stiffness and malignancy in HCC. MRE is a promising tool for early treatment response evaluation.

目的：酪氨酸激酶抑制剂（TKIs），如索拉非尼，是晚期肝细胞癌（HCC）的标准治疗方法，但其生物力学影响和磁共振弹性成像（MRE）在治疗评估中的作用尚不清楚。本研究探讨TKIs是否通过抑制恶性行为来降低肿瘤硬度，以及MRE能否早期发现这种变化。方法：采用裸鼠皮下移植SK-HEP-1肝细胞癌进行前瞻性动物研究。40只荷瘤大鼠随机分为对照组和索拉非尼治疗组（各 = 20只）。多参数3.0 T MRI包括T1和T2加权成像，T1/T2/T2*成像，200 Hz和100 Hz的MRE。在基线（~2 cm3肿瘤体积）和干预后第1、2、3天进行影像学检查。组织学检查包括H&E和免疫组织化学对VEGFR-1、BRAF、Ki67和TUNEL的检测。用原子力显微镜测量离体刚度。采用EdU、Transwell、CCK-8和Western blot检测细胞行为。统计分析包括ICC、Bland-Altman、Mann-Whitney U、重复测量方差分析、Spearman相关和多元回归。结果：TKIs在细胞（P = 0.02）和组织（P = 0.004）水平上降低肿瘤硬度。刚度在200 Hz和两种频率下的第2天和第3天下降。治疗后的肿瘤细胞数量减少，Ki67降低，细胞凋亡增加。刚度与细胞度（r = 0.527）和Ki67 （r = 0.623）相关，均可预测MRE刚度（R2 = 0.537）。结论：TKIs可降低肝细胞癌的僵硬程度和恶性程度。MRE是一种很有前途的早期治疗反应评估工具。

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引用次数: 0

Repeatability and reproducibility of maximum diameter measurements of prostate lesions on MRI with repositioning and variation of imaging sequences: A test-retest study 重新定位和改变成像序列的MRI前列腺病变最大直径测量的可重复性和再现性：一项测试-重新测试研究。

IF 2 4区医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Magnetic resonance imaging

Pub Date : 2025-11-27 DOI: 10.1016/j.mri.2025.110578

Kevin Sun Zhang , Philip Alexander Glemser , Christian Jan Oliver Neelsen , Markus Wennmann , Lukas Thomas Rotkopf , Nils Netzer , Clara Meinzer , Thomas Hielscher , Vivienn Weru , Magdalena Görtz , Albrecht Stenzinger , Markus Hohenfellner , Heinz-Peter Schlemmer , David Bonekamp

Objectives

To assess variability of maximum diameter measurements of prostate lesions in MRI assessing patient repositioning, rater and sequence effects.

Methods

Forty-two patients were included retrospectively, who received a clinical bi−/multiparametric prostate MRI examination and agreed to have the T2-weighted (T2WI) and diffusion weighted-imaging (DWI) sequences scanned twice. Maximum diameter measurements of prostate lesions mentioned in the clinical radiologist reports were performed by four readers in multiple reading sessions for determination of inter-sequence (between two DWI sequences), inter-scan (between clinical and additional scan), intra-rater and inter-rater variability. The primary calculated metrics were the repeatability and reproducibility coefficient (RC/RDC), including pooled RC/RDC.

Results

Variability measured by RCs/RDCs was lowest for measurements obtained within the same reading session, with inter-scan RCs up to 5.6 mm/6.5 mm for T2WI/DWI, pooled RCs of 4.8 mm/5.8 mm, respectively, and inter-sequence RDCs of 5.4 mm–5.9 mm, pooled RDC 5.8 mm. Measurements performed in separate reading sessions demonstrated significantly higher variability for both settings in the majority of cases (RCs: up to 10.9 mm/11.7 mm/10.2 mm for T2WI/DWI/inter-sequence, p ≤ 0.002), pooled RCs/RDCs 9.2 mm–9.9 mm. Measurements necessarily generated in different reading sessions, i.e., intra-rater or inter-rater, demonstrated high variability (RCs/RDCs up to 11.4 mm/11.5 mm for T2WI/DWI).

Conclusions

Prostate lesion measurements demonstrate considerable variability. When measured in one reading session by one rater, lesion diameter differences below the pooled RCs of 4.8 mm, 95 %-CI [3.9, 5.6] for T2WI and 5.8 mm, 95 %-CI [4.7, 7.1] for DWI should not necessarily assumed to be true biological change, as these differences may result from measurement- or repositioning-based variability alone. Caution needs to be taken assessing size changes.

目的：评估磁共振成像中前列腺病变最大直径测量的可变性，以评估患者重新定位、排序和序列效应。方法：回顾性分析42例接受临床双参数/多参数前列腺MRI检查的患者，并同意进行2次t2加权（T2WI）和弥散加权成像（DWI）序列扫描。临床放射科医生报告中提到的前列腺病变的最大直径测量由四名读取器在多次读取会话中完成，以确定序列间（两个DWI序列之间）、扫描间（临床和附加扫描之间）、分级内和分级间的变异性。主要计算指标为重复性和再现性系数（RC/RDC），包括合并RC/RDC。结果：在相同的读数过程中，RCs/RDC测量的变变性最低，T2WI/DWI的扫描间RCs高达5.6 mm/6.5 mm，合并RCs分别为4.8 mm/5.8 mm，序列间RDC为5.4 mm-5.9 mm，合并RDC为5.8 mm。在单独的读数过程中进行的测量显示，在大多数情况下，这两种设置的变异性显著更高（T2WI/DWI/序列间的RCs：高达10.9 mm/11.7 mm/10.2 mm, p ≤ 0.002），合并的RCs/RDCs为9.2 mm-9.9 mm。在不同的阅读过程中产生的测量结果，即内部或内部的测量结果，显示出很高的可变性（T2WI/DWI的RCs/ rdc高达11.4 mm/11.5 mm）。结论：前列腺病变测量显示出相当大的可变性。当由一名评估者在一次读数中测量时，T2WI的病变直径差异低于4.8 mm, 95% %- ci [3.9, 5.6]， DWI的病变直径差异低于5.8 mm, 95% %- ci[4.7, 7.1]，这并不一定被认为是真正的生物学变化，因为这些差异可能仅仅是由测量或重新定位的可变性造成的。评估大小变化时需要谨慎。

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引用次数: 0

Enhancing and accelerating brain MRI through deep learning reconstruction using prior subject-specific imaging 利用先验主体特异性成像通过深度学习重建增强和加速脑MRI

IF 2 4区医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Magnetic resonance imaging

Pub Date : 2025-11-20 DOI: 10.1016/j.mri.2025.110558

Amirmohammad Shamaei , Alexander Stebner , Salome (Lou) Bosshart , Johanna Ospel , Gouri Ginde , Mariana Bento , Roberto Souza

Magnetic resonance imaging (MRI) is a crucial medical imaging modality. However, long acquisition times remain a significant challenge, leading to increased costs, and reduced patient comfort. Recent studies have shown the potential of using deep learning models that incorporate information from prior subject-specific MRI scans to improve reconstruction quality of present scans. Integrating this prior information requires registration of the previous scan to the current image reconstruction, which can be time-consuming. We propose a novel deep-learning-based MRI reconstruction framework which consists of an initial reconstruction network, a deep registration model, and a transformer-based enhancement network. We validated our method on a longitudinal dataset of T1-weighted MRI scans with 2808 images from 18 subjects at four acceleration factors (R5, R10, R15, R20). Quantitative metrics confirmed our approach’s superiority over existing methods (p

<

0.05, Wilcoxon signed-rank test). Furthermore, we analyzed the impact of our MRI reconstruction method on the downstream task of brain segmentation and observed improved accuracy and volumetric agreement with reference segmentations. Our approach also achieved a substantial reduction in total reconstruction time compared to methods that use traditional registration algorithms, making it more suitable for real-time clinical applications. The code associated with this work is publicly available at https://github.com/amirshamaei/longitudinal-mri-deep-recon.

磁共振成像（MRI）是一种重要的医学成像方式。然而，较长的获取时间仍然是一个重大挑战，导致成本增加，降低了患者的舒适度。最近的研究表明，利用深度学习模型结合先前特定主题MRI扫描的信息来提高当前扫描的重建质量具有潜力。整合这些先验信息需要将之前的扫描与当前的图像重建进行配准，这可能很耗时。我们提出了一种新的基于深度学习的MRI重建框架，该框架由初始重建网络、深度配准模型和基于变压器的增强网络组成。我们在一个纵向数据集上验证了我们的方法，该数据集包含来自18名受试者的t1加权MRI扫描图像，其中包含四种加速度因子（R5, R10, R15, R20）的2808张图像。定量指标证实了我们的方法优于现有方法（p < 0.05， Wilcoxon sign -rank检验）。此外，我们分析了我们的MRI重建方法对脑分割下游任务的影响，并观察到准确性和体积一致性与参考分割的提高。与使用传统配准算法的方法相比，我们的方法还大大减少了总重建时间，使其更适合实时临床应用。与这项工作相关的代码可在https://github.com/amirshamaei/longitudinal-mri-deep-recon上公开获得。

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引用次数: 0

Arterial spin labelling as a contrast-free alternative to dynamic contrast enhancement for the evaluation of peripheral zone prostatic lesions on MRI 动脉自旋标记作为一种无造影剂替代动态增强造影剂在MRI上评价外周带前列腺病变

IF 2 4区医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Magnetic resonance imaging

Pub Date : 2025-11-19 DOI: 10.1016/j.mri.2025.110575

Valentina Corato , Vincenzo Vingiani , Bernardo Proner , Petros Martirosian , Armin Pycha , Emanuela Trenti , Alessandro Lanaro , Giovanna Nordio , Riccardo Valletta , Matteo Bonatti

Purpose

To assess the correlation between ASL-derived perfusion parameters and enhancement pattern on DCE in patients with histologically uncharacterized lesions of the peripheral prostatic zone.

Materials and methods

Prospective study: informed consent was obtained. We included 52 patients with peripheral zone lesions ≥4 mm, PI-RADS ≥3. All patients underwent PI-RADS-recommended multiparametric MRI and ASL acquisition using a Flow-sensitive Alternating Inversion Recovery (FAIR) with True Fast Imaging with Steady-State Precession (True-FISP) pulse sequence at 3 T. DCE images were assessed for early focal enhancement (DCE+). Two radiologists independently measured prostatic blood flow (PBF) in the lesion and adjacent normal PZ tissue; the mean of the values was used for further analysis. The PBF ratio (lesion/healthy tissue) was calculated. Statistical analysis included Mann-Whitney U, Wilcoxon tests, and ROC curve analysis.

Results

Fifty-two lesions with median diameter of 8 mm (IQR: 6–12 mm) were included. On DCE, 31/52 (60 %) were DCE+, and 21/52 (40 %) were DCE−. Interobserver agreement for PBF measurements was excellent (ICC 0.980–0.994). Median PBF was significantly higher in target lesions than in healthy tissue (28.03 vs. 15.76 ml/100 g/min, p = 0.0003). DCE+ lesions showed significantly higher PBF than DCE– ones (39.17 vs. 19.04 ml/100 g/min; p = 0.0001), as well as a significantly higher PBF ratio (2.6 vs. 1.09; p < 0.0001). On ROC analysis, PBF ratio showed an AUC of 0.97 (95 % CI: 0.87–0.99; p < 0.0001) in discriminating between DCE+ and DCE− lesions; a cut-off value of >1.66 provided 86 % sensitivity and 100 % specificity in identifying DCE+ lesions.

Conclusions

ASL may serve as a safe, contrast-free alternative for evaluating vascularization of peripheral prostatic zone lesions.

目的探讨前列腺周围区组织学特征不明显病变患者asl灌注参数与DCE增强模式的相关性。材料与方法前瞻性研究：获得知情同意。我们纳入52例外周区病变≥4mm， PI-RADS≥3的患者。所有患者都接受了pi - rads推荐的多参数MRI和ASL采集，使用流量敏感交替反转恢复（FAIR）和真正的快速成像与稳态进动（True- fisp）脉冲序列在3 t时进行DCE图像的早期病灶增强（DCE+）评估。两名放射科医生独立测量病变和邻近正常PZ组织的前列腺血流量（PBF）；取平均值作进一步分析。计算PBF比（病变/健康组织）。统计分析采用Mann-Whitney U检验、Wilcoxon检验和ROC曲线分析。结果共纳入52个中位直径为8 mm （IQR: 6 ~ 12 mm）的病变。在DCE中，31/52（60%）为DCE+， 21/52（40%）为DCE−。观察者间对PBF测量的一致性非常好（ICC 0.980-0.994）。靶病变的中位PBF显著高于健康组织（28.03 vs. 15.76 ml/100 g/min, p = 0.0003）。DCE+病变PBF显著高于DCE -病变（39.17 vs. 19.04 ml/100 g/min, p = 0.0001）， PBF比值显著高于DCE -病变（2.6 vs. 1.09, p < 0.0001）。在ROC分析中，PBF比值显示区分DCE+和DCE -病变的AUC为0.97 (95% CI: 0.87-0.99; p < 0.0001)；截断值>；1.66为鉴别DCE+病变提供了86%的敏感性和100%的特异性。结论sasl可作为一种安全、无对比的评价前列腺周围区病变血管化的方法。

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引用次数: 0

GL-mamba-net: A magnetic resonance imaging restoration network with global-local mamba 曼巴网：一个具有全局-局部曼巴的磁共振成像恢复网络

IF 2 4区医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Magnetic resonance imaging

Pub Date : 2025-11-19 DOI: 10.1016/j.mri.2025.110574

Ke Liang , Zhijin Lin , Jie Yang , Teng Yu , Jieru Chi , Feng Liu

In clinical practice, magnetic resonance imaging is essential for disease diagnosis and evaluation, although it generally requires a prolonged scanning duration. Recently, several deep learning-based restoration techniques have been introduced to accelerate MRI acquisition. However, most existing MRI restoration methods struggle to fully capture local texture features and have limitations in fusing global and local features. To address this issue, the paper introduces a dual path Mamba network. This method uses a strategy of multi-scale local feature and global feature fusion for under-sampled single-coil image domain data, significantly improving both the quality and efficiency of image restoration. Specifically, 1) A multi-scale local Mamba block is proposed, which extracts local information from different regions through a multi-scale window mechanism, capturing diverse local features. 2) A new feature fusion block is proposed, which fuses global and local information to enhance the completeness of feature expression. 3) A dual path Mamba network architecture is proposed. This dual-path design significantly improves feature extraction capability and adaptability in complex and dynamic data environments. Through comprehensive experiments on the NAMIC, fastMRI and BraTS datasets, it is shown that the proposed network surpasses current leading methods across various evaluation metrics, particularly excelling in restoring texture details and tissue structures.

在临床实践中，磁共振成像对于疾病的诊断和评估是必不可少的，尽管它通常需要较长的扫描时间。近年来，一些基于深度学习的修复技术被引入来加速MRI采集。然而，大多数现有的MRI恢复方法难以完全捕获局部纹理特征，并且在融合全局和局部特征方面存在局限性。为了解决这个问题，本文介绍了一种双路径曼巴网络。该方法对欠采样单线圈图像域数据采用多尺度局部特征和全局特征融合策略，显著提高了图像恢复的质量和效率。具体而言，1)提出了一种多尺度局部曼巴块，通过多尺度窗口机制从不同区域提取局部信息，捕捉不同的局部特征；2)提出了一种新的特征融合块，融合全局和局部信息，增强特征表达的完整性。3)提出了一种双路径Mamba网络架构。这种双路径设计显著提高了特征提取能力和对复杂动态数据环境的适应性。通过在NAMIC、fastMRI和BraTS数据集上的综合实验，表明所提出的网络在各种评估指标上都超越了目前领先的方法，特别是在纹理细节和组织结构的恢复方面表现出色。

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引用次数: 0

Deep learning-based perfusion quantification and large vessel exclusion for renal multi-TI arterial spin labelling MRI 基于深度学习的肾多ti动脉自旋标记MRI灌注量化和大血管排除。

IF 2 4区医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Magnetic resonance imaging

Pub Date : 2025-11-17 DOI: 10.1016/j.mri.2025.110573

Jiaying Zhang , Xiangwei Kong , Xi Lin , Yanbin Li , Jeff L. Zhang , Xiaopeng Zong

The multi-TI flow-sensitive alternating inversion recovery sequence is a common ASL technique for probing renal perfusion. However, traditional method for quantifying perfusion, bolus arrival time (BAT) and bolus length (BL) from the images faces challenges due to low signal-to-noise ratio, large vessel contamination, and the absence of magnetization direction information in magnitude images. We proposed a BiLSTM-based deep learning (DL) approach for quantifying perfusion, BAT, and BL, and excluding large vessels. The network was trained on simulated pixel-wise multi-TI signals and tested using simulated and in vivo data. For comparison, the traditional quantification based on Buxton's model fitting was carried out, and manual cortex, medulla, and large vessel masks were drawn on fully relaxed magnitude images. For in vivo data, the quantification results from averages over all repetitions served as reference. In simulation, the DL approach had smaller quantification errors for perfusion and BAT but larger errors for BL than the traditional method. All in vivo parameters derived from the traditional method deviated more from references as number of averages decreased than those derived from DL. The DL masks excluded more high-perfusion pixels than the manual masks. Significant differences between the traditional and DL methods' quantification of in vivo perfusion, BAT, and BL cannot be explained by their differences observed in simulation, suggesting differences between simulated and in vivo data characteristics. The proposed network may serve as a useful tool for quantification in ASL, which is more accurate and more robust against noise than the traditional method.

多ti血流敏感交替反转恢复序列是肾灌注探测常用的ASL技术。然而，传统的图像灌注、丸状到达时间（BAT）和丸状长度（BL）量化方法由于信噪比低、血管污染大以及在量级图像中缺乏磁化方向信息而面临挑战。我们提出了一种基于bilstm的深度学习（DL）方法来量化灌注、BAT和BL，并排除大血管。该网络在模拟的逐像素多ti信号上进行训练，并使用模拟和体内数据进行测试。相比之下，采用传统的基于Buxton模型拟合的量化方法，在完全放松量级的图像上绘制人工皮层、髓质和大血管面具。体内数据以所有重复的平均值作为定量结果的参考。在模拟中，与传统方法相比，DL方法对灌注和BAT的量化误差较小，但对BL的量化误差较大。随着平均值数量的减少，传统方法得到的所有体内参数与参考文献的偏差都大于DL方法得到的参数。DL掩模比手动掩模排除了更多的高灌注像素。传统方法和DL方法在体内灌注、BAT和BL的量化上的显著差异不能用模拟中观察到的差异来解释，说明模拟和体内数据特征存在差异。该网络可以作为一种有用的量化工具，与传统的方法相比，它更准确，对噪声的鲁棒性更强。

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引用次数: 0

Prediction of pathological risk factors in rectal cancer using combined extracellular volume fraction from T1 mapping and apparent diffusion coefficient 利用T1作图的细胞外体积分数和表观扩散系数联合预测直肠癌病理危险因素。

IF 2 4区医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Magnetic resonance imaging

Pub Date : 2025-11-17 DOI: 10.1016/j.mri.2025.110576

Mingyue Zhou , Jianwei Zeng , Chong Wang , Haini Zhang , Xiaohan Liu , Chenzi Wang , Juan Long , Yingying Cui , Hao Wang , Yankai Meng , Chunfeng Hu , Kai Xu

Background

Accurate preoperative prediction of pathological risk factors in rectal cancer is critical for guiding treatment decisions and improving patient outcomes. While the apparent diffusion coefficient (ADC) and extracellular volume fraction (ECV) each provide insights into tumor biology, their combined predictive value remains underexplored.

Objective

To assess the predictive performance of ECV, derived from T1 mapping, and ADC, from diffusion-weighted imaging (DWI), both individually and in combination, for evaluating pathological features in rectal cancer.

Methods

This retrospective study included 51 patients with histologically confirmed rectal adenocarcinoma, who underwent 3.0 T MRI between October 2023 and October 2024. Quantitative ECV and ADC values were extracted from T1 mapping and DWI, respectively. Logistic regression models, incorporating Ridge and Elastic Net regularization, were used to predict T stage, vascular invasion, and nerve invasion. Five-fold cross-validation was applied, and model performance was evaluated using AUC, sensitivity, specificity, and F1 score. DeLong's test was used to compare AUCs between models.

Results

ECV and ADC values were significantly associated with pathological features. ECV was higher and ADC was lower in advanced T stage (T3–4), vascular invasion-positive, and nerve invasion-positive groups (P < 0.05). The combined ECV + ADC model achieved the highest AUCs: 0.906 for T staging, 0.811 for vascular invasion, and 0.861 for nerve invasion, outperforming single-parameter models. However, differences were not statistically significant (P > 0.05).

Conclusion

The combination of T1 mapping-derived ECV and DWI-derived ADC improves the noninvasive prediction of pathological risk factors in rectal cancer. This dual-biomarker approach may enhance preoperative assessment and support personalized treatment strategies.

背景：准确的术前预测直肠癌病理危险因素对指导治疗决策和改善患者预后至关重要。虽然表观扩散系数（ADC）和细胞外体积分数（ECV）各自提供了对肿瘤生物学的见解，但它们的综合预测价值仍未得到充分探索。目的：评估来自T1测图的ECV和来自弥散加权成像（DWI）的ADC在单独和联合评估直肠癌病理特征方面的预测性能。方法：回顾性研究包括51例组织学证实的直肠腺癌患者，于2023年10月至2024年10月接受3.0 T MRI检查。分别从T1映射和DWI中提取定量ECV和ADC值。采用Ridge和Elastic Net正则化的Logistic回归模型预测T分期、血管侵犯和神经侵犯。采用五重交叉验证，并使用AUC、敏感性、特异性和F1评分评估模型性能。DeLong检验用于比较模型之间的auc。结果：ECV、ADC值与病理特征有显著相关性。晚期T期（T3-4）、血管浸润阳性、神经浸润阳性组ECV升高，ADC降低（P  0.05）。结论：T1定位衍生的ECV与dwi衍生的ADC联合应用可提高对直肠癌病理危险因素的无创预测。这种双生物标志物方法可以增强术前评估并支持个性化治疗策略。

{"title":"Prediction of pathological risk factors in rectal cancer using combined extracellular volume fraction from T1 mapping and apparent diffusion coefficient","authors":"Mingyue Zhou , Jianwei Zeng , Chong Wang , Haini Zhang , Xiaohan Liu , Chenzi Wang , Juan Long , Yingying Cui , Hao Wang , Yankai Meng , Chunfeng Hu , Kai Xu","doi":"10.1016/j.mri.2025.110576","DOIUrl":"10.1016/j.mri.2025.110576","url":null,"abstract":"<div><h3>Background</h3><div>Accurate preoperative prediction of pathological risk factors in rectal cancer is critical for guiding treatment decisions and improving patient outcomes. While the apparent diffusion coefficient (ADC) and extracellular volume fraction (ECV) each provide insights into tumor biology, their combined predictive value remains underexplored.</div></div><div><h3>Objective</h3><div>To assess the predictive performance of ECV, derived from T1 mapping, and ADC, from diffusion-weighted imaging (DWI), both individually and in combination, for evaluating pathological features in rectal cancer.</div></div><div><h3>Methods</h3><div>This retrospective study included 51 patients with histologically confirmed rectal adenocarcinoma, who underwent 3.0 T MRI between October 2023 and October 2024. Quantitative ECV and ADC values were extracted from T1 mapping and DWI, respectively. Logistic regression models, incorporating Ridge and Elastic Net regularization, were used to predict T stage, vascular invasion, and nerve invasion. Five-fold cross-validation was applied, and model performance was evaluated using AUC, sensitivity, specificity, and F1 score. DeLong's test was used to compare AUCs between models.</div></div><div><h3>Results</h3><div>ECV and ADC values were significantly associated with pathological features. ECV was higher and ADC was lower in advanced T stage (T3–4), vascular invasion-positive, and nerve invasion-positive groups (<em>P</em> < 0.05). The combined ECV + ADC model achieved the highest AUCs: 0.906 for T staging, 0.811 for vascular invasion, and 0.861 for nerve invasion, outperforming single-parameter models. However, differences were not statistically significant (<em>P</em> > 0.05).</div></div><div><h3>Conclusion</h3><div>The combination of T1 mapping-derived ECV and DWI-derived ADC improves the noninvasive prediction of pathological risk factors in rectal cancer. This dual-biomarker approach may enhance preoperative assessment and support personalized treatment strategies.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"126 ","pages":"Article 110576"},"PeriodicalIF":2.0,"publicationDate":"2025-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145557107","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}

引用次数: 0

Repeatability of in vivo MR cytometry for measuring cell size and density in healthy human livers 体内磁共振细胞术测量健康人肝脏细胞大小和密度的可重复性。

IF 2 4区医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Magnetic resonance imaging

Pub Date : 2025-11-14 DOI: 10.1016/j.mri.2025.110563

Xiaoyu Jiang , Chaoyang Jin , Hakmook Kang , Gracie Piantek , Zhongliang Zu , John C. Gore , Junzhong Xu

Purpose

To evaluate the repeatability of MRI-derived cell size and density measurements in the healthy human liver using MR cytometry, a non-invasive technique for quantifying tissue microstructure,

Methods

Eight healthy subjects underwent two identical MR cytometry scans (2–7 days apart) on a Phillips 3 T scanner. Diffusion data were acquired using pulsed gradient spin echo (PGSE) and oscillating gradient spin echo (OGSE) sequences at multiple diffusion times. Bayes factor model selection compared different MR cytometry signal models, such as IMPULSED, which ignores water exchange between intra and extracellular compartments, and JOINT, which accounts for it. Repeatability of MRI-derived parameters were assessed via whole-volume and multi-size ROI analyses using Bland-Altman plots and correlation coefficients.

Results

The JOINT model was decisively preferred (>90 % of voxels). High repeatability was observed for

d

,

v_{in}

,

{ADC}_{ex}

, and cell density in whole-liver and larger ROIs, with correlations up to r = 0.96. ROI size significantly improved consistency. Coefficients of variation for cell density decreased from 72 % (single voxel) to 28 % (7 × 7 voxels). The exchange rate

k_{in}

could not be reliably estimated.

Conclusion

ROI-based MR cytometry provides repeatable measurements of mean cell size and density, supporting its potential for clinical applications such as assessing steatohepatitis and detecting hepatocellular carcinoma. Protocol optimization to improve SNR is needed for reliable quantification of water exchange.

目的：为了评估使用磁共振细胞术（一种用于量化组织微观结构的非侵入性技术）在健康人肝脏中进行mri衍生细胞大小和密度测量的可重复性，方法：8名健康受试者在Phillips 3 T扫描仪上进行两次相同的磁共振细胞术扫描（间隔2-7 天）。利用脉冲梯度自旋回波（PGSE）和振荡梯度自旋回波（OGSE）序列在多个扩散时刻获取扩散数据。贝叶斯因子模型选择比较了不同的MR细胞术信号模型，如忽略细胞内和细胞外隔室之间水交换的impulse和忽略细胞内和细胞外隔室之间水交换的JOINT。通过使用Bland-Altman图和相关系数进行全体积和多尺寸ROI分析，评估mri衍生参数的可重复性。结果：JOINT模型被决定性地优选（bbb90 %体素）。在全肝和更大的roi中，观察到d、vin、ADCex和细胞密度的高重复性，相关性高达r = 0.96。ROI大小显著提高了一致性。细胞密度的变异系数从72 %（单体素）下降到28 %（7 × 7体素）。汇率亲属无法可靠地估计。结论：基于roi的MR细胞术提供了可重复的平均细胞大小和密度测量，支持其潜在的临床应用，如评估脂肪性肝炎和检测肝细胞癌。为了可靠地量化水交换，需要对协议进行优化以提高信噪比。

{"title":"Repeatability of in vivo MR cytometry for measuring cell size and density in healthy human livers","authors":"Xiaoyu Jiang , Chaoyang Jin , Hakmook Kang , Gracie Piantek , Zhongliang Zu , John C. Gore , Junzhong Xu","doi":"10.1016/j.mri.2025.110563","DOIUrl":"10.1016/j.mri.2025.110563","url":null,"abstract":"<div><h3>Purpose</h3><div>To evaluate the repeatability of MRI-derived cell size and density measurements in the healthy human liver using MR cytometry, a non-invasive technique for quantifying tissue microstructure,</div></div><div><h3>Methods</h3><div>Eight healthy subjects underwent two identical MR cytometry scans (2–7 days apart) on a Phillips 3 T scanner. Diffusion data were acquired using pulsed gradient spin echo (PGSE) and oscillating gradient spin echo (OGSE) sequences at multiple diffusion times. Bayes factor model selection compared different MR cytometry signal models, such as IMPULSED, which ignores water exchange between intra and extracellular compartments, and JOINT, which accounts for it. Repeatability of MRI-derived parameters were assessed via whole-volume and multi-size ROI analyses using Bland-Altman plots and correlation coefficients.</div></div><div><h3>Results</h3><div>The JOINT model was decisively preferred (>90 % of voxels). High repeatability was observed for <span><math><mi>d</mi></math></span>, <span><math><msub><mi>v</mi><mi>in</mi></msub></math></span>, <span><math><msub><mi>ADC</mi><mi>ex</mi></msub></math></span>, and cell density in whole-liver and larger ROIs, with correlations up to <em>r</em> = 0.96. ROI size significantly improved consistency. Coefficients of variation for cell density decreased from 72 % (single voxel) to 28 % (7 × 7 voxels). The exchange rate <span><math><msub><mi>k</mi><mi>in</mi></msub></math></span> could not be reliably estimated.</div></div><div><h3>Conclusion</h3><div>ROI-based MR cytometry provides repeatable measurements of mean cell size and density, supporting its potential for clinical applications such as assessing steatohepatitis and detecting hepatocellular carcinoma. Protocol optimization to improve SNR is needed for reliable quantification of water exchange.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"126 ","pages":"Article 110563"},"PeriodicalIF":2.0,"publicationDate":"2025-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145534515","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}

引用次数: 0