Magnetic resonance imaging最新文献_第8页

A dense recurrent unrolling network leveraging spatio-temporal priors for highly-accelerated dynamic MRI 一个密集的循环展开网络利用时空先验的高加速动态MRI。

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

Magnetic resonance imaging

Pub Date : 2025-12-13 DOI: 10.1016/j.mri.2025.110595

Bin Wang , Yusheng Lian , Wan Zhang , Zilong Liu , Xiaojie Hu , Beiqing Huang , Yuanyuan Wang

Dynamic magnetic resonance imaging (MRI) requires accurate reconstruction from undersampled k-space data to achieve high temporal resolution within clinically acceptable scan times. Deep unrolling architectures have recently emerged as effective solutions by integrating physics-based data consistency with learned priors. However, their ability to exploit temporal relationships remains limited, as many approaches rely on independent stage-wise processing with only final-stage outputs propagated across iterations, which restricts feature interaction and often leads to performance degradation when acceleration factors increase. To enhance temporal prior learning, we introduce a bidirectional recurrent convolutional unit within the sparse prior update module. Our approach strengthens temporal dependency modeling by recurrently aggregating contextual information from both past and future frames, thereby improving stability and representation capacity under highly undersampled conditions. Furthermore, we incorporate inter-stage feature transmission that forwards intermediate representations instead of only single-stage outputs. This design substantially improves multi-stage collaboration, enabling more effective refinement across iterations. Experimental results on accelerated dynamic MRI datasets (6×, 12×, and 24×) demonstrate that the proposed method consistently outperforms state-of-the-art unrolling and deep learning strategies in reconstruction accuracy and temporal fidelity. Ablation studies further validate the contributions of recurrent temporal learning and inter-stage feature transmission.

动态磁共振成像（MRI）需要从欠采样k空间数据精确重建，以在临床可接受的扫描时间内实现高时间分辨率。通过将基于物理的数据一致性与学习先验相结合，深度展开架构最近成为一种有效的解决方案。然而，它们利用时间关系的能力仍然有限，因为许多方法依赖于独立的阶段处理，只有跨迭代传播的最后阶段输出，这限制了特征交互，并且当加速因素增加时经常导致性能下降。为了增强时间先验学习，我们在稀疏先验更新模块中引入了双向循环卷积单元。我们的方法通过循环地聚合过去和未来框架的上下文信息来加强时间依赖性建模，从而提高在高度欠采样条件下的稳定性和表示能力。此外，我们结合了转发中间表示的阶段间特征传输，而不仅仅是单阶段输出。这种设计极大地改进了多阶段协作，在迭代之间实现了更有效的细化。在加速动态MRI数据集（6x、12x和24x）上的实验结果表明，该方法在重建精度和时间保真度方面始终优于最先进的展开和深度学习策略。消融研究进一步证实了反复颞叶学习和阶段间特征传递的作用。

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引用次数: 0

APTWI-differential analysis for breast cancer: Association with histopathologic characteristics and early prediction of neoadjuvant chemotherapy response 乳腺癌的aptwi差异分析：与组织病理学特征和新辅助化疗反应的早期预测的关系。

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

Magnetic resonance imaging

Pub Date : 2025-12-12 DOI: 10.1016/j.mri.2025.110590

Jie Fang , Xiaoxia Wang , Lu Wang , Ying Cao , Yao Huang , Shuling Liu , Huifang Chen , Zhechuan Dai , Tao Yu , Sun Tang , Meng Lin , Yi Zhang , Jiuquan Zhang

The purpose of the study is to investigate the value of Amide proton transfer imaging(APTWI)-differential analysis in association with histopathologic characteristics, and the performance to early predict pathologic complete response (pCR) in participants with breast cancer (BC). Participants with BC who underwent pretreatment APTWI between November 2022 and April 2024 were prospectively enrolled. APT-specific signal quantification was achieved through differential analysis between model-fitted and experimentally acquired Z-spectrum at +3.5 ppm. Univariate analysis was used to identify APT^# values associated with histopathologic characteristics and pCR. The area under the receiver operating characteristic curve (AUC) analysis was performed to evaluate the diagnostic value of APTWI-DIGITAL on histopathologic characteristics and assess the predictive performance for pCR. The analysis ultimately included 123 participants with BC (mean age, 52 years±9 [SD]), 43 participants of whom received neoadjuvant chemotherapy (NAC) and 15 participants who achieved pCR. In the pre-treatment group, the APT^# values showed reasonable performance in identifying the positive status of KI67 proliferation index (P = 0.01, AUC = 0.69), and PR (P = 0.045, AUC = 0.60). In the NAC group, the APT^# values in the pCR participants showed a significant downward trend at the T1 (P = 0.01, AUC = 0.80), and was not significant between pCR and non-pCR at other timepoints. The findings suggest APTWI-differential analysis may be useful imaging biomarkers to characterize the immunohistochemical biomarkers and predict pCR to NAC in BC patients.

本研究的目的是探讨酰胺质子转移成像（APTWI）鉴别分析在乳腺癌（BC）患者中与组织病理特征相关的价值，以及早期预测病理完全缓解（pCR）的性能。在2022年11月至2024年4月期间接受APTWI预处理的BC患者被前瞻性纳入研究。通过模型拟合和实验获得的+3.5 ppm的z谱之间的差异分析，实现了apt特异性信号量化。采用单因素分析确定与组织病理学特征和pCR相关的APT#值。通过受试者工作特征曲线下面积（AUC）分析，评估APTWI-DIGITAL对组织病理特征的诊断价值，并评估pCR的预测性能。分析最终纳入123例BC患者（平均年龄52 岁±9 [SD]）， 43例接受新辅助化疗（NAC）， 15例获得pCR的患者。预处理组APT#值对KI67增殖指数（P = 0.01,AUC = 0.69）和PR （P = 0.045,AUC = 0.60）阳性状态的判断表现合理。在NAC组中，pCR参与者的APT#值在T1处呈显著下降趋势（P = 0.01,AUC = 0.80），在其他时间点pCR与非pCR之间无显著差异。研究结果表明，aptwi差异分析可能是有用的成像生物标志物，用于表征BC患者的免疫组织化学生物标志物和预测pCR到NAC。

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引用次数: 0

Application value of prostate-specific antigen density combined with multiparametric MRI in early diagnosis of prostate cancer 前列腺特异性抗原密度联合多参数MRI在前列腺癌早期诊断中的应用价值。

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

Magnetic resonance imaging

Pub Date : 2025-12-11 DOI: 10.1016/j.mri.2025.110593

Di Wu, Zhaobing Tang

Background

Diagnosis of prostate cancer in the PSA gray zone (4–10 ng/mL) and PI-RADS 3 cases remains challenging. Although multiparametric MRI (mpMRI) is widely used, its diagnostic accuracy is limited by inter-reader variability and the lack of integration with clinical indicators. Prostate-specific antigen density (PSAD) is a valuable risk stratifier, but its optimal combination with mpMRI remains unclear.

Methods

We developed a deep-learning model that integrates PSAD with mpMRI—including T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) maps derived from DWI. A cross-modal attention-guided (CM-AG) fusion module weights the PSAD and mpMRI feature branches. Performance was assessed in the PSA gray zone and the PI-RADS 3 subgroup. Ablation experiments quantified the incremental contributions of PSAD and CM-AG.

Results

The model achieved AUC = 0.89 in the PSA gray-zone cohort and AUC = 0.83 in PI-RADS 3, outperforming single-modality MRI baselines and PI-RADS–based assessment alone (DeLong p < 0.01). In patients with larger prostate volumes, specificity increased by 10.2 %. Ablation results confirmed that both PSAD and CM-AG contributed materially to performance gains.

Conclusion

Fusing PSAD with mpMRI via cross-modal attention improves diagnostic performance, particularly in challenging subgroups (PSA gray zone, PI-RADS 3). This approach may support more consistent risk stratification and earlier detection.

背景：前列腺癌PSA灰色区（4-10 ng/mL）和PI-RADS 3病例的诊断仍然具有挑战性。虽然多参数MRI （mpMRI）被广泛使用，但其诊断准确性受到阅读器间变异性和缺乏与临床指标整合的限制。前列腺特异性抗原密度（PSAD）是一个有价值的风险分层指标，但其与mpMRI的最佳组合尚不清楚。方法：我们开发了一个深度学习模型，将PSAD与mpmri相结合，包括t2加权成像（T2WI）、扩散加权成像（DWI）和由DWI导出的表观扩散系数（ADC）图。跨模态注意引导（CM-AG）融合模块对PSAD和mpMRI特征分支进行加权。在PSA灰色区和PI-RADS 3亚组中评估表现。消融实验量化了PSAD和CM-AG的增量贡献。结果：该模型在PSA灰色区队列中达到AUC = 0.89，在PI-RADS 3中达到AUC = 0.83，优于单模态MRI基线和单独基于PI-RADS的评估(DeLong p 结论：通过跨模态注意将PSAD与mpMRI融合可以提高诊断性能，特别是在具有挑战性的亚组（PSA灰色区，PI-RADS 3）。这种方法可能支持更一致的风险分层和早期检测。

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引用次数: 0

Quantitative assessment of early intervertebral disc degeneration with MR diffusion kurtosis imaging: A radiologic correlation with Pfirrmann grade 磁共振扩散峰度成像对早期椎间盘退变的定量评估：与Pfirrmann分级的放射学相关性。

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

Magnetic resonance imaging

Pub Date : 2025-12-11 DOI: 10.1016/j.mri.2025.110592

Neil Abraham Barnes , Winniecia Dkhar , Rajagopal Kadavigere , Suresh Sukumar , K. Vaishali , Abhimanyu Pradhan , P.S. Priya , Ashwin Prabhu , Nikhil Raj

Background

Degenerative spinal disease is a leading cause of lower back pain worldwide, impairing mobility and quality of life. Early degeneration is increasingly seen in younger adults due to sedentary lifestyles and occupational stress. Conventional MRI, particularly T2-weighted imaging, is limited in detecting early microstructural changes. Diffusion kurtosis imaging (DKI), by quantifying non-Gaussian water diffusion, offers enhanced sensitivity for identifying subtle alterations preceding overt degeneration.

Objective

To evaluate the ability of quantitative DKI parameters to detect early intervertebral disc degeneration by correlating them with the Pfirrmann grading system in the thoracolumbar spine.

Methods

This prospective study included 76 participants, 54 with degenerative spine disease and 22 healthy controls. MRI was performed on a 3 T scanner using sagittal T1-, T2-, and DKI sequences. Parameter maps included mean kurtosis (MK), axial kurtosis (AK), radial kurtosis (RK), fractional anisotropy (FA), and diffusivity indices (MD, AD, RD, KA). Regions of interest were placed in the nucleus pulposus and annulus fibrosus, with subregional analysis of the anterior and posterior annulus. Grade V discs were excluded, yielding (1,287) discs (Grades I–IV). Statistical analyses included group comparisons and Spearman's correlation.

Results

MK, AK, and RK were significantly higher in the degenerative group (p < 0.001), while MD, AD, and RD were substantially lower (p < 0.001). Correlations were strongest in the mid-to-lower lumbar levels, particularly within the nucleus pulposus and anterior annulus.

Conclusion

DKI enables quantitative characterisation of disc microstructure and demonstrates diagnostic potential for differentiating degenerative from non-degenerative discs, supporting its role as an emerging imaging biomarker for early degeneration assessment.

背景：退行性脊柱疾病是世界范围内腰痛的主要原因，影响活动能力和生活质量。由于久坐不动的生活方式和职业压力，早期变性在年轻人中越来越常见。传统的MRI，特别是t2加权成像，在检测早期微结构变化方面是有限的。扩散峰度成像（DKI），通过量化非高斯水扩散，为识别明显退化之前的细微变化提供了增强的灵敏度。目的：评价定量DKI参数与Pfirrmann分级系统在胸腰椎早期椎间盘退变诊断中的应用价值。方法：这项前瞻性研究包括76名参与者，54名退行性脊柱疾病患者和22名健康对照。在3 T扫描仪上使用矢状T1-， T2-和DKI序列进行MRI检查。参数图包括平均峰度（MK）、轴向峰度（AK）、径向峰度（RK）、分数各向异性（FA）和扩散系数指数（MD、AD、RD、KA）。感兴趣的区域位于髓核和纤维环，并对前后环进行分区域分析。排除V级椎间盘，共1171个（I-IV级）。统计分析包括组间比较和斯皮尔曼相关。结果：MK、AK和RK在退行性椎间盘组中显著升高（p ）结论：DKI能够定量表征椎间盘微观结构，并显示出区分退行性椎间盘和非退行性椎间盘的诊断潜力，支持其作为早期退行性椎间盘评估的新兴成像生物标志物的作用。

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引用次数: 0

Non-contrast free-running high-resolution volumetric multi-slab cardiac cine MRI at 3 T 非造影剂自由运行高分辨率多板心脏MRI在3t

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

Magnetic resonance imaging

Pub Date : 2025-12-09 DOI: 10.1016/j.mri.2025.110591

Chenhao Gao, Fan Yang, Zhihao Xue, Junyao Zhang, Zhuo Chen, Sirui Huo, Juan Gao, Yixin Emu, Haiyang Chen, Chenxi Hu

Free-running self-gated 3D cardiac cine imaging is highly desirable for volumetric, high-resolution, breath-hold-free assessment of left ventricular (LV) function. However, its implementation at 3 T remains challenging due to specific absorption rate (SAR) constraints and reduced myocardium-blood contrast. In this study, we propose a novel non-contrast, free-running, self-gated 3D gradient-echo (GRE) cine sequence for 3 T imaging, which acquires multi-slab data using a pseudo-radial Cartesian trajectory with a 1.5 mm slice thickness. To address respiratory motion, a locally low-rank motion-corrected image reconstruction algorithm was developed. Fifteen participants underwent imaging with the proposed multi-slab 3D cine sequence and conventional 2D cine sequences. Additionally, single-slab 3D cine data were acquired in 10 participants. Various image quality metrics (signal-to-noise ratio, contrast-to-noise ratio, myocardial sharpness, and residual artefact) and LV volumetric parameters (end-diastolic volume (EDV), end-systolic volume (ESV), and ejection fraction (EF)) were compared between the different methods. Results demonstrated that the proposed multi-slab 3D cine method provided significantly superior image quality compared to the single-slab 3D approach (myocardial sharpness: 2.82 ± 0.42 vs. 1.58 ± 0.46, P = 0.005; residual artefact: 2.58 ± 0.26 vs. 1.13 ± 0.21, P = 0.005) due to the improvement of image contrast. Furthermore, the multi-slab 3D cine sequence exhibited good agreement and correlation with the reference 2D cine method in terms of volumetric measures (EDV: 140.3 ± 19.9 mL vs. 139.3 ± 20.0 mL, P = 0.357, r = 0.976; ESV: 56.7 ± 11.8 mL vs. 57.7 ± 10.2 mL, P = 0.259, r = 0.964; EF: 59.8 % ± 4.9 % vs. 58.7 % ± 3.7 %, P = 0.073, r = 0.907). In conclusion, the proposed multi-slab 3D cine framework enables free-running 3 T cine imaging with whole-heart coverage and high through-plane resolution. Although myocardium-blood contrast is reduced compared to 2D breath-hold cine, the retained contrast is sufficient to evaluate LV function.

自由运行的自门控3D心脏电影成像是非常理想的容积，高分辨率，无呼吸的左心室（LV）功能评估。然而，由于特定吸收率（SAR）的限制和心肌-血液对比降低，在3t时的实施仍然具有挑战性。在这项研究中，我们提出了一种新的无对比度、自由运行、自门控的3D梯度回波（GRE）序列，用于3t成像，该序列使用1.5 mm层厚的伪径向笛卡尔轨迹获取多层数据。针对呼吸运动，提出了一种局部低秩运动校正图像重建算法。15名参与者接受了拟议的多板3D电影序列和传统的2D电影序列的成像。此外，还获得了10名参与者的单平板三维电影数据。各种图像质量指标（信噪比、对比噪声比、心肌清晰度和残余伪影）和左室容积参数（舒张末期容积（EDV）、收缩末期容积（ESV）和射血分数（EF））在不同方法之间进行了比较。结果表明，由于图像对比度的提高，多板三维成像方法的图像质量明显优于单板三维成像方法（心肌清晰度：2.82±0.42 vs. 1.58±0.46,P = 0.005；残余伪影：2.58±0.26 vs. 1.13±0.21,P = 0.005）。此外，在容积测量方面，多板三维电影序列与参考2D电影方法表现出良好的一致性和相关性（EDV: 140.3±19.9 mL对139.3±20.0 mL, P = 0.357, r = 0.976; ESV: 56.7±11.8 mL对57.7±10.2 mL, P = 0.259, r = 0.964; EF: 59.8%±4.9%对58.7%±3.7%,P = 0.073, r = 0.907）。总之，所提出的多板3D电影框架可以实现全心脏覆盖和高透平面分辨率的自由运行的3t电影成像。虽然与2D屏气片相比，心肌-血液对比降低，但保留的对比足以评估左室功能。

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引用次数: 0

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