Magnetic resonance imaging最新文献_第7页

Fast unconditional diffusion model for accelerated MRI reconstruction 加速MRI重建的快速无条件扩散模型。

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

Magnetic resonance imaging

Pub Date : 2025-10-31 DOI: 10.1016/j.mri.2025.110551

Guijiao Zhao , Chen Zhou , Jianxing Liu , Yue Hu , Peng Li

Accelerated magnetic resonance imaging (MRI) reconstruction from undersampled

k

-space data is a challenging inverse problem that has attracted significant attention in the MRI community. Diffusion models have recently emerged as a promising solution for MRI reconstruction, as they can generate high-quality samples while maintaining sample diversity. However, the inference process of diffusion models is computationally expensive, requiring thousands of steps to ensure the quality of the generated samples, which can take tens of minutes to complete. To address this issue, we propose a novel fast diffusion model for MRI reconstruction, termed FDMR, which aims to accelerate the inference process and improve reconstruction quality. The FDMR framework consists of two main components: the adversarial training of the denoising diffusion GAN and the three-stage inference framework. The adversarial training process is used to train the denoising diffusion GAN with large steps, learning an unconditional diffusion prior and embedding a deep generative prior. The proposed three-stage inference framework includes fast diffusion generation, early stopped deep generative prior adaptation, and diffusion refinement, aiming to accelerate the inference process and improve the reconstruction quality. Extensive experiments demonstrate that FDMR can achieve superior reconstruction accuracy compared to state-of-the-art diffusion methods, yet it operates 4-10 times faster, enabling the reconstruction within just 8 s.

从欠采样k空间数据中加速磁共振成像（MRI）重建是一个具有挑战性的反问题，已经引起了MRI界的极大关注。扩散模型最近成为MRI重建的一种有前途的解决方案，因为它们可以在保持样本多样性的同时生成高质量的样本。然而，扩散模型的推理过程在计算上是昂贵的，需要成千上万的步骤来保证生成的样本的质量，这可能需要几十分钟才能完成。为了解决这一问题，我们提出了一种新的MRI重建快速扩散模型，称为FDMR，旨在加快推理过程，提高重建质量。FDMR框架由两个主要部分组成：去噪扩散GAN的对抗训练和三阶段推理框架。对抗训练过程用于训练大步长的去噪扩散GAN，学习无条件扩散先验并嵌入深度生成先验。提出的三阶段推理框架包括快速扩散生成、早停深度生成先验适应和扩散细化，旨在加快推理过程，提高重构质量。大量的实验表明，与最先进的扩散方法相比，FDMR可以实现更高的重建精度，但它的运行速度要快4-10倍，只需8秒即可实现重建。

{"title":"Fast unconditional diffusion model for accelerated MRI reconstruction","authors":"Guijiao Zhao , Chen Zhou , Jianxing Liu , Yue Hu , Peng Li","doi":"10.1016/j.mri.2025.110551","DOIUrl":"10.1016/j.mri.2025.110551","url":null,"abstract":"<div><div>Accelerated magnetic resonance imaging (MRI) reconstruction from undersampled <span><math><mi>k</mi></math></span>-space data is a challenging inverse problem that has attracted significant attention in the MRI community. Diffusion models have recently emerged as a promising solution for MRI reconstruction, as they can generate high-quality samples while maintaining sample diversity. However, the inference process of diffusion models is computationally expensive, requiring thousands of steps to ensure the quality of the generated samples, which can take tens of minutes to complete. To address this issue, we propose a novel fast diffusion model for MRI reconstruction, termed FDMR, which aims to accelerate the inference process and improve reconstruction quality. The FDMR framework consists of two main components: the adversarial training of the denoising diffusion GAN and the three-stage inference framework. The adversarial training process is used to train the denoising diffusion GAN with large steps, learning an unconditional diffusion prior and embedding a deep generative prior. The proposed three-stage inference framework includes fast diffusion generation, early stopped deep generative prior adaptation, and diffusion refinement, aiming to accelerate the inference process and improve the reconstruction quality. Extensive experiments demonstrate that FDMR can achieve superior reconstruction accuracy compared to state-of-the-art diffusion methods, yet it operates 4-10 times faster, enabling the reconstruction within just 8 s.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"125 ","pages":"Article 110551"},"PeriodicalIF":2.0,"publicationDate":"2025-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145431523","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

Real-time multislice-to-volume motion correction for task-based EPI-fMRI at 7 T 基于任务的EPI-fMRI在7 T时的实时多片-体积运动校正。

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

Magnetic resonance imaging

Pub Date : 2025-10-30 DOI: 10.1016/j.mri.2025.110554

Steven Winata , Daniel Christopher Hoinkiss , Graeme Alexander Keith , Salim al-Wasity , David Andrew Porter

Magnetic resonance imaging (MRI) at ultra-high field strengths such as 7 T unlocks new opportunities. Functional MRI (fMRI) is especially able to benefit due to the increase in the inherent blood‑oxygen-level-dependant (BOLD) signal. In order to utilise this, the higher motion sensitivity at 7 T and various motion sources in fMRI protocols, especially task-based ones, need to be mitigated. This motivated the development of a 7 T implementation of the real-time, prospective Multislice Prospective Acquisition Correction (MS-PACE) technique. MS-PACE allows for a sub-TR, higher temporal resolution motion correction without the need for external tracking equipment. We present an echo-planar imaging (EPI) implementation, evaluated in a 7 T task-based fMRI study. The results show that the technique led to significant, consistent reduction in residual motion across the scanned cohort. An analysis of the temporal SNR of the resting-state scans indicated a general increase in this metric when prospective motion correction was activated. Functional analysis of the data showed an apparent reduction of artefactual activations compared to a standard retrospective motion correction algorithm.

7 T等超高场强的磁共振成像（MRI）带来了新的机遇。由于固有血氧水平依赖性（BOLD）信号的增加，功能性磁共振成像（fMRI）尤其能够受益。为了利用这一点，需要减轻7 T和fMRI协议中各种运动源的较高运动灵敏度，特别是基于任务的运动源。这推动了7 T实现实时、前瞻性多片前瞻性采集校正（MS-PACE）技术的发展。MS-PACE允许在不需要外部跟踪设备的情况下进行子tr，更高时间分辨率的运动校正。我们提出了一种回声平面成像（EPI）的实现，在一项7 T基于任务的fMRI研究中进行了评估。结果表明，该技术在整个扫描队列中导致了显著的、一致的残余运动减少。静息状态扫描的时间信噪比分析表明，当预期运动校正被激活时，该指标普遍增加。数据的功能分析显示，与标准的回顾性运动校正算法相比，人工激活明显减少。

{"title":"Real-time multislice-to-volume motion correction for task-based EPI-fMRI at 7 T","authors":"Steven Winata , Daniel Christopher Hoinkiss , Graeme Alexander Keith , Salim al-Wasity , David Andrew Porter","doi":"10.1016/j.mri.2025.110554","DOIUrl":"10.1016/j.mri.2025.110554","url":null,"abstract":"<div><div>Magnetic resonance imaging (MRI) at ultra-high field strengths such as 7 T unlocks new opportunities. Functional MRI (fMRI) is especially able to benefit due to the increase in the inherent blood‑oxygen-level-dependant (BOLD) signal. In order to utilise this, the higher motion sensitivity at 7 T and various motion sources in fMRI protocols, especially task-based ones, need to be mitigated. This motivated the development of a 7 T implementation of the real-time, prospective Multislice Prospective Acquisition Correction (MS-PACE) technique. MS-PACE allows for a sub-TR, higher temporal resolution motion correction without the need for external tracking equipment. We present an echo-planar imaging (EPI) implementation, evaluated in a 7 T task-based fMRI study. The results show that the technique led to significant, consistent reduction in residual motion across the scanned cohort. An analysis of the temporal SNR of the resting-state scans indicated a general increase in this metric when prospective motion correction was activated. Functional analysis of the data showed an apparent reduction of artefactual activations compared to a standard retrospective motion correction algorithm.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"125 ","pages":"Article 110554"},"PeriodicalIF":2.0,"publicationDate":"2025-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145422017","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

Integration of radiomics, habitat imaging, and deep learning for MRI-based prediction of parametrial invasion in cervical cancer: A dual-center study 放射组学、栖息地成像和深度学习在基于mri的宫颈癌参数浸润预测中的整合：一项双中心研究。

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

Magnetic resonance imaging

Pub Date : 2025-10-30 DOI: 10.1016/j.mri.2025.110542

Yuemei Cui , Ya Li , Jing Na , Junling Lu , Xinyou Wang , Shichao Han , Jun Wang

Objectives

To assess the diagnostic performance of radiomics, habitat imaging, and 2.5D deep learning models for MRI-based prediction of parametrial invasion in cervical cancer, and to evaluate the clinical utility of a multimodal integrated model.

Methods

This dual-center retrospective study included 290 patients with FIGO stage IB1–IIB cervical cancer who underwent preoperative MRI. Patients from Center A (n = 227) were divided into training and validation cohorts, while patients from Center B (n = 63) comprised the external test cohort. Radiomic features were extracted, habitat imaging was performed using k-means clustering, and a 2.5D deep learning model incorporated adjacent slices. Feature selection was conducted using Pearson correlation and LASSO regression. Machine learning models were developed, and an integrated model was constructed. Model performance was evaluated using AUC and accuracy. AUCs were compared with DeLong tests, calibration was assessed with the Hosmer–Lemeshow test, and clinical utility was evaluated with decision curve analysis.

Results

The integrated model outperformed all individual models, achieving AUCs of 0.973, 0.901, and 0.906 in the training, validation, and external test cohorts, respectively. Among individual models, the deep-learning model showed the highest AUCs (0.954, 0.803, 0.833), followed by habitat imaging (0.860, 0.811, 0.843). In the external test cohort, the peritumoral radiomics model outperformed the intratumoral model (0.843 vs. 0.719). The clinical model showed the lowest performance. Hosmer–Lemeshow tests indicated good calibration, and decision curve analysis confirmed superior clinical utility of the integrated model.

Conclusion

The multimodal integrated model, combining radiomics, habitat imaging, 2.5D deep learning, and clinical features, demonstrated superior predictive performance for parametrial invasion in cervical cancer compared with individual models. This approach may enhance preoperative assessment, guide clinical decision-making, and optimize treatment strategies.

目的：评估放射组学、栖息地成像和2.5D深度学习模型在基于mri的宫颈癌参数浸润预测中的诊断性能，并评估多模态集成模型的临床应用价值。方法：本双中心回顾性研究纳入290例FIGO分期IB1-IIB宫颈癌患者，术前行MRI检查。来自A中心的患者（n = 227）分为训练和验证队列，而来自B中心的患者（n = 63）组成外部测试队列。提取放射学特征，使用k-means聚类进行栖息地成像，并结合相邻切片构建2.5D深度学习模型。使用Pearson相关和LASSO回归进行特征选择。建立机器学习模型，构建集成模型。使用AUC和精度评估模型性能。将auc与DeLong试验进行比较，采用Hosmer-Lemeshow试验评估校准，采用决策曲线分析评估临床效用。结果：综合模型优于所有单独模型，在训练、验证和外部测试队列中的auc分别为0.973、0.901和0.906。各模型中，深度学习模型auc最高（0.954、0.803、0.833），其次为生境成像（0.860、0.811、0.843）。在外部测试队列中，肿瘤周围放射组学模型优于肿瘤内模型（0.843比0.719）。临床模型表现最差。Hosmer-Lemeshow试验显示校正效果良好，决策曲线分析证实了该综合模型具有较好的临床应用价值。结论：结合放射组学、栖息地成像、2.5D深度学习和临床特征的多模态集成模型对宫颈癌参数性侵袭的预测效果优于单个模型。该方法可加强术前评估，指导临床决策，优化治疗策略。

{"title":"Integration of radiomics, habitat imaging, and deep learning for MRI-based prediction of parametrial invasion in cervical cancer: A dual-center study","authors":"Yuemei Cui , Ya Li , Jing Na , Junling Lu , Xinyou Wang , Shichao Han , Jun Wang","doi":"10.1016/j.mri.2025.110542","DOIUrl":"10.1016/j.mri.2025.110542","url":null,"abstract":"<div><h3>Objectives</h3><div>To assess the diagnostic performance of radiomics, habitat imaging, and 2.5D deep learning models for MRI-based prediction of parametrial invasion in cervical cancer, and to evaluate the clinical utility of a multimodal integrated model.</div></div><div><h3>Methods</h3><div>This dual-center retrospective study included 290 patients with FIGO stage IB1–IIB cervical cancer who underwent preoperative MRI. Patients from Center A (<em>n</em> = 227) were divided into training and validation cohorts, while patients from Center B (<em>n</em> = 63) comprised the external test cohort. Radiomic features were extracted, habitat imaging was performed using k-means clustering, and a 2.5D deep learning model incorporated adjacent slices. Feature selection was conducted using Pearson correlation and LASSO regression. Machine learning models were developed, and an integrated model was constructed. Model performance was evaluated using AUC and accuracy. AUCs were compared with DeLong tests, calibration was assessed with the Hosmer–Lemeshow test, and clinical utility was evaluated with decision curve analysis.</div></div><div><h3>Results</h3><div>The integrated model outperformed all individual models, achieving AUCs of 0.973, 0.901, and 0.906 in the training, validation, and external test cohorts, respectively. Among individual models, the deep-learning model showed the highest AUCs (0.954, 0.803, 0.833), followed by habitat imaging (0.860, 0.811, 0.843). In the external test cohort, the peritumoral radiomics model outperformed the intratumoral model (0.843 vs. 0.719). The clinical model showed the lowest performance. Hosmer–Lemeshow tests indicated good calibration, and decision curve analysis confirmed superior clinical utility of the integrated model.</div></div><div><h3>Conclusion</h3><div>The multimodal integrated model, combining radiomics, habitat imaging, 2.5D deep learning, and clinical features, demonstrated superior predictive performance for parametrial invasion in cervical cancer compared with individual models. This approach may enhance preoperative assessment, guide clinical decision-making, and optimize treatment strategies.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"125 ","pages":"Article 110542"},"PeriodicalIF":2.0,"publicationDate":"2025-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145422019","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

Feasibility of MR-tagging to quantify spinal cord motion in degenerative cervical myelopathy 核磁共振标记量化退行性颈椎病脊髓运动的可行性。

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

Magnetic resonance imaging

Pub Date : 2025-10-26 DOI: 10.1016/j.mri.2025.110555

Constantin von Deuster , Georg Wilhelm Kajdi , Shila Pazahr , Nikolai Pfender , Markus Hupp , Armin Curt , Reto Sutter , Daniel Nanz

Background

The aim of this study was to investigate the feasibility of MR-tagging for direct visualization and quantification of pathologically altered spinal-cord motion in patients with cervical spinal stenosis and compare it to the standard approach of phase contrast (PC) imaging.

Methods

In this prospective study, sagittal sections (22 cm field of view) of the cervical spine of nine patients with mono-segmental spinal-canal stenosis were imaged in different heart phases after selective pre-saturation of tissue magnetization in an axially oriented tag-stripe pattern (MR-tagging). Video loops of images acquired in different heart phases were viewed to directly observe and compare head-feet (HF) displacement at the level of the stenosis. The maximum HF displacement of MR-tags in the cord was quantitatively assessed and compared to that derived from integration of PC velocity data.

Results

Regional MR-tag displacement in the spinal cord could successfully be observed in all patients (4 females, 5 males, mean age 57 ± 7 years). Maximum displacement data derived from tagging at the stenosis level correlated excellently (R² = 0.84) with matched measurements from PC imaging.

Conclusion

Without complex post-processing, MR-tag imaging provides an intuitive direct visualization and quantification of pathologically altered spinal-cord motion at the level of cervical stenosis offering a faster alternative to PC imaging in clinical routine.

背景：本研究的目的是探讨核磁共振标记对颈椎管狭窄患者病理改变的脊髓运动的直接可视化和量化的可行性，并将其与标准的相位对比（PC）成像方法进行比较。方法：在这项前瞻性研究中，对9例单节段椎管狭窄患者的颈椎矢状面（22 cm视野）进行轴向标记-条纹模式（MR-tagging）选择性预饱和组织磁化后，在不同的心脏阶段进行成像。观察不同心脏期影像的视频循环，直接观察和比较狭窄水平的头足位移。定量评估了脐带中核磁共振标签的最大高频位移，并与PC速度数据集成得出的位移进行了比较。结果：所有患者（女性4例，男性5例，平均年龄57岁 ± 7 岁）均可成功观察到脊髓局部核磁共振标签移位。狭窄水平标记的最大位移数据与PC成像的匹配测量结果极好地相关（R2 = 0.84）。结论：无需复杂的后处理，磁共振标签成像在颈椎狭窄水平提供了直观的直接可视化和定量病理改变的脊髓运动，在临床常规中提供了比PC成像更快的选择。

{"title":"Feasibility of MR-tagging to quantify spinal cord motion in degenerative cervical myelopathy","authors":"Constantin von Deuster , Georg Wilhelm Kajdi , Shila Pazahr , Nikolai Pfender , Markus Hupp , Armin Curt , Reto Sutter , Daniel Nanz","doi":"10.1016/j.mri.2025.110555","DOIUrl":"10.1016/j.mri.2025.110555","url":null,"abstract":"<div><h3>Background</h3><div>The aim of this study was to investigate the feasibility of MR-tagging for direct visualization and quantification of pathologically altered spinal-cord motion in patients with cervical spinal stenosis and compare it to the standard approach of phase contrast (PC) imaging.</div></div><div><h3>Methods</h3><div>In this prospective study, sagittal sections (22 cm field of view) of the cervical spine of nine patients with mono-segmental spinal-canal stenosis were imaged in different heart phases after selective pre-saturation of tissue magnetization in an axially oriented tag-stripe pattern (MR-tagging). Video loops of images acquired in different heart phases were viewed to directly observe and compare head-feet (HF) displacement at the level of the stenosis. The maximum HF displacement of MR-tags in the cord was quantitatively assessed and compared to that derived from integration of PC velocity data.</div></div><div><h3>Results</h3><div>Regional MR-tag displacement in the spinal cord could successfully be observed in all patients (4 females, 5 males, mean age 57 ± 7 years). Maximum displacement data derived from tagging at the stenosis level correlated excellently (R<sup>2</sup> = 0.84) with matched measurements from PC imaging.</div></div><div><h3>Conclusion</h3><div>Without complex post-processing, MR-tag imaging provides an intuitive direct visualization and quantification of pathologically altered spinal-cord motion at the level of cervical stenosis offering a faster alternative to PC imaging in clinical routine.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"125 ","pages":"Article 110555"},"PeriodicalIF":2.0,"publicationDate":"2025-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145390825","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

Quantitative proton density fat-fraction at 9.4 T using fast spin echo and asymmetric multi-echo gradient-echo pulse sequences 使用快速自旋回波和非对称多回波梯度回波脉冲序列在9.4 T下定量质子密度脂肪分数

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

Magnetic resonance imaging

Pub Date : 2025-10-24 DOI: 10.1016/j.mri.2025.110550

Radim Kořínek, Lucie Krátká, Zenon Starčuk Jr

Purpose

Quantifying proton density fat fraction (PDFF) in small abdominal organs is challenging due to low T₁/T₂ contrast and susceptibility artifacts. We develop a hybrid 7-echo CSE-MRI sequence with arbitrary echo spacing, inspired by GRASE-type imaging, aiming for distortion-free PDFF mapping in small animals. The method is designed to be comparable to established conventional methods, with potential for increased robustness.

Methods

We developed a Fast Spin Echo Asymmetric Bipolar Multi-Gradient Echo (FSE-AbMGE) sequence by integrating a fast spin-echo readout with an asymmetrically placed bipolar multi-echo gradient-echo train. The sequence was implemented at 9.4 T and combined with robust phase unwrapping and water-fat reconstruction algorithms using full fat spectral modeling. Validation was performed using phantoms with known PDFF values (0–22 %) and in vivo experiments on several female mice (n = 2). Reference PDFF values were obtained using single-voxel ¹H-MRS.

Results

The proposed method enabled high-resolution PDFF mapping with minimal chemical shift and susceptibility artifacts. Phantom experiments showed strong agreement with both spectroscopic and ground truth values (R² > 0.98, p < 0.001). The method was also tested in vivo, demonstrating robust water-fat separation and quantification.

Conclusion

The FSE-AbMGE sequence is well-suited for accurate abdominal fat quantification in small animals. While additional validation is needed, especially in reproducibility and broader biological settings, the method shows promise for high-field fat quantification and may offer a framework adaptable to lower-field pre-clinical applications.

目的：由于低T1/T2对比和敏感性伪影，腹部小器官的质子密度脂肪分数（PDFF）的定量具有挑战性。受grase型成像的启发，我们开发了一种具有任意回波间隔的混合7回波CSE-MRI序列，旨在对小动物进行无失真的PDFF成像。该方法的设计可与已建立的常规方法相媲美，具有增强鲁棒性的潜力。方法将快速自旋回波读出与不对称放置的双极多回波梯度回波序列相结合，构建了快速自旋回波非对称双极多回波梯度回波序列。该序列在9.4 T下实现，并结合了健壮的相位展开和使用全脂肪谱建模的水脂肪重建算法。通过已知PDFF值（0 - 22%）的模型和几只雌性小鼠（n = 2）的体内实验进行验证。采用单体素1H-MRS获得参考PDFF值。结果该方法能以最小的化学位移和敏感性伪影实现高分辨率PDFF制图。幻影实验显示与光谱和地面真值非常吻合（R2 > 0.98, p < 0.001）。该方法还在体内进行了测试，证明了稳健的水脂肪分离和定量。结论FSE-AbMGE序列适用于小动物腹部脂肪的精确定量。虽然需要额外的验证，特别是在可重复性和更广泛的生物学环境中，该方法显示出高场脂肪定量的前景，并可能提供一个适用于低场临床前应用的框架。

{"title":"Quantitative proton density fat-fraction at 9.4 T using fast spin echo and asymmetric multi-echo gradient-echo pulse sequences","authors":"Radim Kořínek, Lucie Krátká, Zenon Starčuk Jr","doi":"10.1016/j.mri.2025.110550","DOIUrl":"10.1016/j.mri.2025.110550","url":null,"abstract":"<div><h3><strong>Purpose</strong></h3><div>Quantifying proton density fat fraction (PDFF) in small abdominal organs is challenging due to low <em>T</em><sub>1</sub>/<em>T</em><sub>2</sub> contrast and susceptibility artifacts. We develop a hybrid 7-echo CSE-MRI sequence with arbitrary echo spacing, inspired by GRASE-type imaging, aiming for distortion-free PDFF mapping in small animals. The method is designed to be comparable to established conventional methods, with potential for increased robustness.</div></div><div><h3><strong>Methods</strong></h3><div>We developed a Fast Spin Echo Asymmetric Bipolar Multi-Gradient Echo (FSE-AbMGE) sequence by integrating a fast spin-echo readout with an asymmetrically placed bipolar multi-echo gradient-echo train. The sequence was implemented at 9.4 T and combined with robust phase unwrapping and water-fat reconstruction algorithms using full fat spectral modeling. Validation was performed using phantoms with known PDFF values (0–22 %) and in vivo experiments on several female mice (<em>n</em> = 2). Reference PDFF values were obtained using single-voxel <sup>1</sup>H-MRS.</div></div><div><h3><strong>Results</strong></h3><div>The proposed method enabled high-resolution PDFF mapping with minimal chemical shift and susceptibility artifacts. Phantom experiments showed strong agreement with both spectroscopic and ground truth values (R<sup>2</sup> > 0.98, <em>p</em> < 0.001). The method was also tested in vivo, demonstrating robust water-fat separation and quantification.</div></div><div><h3><strong>Conclusion</strong></h3><div>The FSE-AbMGE sequence is well-suited for accurate abdominal fat quantification in small animals. While additional validation is needed, especially in reproducibility and broader biological settings, the method shows promise for high-field fat quantification and may offer a framework adaptable to lower-field pre-clinical applications.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"125 ","pages":"Article 110550"},"PeriodicalIF":2.0,"publicationDate":"2025-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145425788","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

The quantitative spatiotemporal relationship of whole brain activity of human brains revealed by fMRI 功能磁共振成像（fMRI）揭示的人类全脑活动定量时空关系

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

Magnetic resonance imaging

Pub Date : 2025-10-24 DOI: 10.1016/j.mri.2025.110552

Jie Huang

It is imperative to study individual brain functioning for understanding the neural bases of individual behavioral and clinical traits. BOLD-fMRI measures the four-dimensional (3 spatial and 1 temporal) neural activity across the entire brain at large-scale systems level. All local activities across the entire brain constitute the whole brain activity and each local activity is a part of that whole brain activity. Unlike a local activity that is characterized by its temporal neural activity, the whole brain activity is characterized by its spatial variation across the entire brain. We present a novel data-driven method to analyze the whole brain activity when performing tasks. The method enabled us to analyze the whole brain activity for each task trial and each individual subject with no requirement of a priori knowledge of task-evoked BOLD response. Our study revealed a quantitative spatiotemporal relationship of the whole brain activity with the local activities. The whole brain activity demonstrated a remarkable dynamic activity that varied from trial to trial when performing the same task repeatedly, showing the importance of analyzing the whole brain activity for investigating the neural bases of personal traits.

研究个体脑功能对于理解个体行为和临床特征的神经基础是必要的。BOLD-fMRI在大尺度系统水平上测量整个大脑的四维（3个空间和1个时间）神经活动。整个大脑的所有局部活动都构成了整个大脑活动，而每个局部活动都是整个大脑活动的一部分。与局部活动以其时间神经活动为特征不同，全脑活动以其在整个大脑中的空间变化为特征。我们提出了一种新的数据驱动方法来分析执行任务时的全脑活动。该方法使我们能够分析每个任务试验和每个个体受试者的整个大脑活动，而不需要对任务诱发的BOLD反应有先验知识。我们的研究揭示了全脑活动与局部活动的定量时空关系。在重复执行相同的任务时，全脑活动表现出显著的动态变化，表明分析全脑活动对于研究个人特征的神经基础的重要性。

{"title":"The quantitative spatiotemporal relationship of whole brain activity of human brains revealed by fMRI","authors":"Jie Huang","doi":"10.1016/j.mri.2025.110552","DOIUrl":"10.1016/j.mri.2025.110552","url":null,"abstract":"<div><div>It is imperative to study individual brain functioning for understanding the neural bases of individual behavioral and clinical traits. BOLD-fMRI measures the four-dimensional (3 spatial and 1 temporal) neural activity across the entire brain at large-scale systems level. All local activities across the entire brain constitute the whole brain activity and each local activity is a part of that whole brain activity. Unlike a local activity that is characterized by its temporal neural activity, the whole brain activity is characterized by its spatial variation across the entire brain. We present a novel data-driven method to analyze the whole brain activity when performing tasks. The method enabled us to analyze the whole brain activity for each task trial and each individual subject with no requirement of a priori knowledge of task-evoked BOLD response. Our study revealed a quantitative spatiotemporal relationship of the whole brain activity with the local activities. The whole brain activity demonstrated a remarkable dynamic activity that varied from trial to trial when performing the same task repeatedly, showing the importance of analyzing the whole brain activity for investigating the neural bases of personal traits.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"125 ","pages":"Article 110552"},"PeriodicalIF":2.0,"publicationDate":"2025-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145425789","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

Monte Carlo simulations of transverse relaxation for characterization of physicochemical properties of superparamagnetic iron oxide nanoparticles 表征超顺磁性氧化铁纳米颗粒物理化学性质的横向弛豫蒙特卡罗模拟

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

Magnetic resonance imaging

Pub Date : 2025-10-24 DOI: 10.1016/j.mri.2025.110553

Lauritz Klünder , Bastian Maus , María Belén Rivas Aiello , Athina Drakonaki , Michael Holtkamp , Uwe Karst , Christos Gatsogiannis , Cristian Strassert , Cornelius Faber

Superparamagnetic iron oxide nanoparticles are used in MRI as

T_{2}

or

T_{2}^{*}

contrast agents and, in combination with relaxometry, enable quantitative analysis of physiological and pathological processes. However, the induced changes in relaxation times are influenced by a complex interplay of the contrast agents' physicochemical properties. Here, an open-source Monte Carlo simulation pipeline was implemented, which enables the characterization of these relaxation time changes caused by MRI contrast agents. The simulation tool was validated by showing that simulated relaxation times for iron oxide particles matched the solutions of analytical models of the respective diffusion regimes. For comparison with relaxometry measurements,

T_{2}

and

T_{2}^{*}

of four MRI contrast agents Ferucarbotran, FeraSpin XL, magnetite nanohexagons (MNH@OH) and magnetite nanocubes (MNC@OH) were simulated, using three approaches for modeling contrast agent size and composition: 1) uniform particle sizes using the median hydrodynamic radii; 2) distributed radii corresponding to measured hydrodynamic radius distributions; 3) size-distributed magnetite cores in a coating layer of uniform radius. The simulation accurately reproduced measured relaxation times when appropriate modeling strategies for contrast agent size and composition were used. For FeraSpin XL and MNH@OH, using uniform radii provided good estimates of relaxation times, which was further improved by using the size distributions. For MNC@OH, discrepancies in simulated and measured

T_{2}

for all approaches were attributed to particle aggregation. For Ferucarbotran, coating and size distribution of the core had to be considered to match experimental data.

超顺磁性氧化铁纳米颗粒在MRI中用作T2或T2 *造影剂，并与松弛法结合使用，可以定量分析生理和病理过程。然而，诱导弛豫时间的变化受到造影剂的物理化学性质的复杂相互作用的影响。在这里，实现了一个开源的蒙特卡罗模拟管道，它能够表征MRI造影剂引起的这些弛豫时间变化。模拟工具通过显示氧化铁颗粒的模拟弛豫时间与各自扩散机制的解析模型的解相匹配来验证。为了与松弛测量结果进行比较，采用三种方法模拟造影剂大小和组成，模拟了四种MRI造影剂Ferucarbotran， FeraSpin XL，磁铁矿纳米六边形（MNH@OH）和磁铁矿纳米立方体（MNC@OH）的T2和T2∗:1)使用中位数流体动力半径均匀粒径；2)实测水动力半径分布对应的分布半径；3)磁铁矿岩心分布在半径均匀的涂覆层中。当使用适当的造影剂大小和成分建模策略时，模拟准确地再现了测量到的松弛时间。对于FeraSpin XL和MNH@OH，使用均匀半径可以很好地估计松弛时间，通过使用尺寸分布可以进一步改善松弛时间。对于MNC@OH，所有方法的模拟和测量T2的差异归因于颗粒聚集。对于碳铁，必须考虑涂层和芯的尺寸分布以匹配实验数据。

{"title":"Monte Carlo simulations of transverse relaxation for characterization of physicochemical properties of superparamagnetic iron oxide nanoparticles","authors":"Lauritz Klünder , Bastian Maus , María Belén Rivas Aiello , Athina Drakonaki , Michael Holtkamp , Uwe Karst , Christos Gatsogiannis , Cristian Strassert , Cornelius Faber","doi":"10.1016/j.mri.2025.110553","DOIUrl":"10.1016/j.mri.2025.110553","url":null,"abstract":"<div><div>Superparamagnetic iron oxide nanoparticles are used in MRI as <span><math><msub><mi>T</mi><mn>2</mn></msub></math></span> or <span><math><msubsup><mi>T</mi><mn>2</mn><mo>∗</mo></msubsup></math></span> contrast agents and, in combination with relaxometry, enable quantitative analysis of physiological and pathological processes. However, the induced changes in relaxation times are influenced by a complex interplay of the contrast agents' physicochemical properties. Here, an open-source Monte Carlo simulation pipeline was implemented, which enables the characterization of these relaxation time changes caused by MRI contrast agents. The simulation tool was validated by showing that simulated relaxation times for iron oxide particles matched the solutions of analytical models of the respective diffusion regimes. For comparison with relaxometry measurements, <span><math><msub><mi>T</mi><mn>2</mn></msub></math></span> and <span><math><msubsup><mi>T</mi><mn>2</mn><mo>∗</mo></msubsup></math></span> of four MRI contrast agents Ferucarbotran, FeraSpin XL, magnetite nanohexagons (MNH@OH) and magnetite nanocubes (MNC@OH) were simulated, using three approaches for modeling contrast agent size and composition: 1) uniform particle sizes using the median hydrodynamic radii; 2) distributed radii corresponding to measured hydrodynamic radius distributions; 3) size-distributed magnetite cores in a coating layer of uniform radius. The simulation accurately reproduced measured relaxation times when appropriate modeling strategies for contrast agent size and composition were used. For FeraSpin XL and MNH@OH, using uniform radii provided good estimates of relaxation times, which was further improved by using the size distributions. For MNC@OH, discrepancies in simulated and measured <span><math><msub><mi>T</mi><mn>2</mn></msub></math></span> for all approaches were attributed to particle aggregation. For Ferucarbotran, coating and size distribution of the core had to be considered to match experimental data.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"125 ","pages":"Article 110553"},"PeriodicalIF":2.0,"publicationDate":"2025-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145425790","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

Investigating microbleeds and white matter hyperintensities in TBI at a tract-level: A DTI study TBI微出血和白质高信号在神经束水平的研究：一项DTI研究。

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

Magnetic resonance imaging

Pub Date : 2025-10-17 DOI: 10.1016/j.mri.2025.110541

Zalán Petneházy , Dávid Bognár , Péter Laar , Tamás Dóczi , Attila Schwarcz , Bálint S. Környei , Arnold Tóth

Objectives

This study aimed to determine whether focal MRI lesions such as microbleeds (MBs) and focal white matter hyperintensities (FWMHs) serve as reliable and specific markers for tract-level white matter injury in traumatic brain injury (TBI).

Materials & methods

Twenty-two patients with moderate-to-severe TBI and 22 age-matched healthy controls underwent MRI on a 3 T Siemens Prisma scanner. Imaging included susceptibility-weighted imaging (SWI), fluid-attenuated inversion recovery (FLAIR), and diffusion tensor imaging (DTI). Focal lesions were manually identified on SWI and FLAIR and mapped onto tractography reconstructions. Diffusion metrics—fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were compared between lesion-affected tracts, contralateral normal-appearing white matter (NAWM), and corresponding control tracts. Statistical analyses were performed using repeated measures ANOVA with Greenhouse-Geisser correction and Bonferroni-adjusted post hoc tests for FA. Friedman tests were conducted for MD, AD, and RD, followed by Bonferroni-corrected Wilcoxon post hoc comparisons.

Results

In this study, we identified 27 MBs and 66 FWMHs intersecting white matter tracts. We observed notable differences in diffusion metrics when comparing lesion-affected tracts to healthy controls. In MB-affected tracts, fractional anisotropy (FA) differed significantly (p = 0.002), while mean diffusivity (MD) also showed a significant alteration (p = 0.002), along with radial diffusivity (RD) (p < 0.001). Similarly, in FWMH-affected tracts, significant differences were observed in FA (p < 0.001), MD (p < 0.001), axial diffusivity (AD) (p < 0.001), and RD (p < 0.001). However, we did not find any significant differences between lesion-affected tracts and the contralateral normal-appearing white matter (NAWM).

Conclusion

MBs and FWMHs do not co-localize with axonal injury at the tract level but indicate a global white matter damage.

目的：本研究旨在确定局灶性MRI病变，如微出血（MBs）和局灶性白质高信号（FWMHs）是否可作为创伤性脑损伤（TBI）中神经束水平白质损伤的可靠和特异性标志物。材料和方法：22例中重度TBI患者和22例年龄匹配的健康对照者在3 T西门子Prisma扫描仪上进行MRI。成像包括磁化率加权成像（SWI）、流体衰减反演恢复（FLAIR）和扩散张量成像（DTI）。在SWI和FLAIR上手动识别局灶性病变，并将其映射到牵道造影重建上。比较病变影响束、对侧正常白质束（NAWM）和相应对照束的扩散指标——分数各向异性（FA）、平均扩散率（MD）、轴向扩散率（AD）和径向扩散率（RD）。统计分析采用重复测量方差分析，采用温室-盖瑟校正和bonferroni校正的FA事后检验。对MD、AD和RD进行Friedman检验，然后进行bonferroni校正的Wilcoxon事后比较。结果：在本研究中，我们鉴定了27个mb和66个fwmh相交于白质束。我们观察到弥散指标的显著差异，当比较病变影响束和健康对照。在mb影响的神经束中，分数各向异性（FA）差异显著（p = 0.002），平均弥漫性（MD）也有显著变化（p = 0.002），径向弥漫性（RD）也有显著变化（p ）。结论：mb和fwmh在神经束水平上不与轴突损伤共发，但表明白质损伤的全身性。

{"title":"Investigating microbleeds and white matter hyperintensities in TBI at a tract-level: A DTI study","authors":"Zalán Petneházy , Dávid Bognár , Péter Laar , Tamás Dóczi , Attila Schwarcz , Bálint S. Környei , Arnold Tóth","doi":"10.1016/j.mri.2025.110541","DOIUrl":"10.1016/j.mri.2025.110541","url":null,"abstract":"<div><h3>Objectives</h3><div>This study aimed to determine whether focal MRI lesions such as microbleeds (MBs) and focal white matter hyperintensities (FWMHs) serve as reliable and specific markers for tract-level white matter injury in traumatic brain injury (TBI).</div></div><div><h3>Materials & methods</h3><div>Twenty-two patients with moderate-to-severe TBI and 22 age-matched healthy controls underwent MRI on a 3 T Siemens Prisma scanner. Imaging included susceptibility-weighted imaging (SWI), fluid-attenuated inversion recovery (FLAIR), and diffusion tensor imaging (DTI). Focal lesions were manually identified on SWI and FLAIR and mapped onto tractography reconstructions. Diffusion metrics—fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were compared between lesion-affected tracts, contralateral normal-appearing white matter (NAWM), and corresponding control tracts. Statistical analyses were performed using repeated measures ANOVA with Greenhouse-Geisser correction and Bonferroni-adjusted post hoc tests for FA. Friedman tests were conducted for MD, AD, and RD, followed by Bonferroni-corrected Wilcoxon post hoc comparisons.</div></div><div><h3>Results</h3><div>In this study, we identified 27 MBs and 66 FWMHs intersecting white matter tracts. We observed notable differences in diffusion metrics when comparing lesion-affected tracts to healthy controls. In MB-affected tracts, fractional anisotropy (FA) differed significantly (<em>p</em> = 0.002), while mean diffusivity (MD) also showed a significant alteration (p = 0.002), along with radial diffusivity (RD) (<em>p</em> < 0.001). Similarly, in FWMH-affected tracts, significant differences were observed in FA (<em>p</em> < 0.001), MD (p < 0.001), axial diffusivity (AD) (p < 0.001), and RD (p < 0.001). However, we did not find any significant differences between lesion-affected tracts and the contralateral normal-appearing white matter (NAWM).</div></div><div><h3>Conclusion</h3><div>MBs and FWMHs do not co-localize with axonal injury at the tract level but indicate a global white matter damage.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"125 ","pages":"Article 110541"},"PeriodicalIF":2.0,"publicationDate":"2025-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145329540","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

Total tumor apparent diffusion coefficient histogram analysis of whole-body DWI-MRI for prognostic stratification in patients with R-ISS stage II multiple myeloma 全肿瘤表观扩散系数直方图分析在R-ISS II期多发性骨髓瘤患者预后分层中的应用。

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

Magnetic resonance imaging

Pub Date : 2025-10-14 DOI: 10.1016/j.mri.2025.110536

Junde Zhou , Qin Wang , Yanting Liu , Lu Zhang , Jiao Li , Shuo Li , Dong Liu , Jinxia Zhu , Robert Grimm , Alto Stemmer , Shuang Xia , Wenyang Huang , Sheng Xie , Haibo Zhang , Jian Li , Huadan Xue , Zhengyu Jin

Purpose

This study aimed to explore the utility of total tumor apparent diffusion coefficient (ttADC) histogram analysis based on whole-body diffusion-weighted magnetic resonance imaging (DWI-MRI) for prognostic stratification in patients with Revised International Staging System stage II (R-ISS II) multiple myeloma (MM).

Methods

Patients with R-ISS II MM who underwent baseline whole-body MRI prior to treatment were retrospectively enrolled. The ttADC histogram parameters of the whole-body DWI-MRI were obtained using MR Total Tumor Load software (Siemens Healthcare, Erlangen, Germany). The overall survival (OS) and the progression-free survival (PFS) of the cohort was recorded. Cox regression analyses were used to evaluate the clinical features and ttADC histogram parameters for their association with OS and PFS.

Results

A total of 61 R-ISS II MM patients were retrospectively included. During a mean follow-up period of 80 months, 27 patients died, 4 patients lost follow-up for OS, and 4 patients lost follow-up for PFS. Multivariate analysis revealed that increased median ttADC (≥0.620 × 10⁻³ mm²/s) [hazard ratio (HR) = 2.291, P = 0.046, 95 % confidence interval (CI): 1.014–5.175] was independently associated with OS in R-ISS II MM patients. No significant association was observed between the ttADC histogram parameters and PFS.

Conclusion

The median ttADC of whole-body DWI-MRI is an independent predictor of OS in R-ISS II MM patients, suggesting its potential role in further prognostic stratification in this patients' subgroup.

目的：本研究旨在探讨基于全身弥散加权磁共振成像（DWI-MRI）的肿瘤总表观扩散系数（ttADC）直方图分析在修订国际分期系统II期（R-ISS II）多发性骨髓瘤（MM）患者预后分层中的应用。方法：回顾性纳入治疗前接受基线全身MRI检查的R-ISS II型MM患者。使用MR Total Tumor Load软件（Siemens Healthcare, Erlangen, Germany）获得全身DWI-MRI的ttADC直方图参数。记录该队列的总生存期（OS）和无进展生存期（PFS）。采用Cox回归分析评估临床特征和ttADC直方图参数与OS和PFS的关系。结果：回顾性分析了61例R-ISS II型MM患者。在平均80 个月的随访期间，27例患者死亡，4例患者因OS失去随访，4例患者因PFS失去随访。多因素分析显示，中位ttADC升高（≥0.620 × 10-3 mm2/s）[风险比（HR） = 2.291,P = 0.046,95 %可信区间（CI）： 1.014-5.175]与R-ISS II型MM患者的OS独立相关。ttADC直方图参数与PFS之间无显著相关性。结论：全身DWI-MRI的中位ttADC是R-ISS II型MM患者OS的独立预测因子，提示其在该患者亚组进一步预后分层中的潜在作用。

{"title":"Total tumor apparent diffusion coefficient histogram analysis of whole-body DWI-MRI for prognostic stratification in patients with R-ISS stage II multiple myeloma","authors":"Junde Zhou , Qin Wang , Yanting Liu , Lu Zhang , Jiao Li , Shuo Li , Dong Liu , Jinxia Zhu , Robert Grimm , Alto Stemmer , Shuang Xia , Wenyang Huang , Sheng Xie , Haibo Zhang , Jian Li , Huadan Xue , Zhengyu Jin","doi":"10.1016/j.mri.2025.110536","DOIUrl":"10.1016/j.mri.2025.110536","url":null,"abstract":"<div><h3>Purpose</h3><div>This study aimed to explore the utility of total tumor apparent diffusion coefficient (ttADC) histogram analysis based on whole-body diffusion-weighted magnetic resonance imaging (DWI-MRI) for prognostic stratification in patients with Revised International Staging System stage II (R-ISS II) multiple myeloma (MM).</div></div><div><h3>Methods</h3><div>Patients with R-ISS II MM who underwent baseline whole-body MRI prior to treatment were retrospectively enrolled. The ttADC histogram parameters of the whole-body DWI-MRI were obtained using MR Total Tumor Load software (Siemens Healthcare, Erlangen, Germany). The overall survival (OS) and the progression-free survival (PFS) of the cohort was recorded. Cox regression analyses were used to evaluate the clinical features and ttADC histogram parameters for their association with OS and PFS.</div></div><div><h3>Results</h3><div>A total of 61 R-ISS II MM patients were retrospectively included. During a mean follow-up period of 80 months, 27 patients died, 4 patients lost follow-up for OS, and 4 patients lost follow-up for PFS. Multivariate analysis revealed that increased median ttADC (≥0.620 × 10<sup>−3</sup> mm<sup>2</sup>/s) [hazard ratio (HR) = 2.291, <em>P</em> = 0.046, 95 % confidence interval (CI): 1.014–5.175] was independently associated with OS in R-ISS II MM patients. No significant association was observed between the ttADC histogram parameters and PFS.</div></div><div><h3>Conclusion</h3><div>The median ttADC of whole-body DWI-MRI is an independent predictor of OS in R-ISS II MM patients, suggesting its potential role in further prognostic stratification in this patients' subgroup.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"125 ","pages":"Article 110536"},"PeriodicalIF":2.0,"publicationDate":"2025-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145308715","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

Combination of clinicopathological and MRI based radiomics features in predicting homologous recombination repair genes mutations in prostate cancer 结合临床病理和基于MRI的放射组学特征预测前列腺癌同源重组修复基因突变。

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

Magnetic resonance imaging

Pub Date : 2025-10-10 DOI: 10.1016/j.mri.2025.110534

Ruchuan Chen , Guoqing Hu , Bingni Zhou , Hualei Gan , Xiaofeng Liu , Lin Deng , Liangping Zhou , Yajia Gu , Xiaohang Liu

Purpose

To develop Homologous Recombination Repair (HRR) Genes mutations prediction models for prostate cancer using MRI radiomics and clinicopathological features.

Methods

Totally 353 prostate cancer patients (102 with HRR genes mutations) from three centers (center 1: training and internal test cohorts, center 2 and 3: external test cohorts) underwent multiparametric MRI. Each patient's index tumor lesion was delineated on T2-weighted imaging (T2WI), dynamic contrast enhancement (DCE) MRI, diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) images to obtain 428 radiomics features. Features associated with mutations were selected from clinicopathological features using Mann-Whitney U and Logistic regression (LR) test, radiomics features using Least Absolute Shrinkage and Selection Operator. Clinicopathological model was constructed with selected clinicopathological features. Logistic regression (LR), support vector machine (SVM) and linear discriminant analysis (LDA) classifiers were used to construct Radiomics and combined clinicopathological-radiomics models. Predictive efficiencies of models were compared using areas under the receiver operating characteristic curve (AUC).

Results

One clinicopathological and six radiomics features were selected. Radiomics with SVM, LR, LDA and Clinicopathological models achieved AUCs of 0.76, 0.76, 0.76, 0.68 and 0.75, 0.76, 0.67, 0.73 in internal and external test cohort. AUCs of combined clinicopathological-radiomics models with LDA in internal and external test cohort (0.83 and 0.82) were slightly higher than combined models with LR (0.81 and 0.79) and SVM (both 0.80) (P > 0.05), but were significantly higher than radiomics and clinicopathological models in both cohorts (P < 0.05).

Conclusion

LDA classifier incorporating radiomics and clinicopathological features predicting could effectively predict HRR genes mutations in prostate cancer.

目的：建立基于MRI放射组学和临床病理特征的前列腺癌同源重组修复（HRR）基因突变预测模型。方法：来自三个中心（中心1：训练和内部测试队列，中心2和3：外部测试队列）的353例前列腺癌患者（102例HRR基因突变）接受了多参数MRI检查。通过t2加权成像（T2WI）、动态对比增强（DCE） MRI、弥散加权成像（DWI）和表观弥散系数（ADC）图像描绘每位患者的指数肿瘤病变，获得428个放射组学特征。使用Mann-Whitney U和Logistic回归（LR）检验从临床病理特征中选择与突变相关的特征，使用最小绝对收缩和选择算子从放射组学特征中选择与突变相关的特征。选取临床病理特征建立临床病理模型。采用Logistic回归（LR）、支持向量机（SVM）和线性判别分析（LDA）分类器构建放射组学和临床病理-放射组学联合模型。使用受试者工作特征曲线下面积（AUC）比较模型的预测效率。结果：选取1例临床病理特征和6例放射组学特征。使用SVM、LR、LDA和临床病理模型的放射组学在内外测试队列中的auc分别为0.76、0.76、0.76、0.68和0.75、0.76、0.67、0.73。LDA联合临床病理-放射组学模型的auc在内外检测队列中分别为0.83和0.82，略高于LR联合模型（0.81和0.79）和SVM联合模型（均为0.80）（P > 0.05），但在两个队列中均显著高于放射组学和临床病理模型（P ）。结论：结合放射组学和临床病理特征预测的LDA分类器可有效预测前列腺癌HRR基因突变。

{"title":"Combination of clinicopathological and MRI based radiomics features in predicting homologous recombination repair genes mutations in prostate cancer","authors":"Ruchuan Chen , Guoqing Hu , Bingni Zhou , Hualei Gan , Xiaofeng Liu , Lin Deng , Liangping Zhou , Yajia Gu , Xiaohang Liu","doi":"10.1016/j.mri.2025.110534","DOIUrl":"10.1016/j.mri.2025.110534","url":null,"abstract":"<div><h3>Purpose</h3><div>To develop Homologous Recombination Repair (HRR) Genes mutations prediction models for prostate cancer using MRI radiomics and clinicopathological features.</div></div><div><h3>Methods</h3><div>Totally 353 prostate cancer patients (102 with HRR genes mutations) from three centers (center 1: training and internal test cohorts, center 2 and 3: external test cohorts) underwent multiparametric MRI. Each patient's index tumor lesion was delineated on T2-weighted imaging (T2WI), dynamic contrast enhancement (DCE) MRI, diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) images to obtain 428 radiomics features. Features associated with mutations were selected from clinicopathological features using Mann-Whitney U and Logistic regression (LR) test, radiomics features using Least Absolute Shrinkage and Selection Operator. Clinicopathological model was constructed with selected clinicopathological features. Logistic regression (LR), support vector machine (SVM) and linear discriminant analysis (LDA) classifiers were used to construct Radiomics and combined clinicopathological-radiomics models. Predictive efficiencies of models were compared using areas under the receiver operating characteristic curve (AUC).</div></div><div><h3>Results</h3><div>One clinicopathological and six radiomics features were selected. Radiomics with SVM, LR, LDA and Clinicopathological models achieved AUCs of 0.76, 0.76, 0.76, 0.68 and 0.75, 0.76, 0.67, 0.73 in internal and external test cohort. AUCs of combined clinicopathological-radiomics models with LDA in internal and external test cohort (0.83 and 0.82) were slightly higher than combined models with LR (0.81 and 0.79) and SVM (both 0.80) (<em>P</em> > 0.05), but were significantly higher than radiomics and clinicopathological models in both cohorts (<em>P</em> < 0.05).</div></div><div><h3>Conclusion</h3><div>LDA classifier incorporating radiomics and clinicopathological features predicting could effectively predict HRR genes mutations in prostate cancer.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"124 ","pages":"Article 110534"},"PeriodicalIF":2.0,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145275099","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