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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 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。
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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 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。
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引用次数: 0
A Bayesian CAIPIVAT approach with through-plane acceleration to enhance efficiency of simultaneously encoded slice acquisition in FMRI 一种通过平面加速的贝叶斯CAIPIVAT方法提高FMRI同步编码切片采集效率。
IF 2 4区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Pub Date : 2025-10-09 DOI: 10.1016/j.mri.2025.110540
Ke Xu, Daniel B. Rowe
FMRI has been a safe medical imaging tool to study brain function by demonstrating the spatial and temporal changes in brain metabolism in recent decades. To capture brain functionality more efficiently, efforts focus on accelerating image acquisition acquired per unit of time that create each volume image without losing full anatomical structure. The Simultaneous Multi-Slice (SMS) technique provides a reconstruction method where multiple slices are acquired and aliased concurrently. Traditional imaging techniques such as SENSE and GRAPPA can reconstruct an image from less measured data but have their drawbacks. The Controlled Aliasing in Parallel Imaging (CAIPI) and view angle tilting (VAT) techniques achieve slice-wise image shift to decrease the influence of the geometry factor (g-factor) of coil sensitivities and prevent the singular problem of the design matrix. In this paper, a Bayesian CAIPIVAT approach for multi-coil separation of parallel encoded complex-valued slices (mSPECS-CAIPIVAT) with a novel SMS approach is presented and combined with the Hadamard phase-encoding method for image separation. Our proposed approach was applied to simulation and experimental studies showing a decrease in the influence of the g-factor while increasing the brain activation detection rate. The signal-to-noise ratio and the contrast-to-noise ratio are also improved by our approach.
近几十年来,功能磁共振成像(FMRI)通过显示脑代谢的时空变化,已成为研究脑功能的一种安全的医学成像工具。为了更有效地捕捉大脑功能,人们致力于在不丢失完整解剖结构的情况下,加快每单位时间内的图像采集速度。同时多片(SMS)技术提供了一种同时获取和混叠多个片的重建方法。传统的成像技术,如SENSE和GRAPPA可以从较少测量的数据重建图像,但有其缺点。平行成像中的可控混叠(CAIPI)和视角倾斜(VAT)技术实现了逐片图像移位,以减少线圈灵敏度的几何因子(g因子)的影响,防止设计矩阵的奇异性问题。本文提出了一种新的基于SMS的并行编码复值切片多线圈分离的贝叶斯CAIPIVAT方法,并将其与Hadamard相位编码方法相结合进行图像分离。我们提出的方法应用于模拟和实验研究,表明g因子的影响降低,同时提高了脑激活检测率。该方法还提高了信号的信噪比和信噪比。
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引用次数: 0
Correcting unwanted diffusion weighting in diffusion-weighted-STEAM sequence for time-dependent diffusion kurtosis imaging 校正时间相关扩散峰度成像中扩散加权- steam序列中不需要的扩散加权
IF 2 4区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Pub Date : 2025-10-08 DOI: 10.1016/j.mri.2025.110535
Qinfeng Zhu , Ruicheng Ba , Zuozhen Cao , Yao Shen , Haotian Li , Yi-Cheng Hsu , Xu Yan , Dan Wu

Purpose

This study proposes an optimized acquisition protocol to minimize the unwanted diffusion weighting in DW-STEAM and facilitate time-dependent diffusion kurtosis imaging (tDKI).

Methods

We first corrected the diffusion-direction-dependent shift by optimizing the diffusion gradient amplitude. We then proposed to use low-b-value in the reference image, instead of the conventional non-diffusion-weighted (b0) acquisition, and removed the crusher gradients. The tDKI measurements from the proposed strategy were compared with conventional DWIs that included crushers in the b0 image, in a water phantom and in healthy adults (n = 8) on 3 T, and the water exchange time (τex) was calculated from the tDKI measurements. The optimal strategy was tested in five ex vivo human brains, and the results were compared with in vivo data.

Results

Neglecting the diffusion weighting in b0 images introduced an artificial time dependence in the apparent diffusivity of the water phantom, and resulted in elevated estimates of water exchange time (τex) in in the in vivo data. Additionally, the AIC indicated that, even when diffusion weighting in the b0 images was accounted for, the kurtosis estimation remained less stable in the in vivo than with the crusher-free approach. In contrast, using low-b-value images as reference measurements yielded reasonable tDKI estimates, with τex ranging from 15 to 40 ms for gray matter in vivo and from 20 to 60 ms for gray matter ex vivo.

Conclusions

The optimized DW-STEAM acquisition eliminated artificial diffusion-time dependence, enabling the acquisition of accurate tDKI data for mapping structural morphology and transmembrane permeability.
本研究提出了一种优化的采集方案,以最大限度地减少DW-STEAM中不必要的扩散权重,并促进时间相关扩散峰度成像(tDKI)。方法首先通过优化扩散梯度振幅修正扩散方向相关偏移。然后,我们提出在参考图像中使用低b值,而不是传统的非扩散加权(b0)采集,并去除破碎机梯度。将该策略的tDKI测量值与常规dwi进行比较,常规dwi包括b0图像、水幻影和健康成人(n = 8)在3 T中的破碎机,并根据tDKI测量值计算水交换时间(τex)。该优化策略在5个离体人脑中进行了测试,并与体内数据进行了比较。结果忽略b0图像中的扩散权重会导致水影表观扩散率产生人为的时间依赖性,从而导致体内数据中水交换时间(τex)的估计升高。此外,AIC表明,即使考虑了b0图像中的扩散权重,在体内的峰度估计仍然不如无破碎方法稳定。相比之下,使用低b值图像作为参考测量得到了合理的tDKI估计,体内灰质的τex范围为15至40 ms,体外灰质的τex范围为20至60 ms。结论优化后的DW-STEAM采集消除了人为的扩散时间依赖,能够获得准确的tDKI数据,用于绘制结构形态和跨膜渗透率。
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引用次数: 0
Sensitivity of quantitative diffusion MRI tractography and microstructure to anisotropic spatial sampling 定量扩散MRI示踪和微观结构对各向异性空间采样的敏感性。
IF 2 4区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Pub Date : 2025-10-06 DOI: 10.1016/j.mri.2025.110539
Elyssa M. McMaster , Nancy R. Newlin , Chloe Cho , Gaurav Rudravaram , Adam M. Saunders , Aravind R. Krishnan , Lucas W. Remedios , Michael E. Kim , Hanliang Xu , Kurt G. Schilling , François Rheault , Laurie E. Cutting , Bennett A. Landman

Purpose

Diffusion weighted MRI (dMRI) and its models of neural structure provide insight into human brain organization and variations in white matter. A recent study by McMaster, et al. showed that complex graph measures of the connectome, the graphical representation of a tractogram, vary with spatial sampling changes, but biases introduced by anisotropic voxels in the process have not been well characterized. This study uses microstructural measures (fractional anisotropy and mean diffusivity) and white matter bundle properties (bundle volume, length, and surface area) to further understand the effect of anisotropic voxels on microstructure and tractography.

Methods

The statistical significance of the selected measures derived from dMRI data were assessed by comparing three white matter bundles at different spatial resolutions with 44 subjects from the Human Connectome Project – Young Adult dataset scan/rescan data using the Wilcoxon Signed-Rank test. The original isotropic resolution (1.25 mm isotropic) was explored with 6 anisotropic resolutions with 0.25 mm incremental steps in the z dimension. Then, all generated resolutions were upsampled to 1.25 mm isotropic and 1 mm isotropic.

Results

There were statistically significant differences between at least one microstructural and one bundle measure at every resolution (p0.05, corrected for multiple comparisons). Cohen's d coefficient evaluated the effect size of anisotropic voxels on microstructure and tractography.

Conclusion

Fractional anisotropy and mean diffusivity cannot be recovered with basic up-sampling from low quality data with gold-standard data with the methods selected for this study. However, the bundle measures across our selected regions of interest become more repeatable when voxels are resampled to 1 mm isotropic.
目的:弥散加权MRI (Diffusion weighted MRI, dMRI)及其神经结构模型提供了对人脑组织和白质变化的深入了解。麦克马斯特等人最近的一项研究表明,连接体的复杂图形测量(图的图形表示)随空间采样变化而变化,但各向异性体素在此过程中引入的偏差尚未得到很好的表征。本研究通过显微结构测量(分数各向异性和平均扩散率)和白质束特性(束体积、长度和表面积)来进一步了解各向异性体素对微结构和束束成像的影响。方法:采用Wilcoxon sign - rank检验,将来自人类连接组项目-年轻人数据集扫描/重新扫描数据的44名受试者在不同空间分辨率下的三个白质束进行比较,以评估从dMRI数据中获得的选定测量的统计显著性。原始各向同性分辨率(1.25 mm各向同性)以6个各向异性分辨率(z维增量为0.25 mm)进行探索。然后,所有生成的分辨率上采样到1.25 mm各向同性和1 mm各向同性。结果:各分辨率下至少一项显微结构测量与一项束测量差异有统计学意义(p≤0.05,经多次比较校正)。Cohen’s d系数评估了各向异性体素对微观结构和示踪学的影响大小。结论:采用本研究选择的方法,用金标准数据对低质量数据进行基本上采样,不能恢复分数各向异性和平均扩散率。然而,当体素被重新采样到1 mm各向同性时,我们所选择的感兴趣区域的束测量变得更加可重复。
{"title":"Sensitivity of quantitative diffusion MRI tractography and microstructure to anisotropic spatial sampling","authors":"Elyssa M. McMaster ,&nbsp;Nancy R. Newlin ,&nbsp;Chloe Cho ,&nbsp;Gaurav Rudravaram ,&nbsp;Adam M. Saunders ,&nbsp;Aravind R. Krishnan ,&nbsp;Lucas W. Remedios ,&nbsp;Michael E. Kim ,&nbsp;Hanliang Xu ,&nbsp;Kurt G. Schilling ,&nbsp;François Rheault ,&nbsp;Laurie E. Cutting ,&nbsp;Bennett A. Landman","doi":"10.1016/j.mri.2025.110539","DOIUrl":"10.1016/j.mri.2025.110539","url":null,"abstract":"<div><h3>Purpose</h3><div>Diffusion weighted MRI (dMRI) and its models of neural structure provide insight into human brain organization and variations in white matter. A recent study by McMaster, et al. showed that complex graph measures of the connectome, the graphical representation of a tractogram, vary with spatial sampling changes, but biases introduced by anisotropic voxels in the process have not been well characterized. This study uses microstructural measures (fractional anisotropy and mean diffusivity) and white matter bundle properties (bundle volume, length, and surface area) to further understand the effect of anisotropic voxels on microstructure and tractography.</div></div><div><h3>Methods</h3><div>The statistical significance of the selected measures derived from dMRI data were assessed by comparing three white matter bundles at different spatial resolutions with 44 subjects from the Human Connectome Project – Young Adult dataset scan/rescan data using the Wilcoxon Signed-Rank test. The original isotropic resolution (1.25 mm isotropic) was explored with 6 anisotropic resolutions with 0.25 mm incremental steps in the <em>z</em> dimension. Then, all generated resolutions were upsampled to 1.25 mm isotropic and 1 mm isotropic.</div></div><div><h3>Results</h3><div>There were statistically significant differences between at least one microstructural and one bundle measure at every resolution (<span><math><mi>p</mi><mo>≤</mo><mn>0.05</mn></math></span>, corrected for multiple comparisons). Cohen's <span><math><mi>d</mi></math></span> coefficient evaluated the effect size of anisotropic voxels on microstructure and tractography.</div></div><div><h3>Conclusion</h3><div>Fractional anisotropy and mean diffusivity cannot be recovered with basic up-sampling from low quality data with gold-standard data with the methods selected for this study. However, the bundle measures across our selected regions of interest become more repeatable when voxels are resampled to 1 mm isotropic.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"124 ","pages":"Article 110539"},"PeriodicalIF":2.0,"publicationDate":"2025-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145244670","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
Role of large language models for etiological classification of brain stroke based on MRI brain reports: a feasibility study 基于MRI脑报告的大语言模型在脑卒中病因分类中的作用:可行性研究。
IF 2 4区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Pub Date : 2025-10-06 DOI: 10.1016/j.mri.2025.110538
Jorge Escartín , Pilar López-Úbeda , Teodoro Martín-Noguerol , Antonio Luna

Purpose

Ischemic stroke, a leading cause of global disability and mortality, demands precise etiological classification for effective management. The variability in the use of existing stroke classification systems, along with the challenges in manual etiological labeling from brain MRI radiological reports, calls for an innovative approach. This study aims to develop and evaluate a Natural Language Processing (NLP) algorithm using transformer-based models for the extraction and classification of ischemic stroke types from MRI reports, enhancing diagnostic efficiency and stroke management.

Methods

We built a dataset comprising 635 brain MRI reports, annotated for four distinct ischemic stroke types. All were clinically consistent with focal neurologic impairment due to stroke. The study involved evaluating two pre-trained models BERT (Bert clinical and Beto) and two models RoBERTa (Roberta clinical trials and Roberta biomedical), focusing on their ability to accurately classify stroke subtypes.

Results

The Roberta biomedical model emerged as the most effective, demonstrating superior performance with an accuracy of 76.7 % with statistically significant results. This model also achieved the highest precision, recall, and F1 scores across all stroke types, indicating its robustness in stroke subtype classification.

Conclusion

The study highlights the potential of NLP algorithms in automating stroke classification from MRI reports, which could significantly aid in diagnostic processes and streamline stroke management strategies.
目的:缺血性脑卒中是全球致残和死亡的主要原因,需要精确的病因分类以进行有效的治疗。现有脑卒中分类系统使用的可变性,以及从脑MRI放射学报告中手动标记病因的挑战,需要一种创新的方法。本研究旨在开发和评估一种基于变压器模型的自然语言处理(NLP)算法,用于从MRI报告中提取和分类缺血性卒中类型,提高诊断效率和卒中管理。方法:我们建立了一个包含635份脑MRI报告的数据集,对四种不同的缺血性卒中类型进行了注释。所有患者均符合脑卒中引起的局灶性神经损伤。该研究包括评估两个预训练模型BERT (BERT临床和Beto)和两个模型RoBERTa (RoBERTa临床试验和RoBERTa生物医学),重点关注它们准确分类中风亚型的能力。结果:Roberta生物医学模型最有效,准确率为76.7 %,具有统计学意义。该模型在所有脑卒中类型中也取得了最高的准确率、召回率和F1分数,表明其在脑卒中亚型分类中的稳健性。结论:该研究强调了NLP算法在从MRI报告中自动分类脑卒中方面的潜力,这可以显著帮助诊断过程和简化脑卒中管理策略。
{"title":"Role of large language models for etiological classification of brain stroke based on MRI brain reports: a feasibility study","authors":"Jorge Escartín ,&nbsp;Pilar López-Úbeda ,&nbsp;Teodoro Martín-Noguerol ,&nbsp;Antonio Luna","doi":"10.1016/j.mri.2025.110538","DOIUrl":"10.1016/j.mri.2025.110538","url":null,"abstract":"<div><h3>Purpose</h3><div>Ischemic stroke, a leading cause of global disability and mortality, demands precise etiological classification for effective management. The variability in the use of existing stroke classification systems, along with the challenges in manual etiological labeling from brain MRI radiological reports, calls for an innovative approach. This study aims to develop and evaluate a Natural Language Processing (NLP) algorithm using transformer-based models for the extraction and classification of ischemic stroke types from MRI reports, enhancing diagnostic efficiency and stroke management.</div></div><div><h3>Methods</h3><div>We built a dataset comprising 635 brain MRI reports, annotated for four distinct ischemic stroke types. All were clinically consistent with focal neurologic impairment due to stroke. The study involved evaluating two pre-trained models BERT (Bert clinical and Beto) and two models RoBERTa (Roberta clinical trials and Roberta biomedical), focusing on their ability to accurately classify stroke subtypes.</div></div><div><h3>Results</h3><div>The Roberta biomedical model emerged as the most effective, demonstrating superior performance with an accuracy of 76.7 % with statistically significant results. This model also achieved the highest precision, recall, and F1 scores across all stroke types, indicating its robustness in stroke subtype classification.</div></div><div><h3>Conclusion</h3><div>The study highlights the potential of NLP algorithms in automating stroke classification from MRI reports, which could significantly aid in diagnostic processes and streamline stroke management strategies.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"124 ","pages":"Article 110538"},"PeriodicalIF":2.0,"publicationDate":"2025-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145244717","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
Combined model based on multimodal imaging and clinical pathology: A new pathway to assess hypoxia status and HIF-1α expression in breast cancer 基于多模态成像和临床病理的联合模型:评估乳腺癌缺氧状态和HIF-1α表达的新途径。
IF 2 4区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Pub Date : 2025-10-03 DOI: 10.1016/j.mri.2025.110537
Zhiyuan He , Yiwen Wang , Yunxi Li , Laimin Zhu , Yueqin Chen , Ning Mao , Wenwen Zhao , Xiuzheng Yue , Yufei Xue , Shuzhen Wang , Weiwei Wang , Zhanguo Sun

Purpose

To develop and validate a combined model integrating multimodal magnetic resonance imaging (MRI) and clinical-pathological parameters to assess hypoxia status and hypoxia-inducible factor-1α (HIF-1α) expression in mass-like breast cancer.

Methods

This retrospective cohort study included 197 patients with mass-like breast cancer from two medical centers, who were divided into a training set (n = 104), an internal validation set (n = 45), and an external validation set (n = 48). Clinical-pathological and multimodal MRI parameters were analyzed using histopathology as the reference. The combined model was developed through logistic and least absolute shrinkage and selection operator (LASSO) regression analysis to identify features, and visualized using nomograms.

Results

Axillary lymph node (ALN) metastasis, time-intensity curve (TIC) type, mean diffusivity (MD), volumetric transfer constant (Ktrans), and rate constant (Kep) were selected to construct the combined model. The diagnostic performance of the combined model [area under the curve (AUC) = 0.967, 95 % CI: 0.913–0.992] (training), was significantly better than that of other individual models (P < 0.001). This performance was replicated in internal (AUC= 0.907) and external (AUC = 0.928) validation sets. The nomogram of the combined model showed excellent calibration (Hosmer-Lemeshow P = 0.653) and the highest net benefit across threshold probabilities in the decision curve analysis (DCA). Tumors with high HIF-1α expression exhibited higher ALN metastasis, histological grade, unclear margins, Type 3 TIC, and elevated Ktrans, Kep, and MK, but reduced MD values.

Conclusions

The combined model (ALN + TIC + MD + Ktrans + Kep) shows potential as a reliable tool for predicting HIF-1α expression levels in mass-like breast cancer.
目的:建立并验证一种结合多模态磁共振成像(MRI)和临床病理参数的联合模型,以评估肿块样乳腺癌的缺氧状态和缺氧诱导因子-1α (HIF-1α)的表达。方法:本回顾性队列研究纳入来自两个医疗中心的197例肿块样乳腺癌患者,将其分为训练集(n = 104)、内部验证集(n = 45)和外部验证集(n = 48)。以组织病理学为参考,分析临床病理及多模态MRI参数。组合模型通过逻辑、最小绝对收缩和选择算子(LASSO)回归分析来识别特征,并使用模态图进行可视化。结果:选择腋窝淋巴结(ALN)转移、时间-强度曲线(TIC)类型、平均扩散系数(MD)、体积转移常数(Ktrans)和速率常数(Kep)构建联合模型。联合模型[曲线下面积(AUC) = 0.967,95 % CI: 0.913-0.992](训练)的诊断性能显著优于其他单独模型(P trans、Kep和MK),但降低了MD值。结论:联合模型(ALN + TIC + MD + Ktrans + Kep)有望成为预测肿块样乳腺癌中HIF-1α表达水平的可靠工具。
{"title":"Combined model based on multimodal imaging and clinical pathology: A new pathway to assess hypoxia status and HIF-1α expression in breast cancer","authors":"Zhiyuan He ,&nbsp;Yiwen Wang ,&nbsp;Yunxi Li ,&nbsp;Laimin Zhu ,&nbsp;Yueqin Chen ,&nbsp;Ning Mao ,&nbsp;Wenwen Zhao ,&nbsp;Xiuzheng Yue ,&nbsp;Yufei Xue ,&nbsp;Shuzhen Wang ,&nbsp;Weiwei Wang ,&nbsp;Zhanguo Sun","doi":"10.1016/j.mri.2025.110537","DOIUrl":"10.1016/j.mri.2025.110537","url":null,"abstract":"<div><h3>Purpose</h3><div>To develop and validate a combined model integrating multimodal magnetic resonance imaging (MRI) and clinical-pathological parameters to assess hypoxia status and hypoxia-inducible factor-1α (HIF-1α) expression in mass-like breast cancer.</div></div><div><h3>Methods</h3><div>This retrospective cohort study included 197 patients with mass-like breast cancer from two medical centers, who were divided into a training set (<em>n</em> = 104), an internal validation set (<em>n</em> = 45), and an external validation set (<em>n</em> = 48). Clinical-pathological and multimodal MRI parameters were analyzed using histopathology as the reference. The combined model was developed through logistic and least absolute shrinkage and selection operator (LASSO) regression analysis to identify features, and visualized using nomograms.</div></div><div><h3>Results</h3><div>Axillary lymph node (ALN) metastasis, time-intensity curve (TIC) type, mean diffusivity (MD), volumetric transfer constant (K<sup>trans</sup>), and rate constant (Kep) were selected to construct the combined model. The diagnostic performance of the combined model [area under the curve (AUC) = 0.967, 95 % CI: 0.913–0.992] (training), was significantly better than that of other individual models (<em>P</em> &lt; 0.001). This performance was replicated in internal (AUC= 0.907) and external (AUC = 0.928) validation sets. The nomogram of the combined model showed excellent calibration (Hosmer-Lemeshow <em>P</em> = 0.653) and the highest net benefit across threshold probabilities in the decision curve analysis (DCA). Tumors with high HIF-1α expression exhibited higher ALN metastasis, histological grade, unclear margins, Type 3 TIC, and elevated K<sup>trans</sup>, Kep, and MK, but reduced MD values.</div></div><div><h3>Conclusions</h3><div>The combined model (ALN + TIC + MD + K<sup>trans</sup> + Kep) shows potential as a reliable tool for predicting HIF-1α expression levels in mass-like breast cancer.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"124 ","pages":"Article 110537"},"PeriodicalIF":2.0,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145232921","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
Optimizing MPRAGE for enhanced blood suppression and intraplaque hemorrhage detection in carotid artery imaging 优化MPRAGE在颈动脉成像中增强血液抑制和斑块内出血检测。
IF 2 4区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Pub Date : 2025-09-30 DOI: 10.1016/j.mri.2025.110531
Seong-Eun Kim , John A. Roberts , J. Rock Hadley , J. Scott McNally , Gerald S. Treiman , Yibin Xie , Debiao Li , Kim-Lien Nguyen , Dimitrios Mitsouras , Jonas Schollenberger , David Saloner , Arunbalaji Pugazhendhi , Kevin J. Johnson , Maria Altbach , Herman Morris , Kevin DeMarco , Vibhas Deshpande , Pedro Itriago-Leon , Dennis L. Parker

Purpose

This study aims to optimize the Magnetization Prepared Rapid Acquisition Gradient Echo (MPRAGE) technique to improve the accuracy of intraplaque hemorrhage (IPH) detection in carotid diseases and enhance reliability for clinical use, addressing the challenge of inconsistent blood suppression observed in commonly used clinical protocols.

Methods

Bloch equation simulations were used to evaluate the effects of inversion time and flip angle on blood suppression and tissue contrast. The optimized parameters were implemented on a clinical 3 T scanner and tested in four subjects. Quantitative measures included blood–muscle contrast and contrast-to-noise ratios (CNR) for lumen–wall and lumen–IPH. Imaging was performed in 21 patients with carotid artery disease, two MPRAGE acquisitions were performed per patient: (1) at the magnet isocenter with the standard IR pulse, and (2) at a 50-mm shifted position toward the heart with the wideband IR pulse. Qualitative image quality was evaluated independently by two neuroradiologists using a predefined 4-point scale (1 = poor, 4 = excellent) for blood suppression, vessel wall clarity, motion artifacts, and IPH visualization, in addition to quantitative SNR and CNR measurements.

Results

The optimized MPRAGE sequence demonstrated significantly improved blood suppression, with blood–muscle contrast increasing from 0.42 ± 0.08 to 0.61 ± 0.07 (p = 0.002). Lumen–wall CNR increased from 15.2 ± 3.4 to 22.8 ± 4.1 (p = 0.01), and lumen–IPH CNR increased from 18.7 ± 5.2 to 26.3 ± 6.0 (p = 0.004). These improvements enhanced vessel wall delineation and IPH conspicuity.

Conclusion

Optimization of MPRAGE parameters enhances blood suppression and contrast, providing improved visualization of the carotid vessel wall and more reliable detection of IPH. This approach may increase the diagnostic accuracy of carotid plaque imaging.
目的:本研究旨在优化磁化制备快速采集梯度回波(MPRAGE)技术,以提高颈动脉疾病斑块内出血(IPH)检测的准确性,提高临床使用的可靠性,解决常用临床方案中观察到的血液抑制不一致的挑战。方法:采用Bloch方程模拟评价倒置时间和翻转角度对血液抑制和组织造影的影响。优化后的参数在临床3 T扫描仪上实现,并在4名受试者中进行了测试。定量测量包括血肌对比和管壁和管腔iph的噪声对比比(CNR)。对21例颈动脉疾病患者进行影像学检查,每例患者进行两次MPRAGE采集:(1)在磁体等心处进行标准IR脉冲采集,(2)在向心脏方向偏移50 mm处进行宽带IR脉冲采集。定性图像质量由两名神经放射学家使用预定义的4分制(1 = 差,4 = 优)独立评估,包括血压抑制、血管壁清晰度、运动伪影和IPH可视化,以及定量信噪比和CNR测量。结果:优化后的MPRAGE序列明显改善了血液抑制效果,血肌对比从0.42 ± 0.08增加到0.61 ± 0.07 (p = 0.002)。Lumen-wall CNR增加从15.2 ± 3.4到22.8 ± 4.1 (p = 0.01),和lumen-IPH CNR增加从18.7 ± 5.2到26.3 ±6.0 (p = 0.004)。这些改善增强了血管壁的描绘和IPH的显著性。结论:优化MPRAGE参数可增强血液抑制和造影,改善颈动脉血管壁的可视化,更可靠地检测IPH。该方法可提高颈动脉斑块成像的诊断准确性。
{"title":"Optimizing MPRAGE for enhanced blood suppression and intraplaque hemorrhage detection in carotid artery imaging","authors":"Seong-Eun Kim ,&nbsp;John A. Roberts ,&nbsp;J. Rock Hadley ,&nbsp;J. Scott McNally ,&nbsp;Gerald S. Treiman ,&nbsp;Yibin Xie ,&nbsp;Debiao Li ,&nbsp;Kim-Lien Nguyen ,&nbsp;Dimitrios Mitsouras ,&nbsp;Jonas Schollenberger ,&nbsp;David Saloner ,&nbsp;Arunbalaji Pugazhendhi ,&nbsp;Kevin J. Johnson ,&nbsp;Maria Altbach ,&nbsp;Herman Morris ,&nbsp;Kevin DeMarco ,&nbsp;Vibhas Deshpande ,&nbsp;Pedro Itriago-Leon ,&nbsp;Dennis L. Parker","doi":"10.1016/j.mri.2025.110531","DOIUrl":"10.1016/j.mri.2025.110531","url":null,"abstract":"<div><h3>Purpose</h3><div>This study aims to optimize the Magnetization Prepared Rapid Acquisition Gradient Echo (MPRAGE) technique to improve the accuracy of intraplaque hemorrhage (IPH) detection in carotid diseases and enhance reliability for clinical use, addressing the challenge of inconsistent blood suppression observed in commonly used clinical protocols.</div></div><div><h3>Methods</h3><div>Bloch equation simulations were used to evaluate the effects of inversion time and flip angle on blood suppression and tissue contrast. The optimized parameters were implemented on a clinical 3 T scanner and tested in four subjects. Quantitative measures included blood–muscle contrast and contrast-to-noise ratios (CNR) for lumen–wall and lumen–IPH. Imaging was performed in 21 patients with carotid artery disease, two MPRAGE acquisitions were performed per patient: (1) at the magnet isocenter with the standard IR pulse, and (2) at a 50-mm shifted position toward the heart with the wideband IR pulse. Qualitative image quality was evaluated independently by two neuroradiologists using a predefined 4-point scale (1 = poor, 4 = excellent) for blood suppression, vessel wall clarity, motion artifacts, and IPH visualization, in addition to quantitative SNR and CNR measurements.</div></div><div><h3>Results</h3><div>The optimized MPRAGE sequence demonstrated significantly improved blood suppression, with blood–muscle contrast increasing from 0.42 ± 0.08 to 0.61 ± 0.07 (<em>p</em> = 0.002). Lumen–wall CNR increased from 15.2 ± 3.4 to 22.8 ± 4.1 (<em>p</em> = 0.01), and lumen–IPH CNR increased from 18.7 ± 5.2 to 26.3 ± 6.0 (<em>p</em> = 0.004). These improvements enhanced vessel wall delineation and IPH conspicuity.</div></div><div><h3>Conclusion</h3><div>Optimization of MPRAGE parameters enhances blood suppression and contrast, providing improved visualization of the carotid vessel wall and more reliable detection of IPH. This approach may increase the diagnostic accuracy of carotid plaque imaging.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"124 ","pages":"Article 110531"},"PeriodicalIF":2.0,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145213152","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
PHASE: Personalized Head-based Automatic Simulation for Electromagnetic properties in 7T MRI 阶段:7T MRI电磁特性的个性化头部自动仿真。
IF 2 4区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Pub Date : 2025-09-25 DOI: 10.1016/j.mri.2025.110532
Zhengyi Lu , Hao Liang , Ming Lu , Dann Martin , Benjamin M. Hardy , Benoit M. Dawant , Xiao Wang , Xinqiang Yan , Yuankai Huo
Accurate and individualized human head models are becoming increasingly important for electromagnetic (EM) simulations. These simulations depend on precise anatomical representations to realistically model electric and magnetic field distributions, particularly when evaluating Specific Absorption Rate (SAR) within safety guidelines. State of the art simulations use the Virtual Population due to limited public resources and the impracticality of manually annotating patient data at scale. This paper introduces Personalized Head-based Automatic Simulation for EM properties (PHASE), an automated open-source toolbox that generates high-resolution, patient-specific head models for EM simulations using paired T1-weighted (T1w) magnetic resonance imaging (MRI) and computed tomography (CT) scans with 14 tissue labels. To evaluate the performance of PHASE models, we conduct semi-automated segmentation and EM simulations on 15 real human patients, serving as the gold standard reference. The PHASE model achieved comparable global SAR and localized SAR averaged over 10 grams of tissue (SAR-10g), demonstrating its potential as a promising tool for generating large-scale human model datasets in the future. The code and models of PHASE toolbox have been made publicly available: https://github.com/hrlblab/PHASE.
精确和个性化的人体头部模型对于电磁仿真变得越来越重要。这些模拟依赖于精确的解剖表征来真实地模拟电场和磁场分布,特别是在评估安全指南内的比吸收率(SAR)时。由于有限的公共资源和大规模手动注释患者数据的不切实际,最先进的模拟使用虚拟人口。本文介绍了基于个性化头部的电磁特性自动仿真(PHASE),这是一个自动化的开源工具箱,可以使用配对t1加权(T1w)磁共振成像(MRI)和计算机断层扫描(CT)扫描14个组织标签,为电磁仿真生成高分辨率,患者特定的头部模型。为了评估PHASE模型的性能,我们对15名真实的人类患者进行了半自动分割和EM模拟,作为金标准参考。PHASE模型实现了可比较的全球SAR和局部SAR,平均超过10克组织(SAR-10克),显示了其作为未来生成大规模人体模型数据集的有前途的工具的潜力。PHASE工具箱的代码和模型已经公开提供:https://github.com/hrlblab/PHASE。
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引用次数: 0
Coherent flow effects on IVIM-based perfusion measurements: A phantom study in 3 T 相干血流对ivim灌注测量的影响:3 T的幻像研究。
IF 2 4区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Pub Date : 2025-09-23 DOI: 10.1016/j.mri.2025.110533
Kamil Lipiński , Grzegorz Domański , Piotr Bogorodzki
Quantitative, non-invasive measurement of perfusion remains a challenge in MRI. The Intravoxel Incoherent Motion (IVIM) technique, based on Diffusion-Weighted Imaging (DWI), offers a method to estimate perfusion at the sub-voxel level by modeling blood flow as a pseudo-diffusive process within a microvascular network. Key IVIM-derived parameters include the perfusion fraction (f) and the pseudo-diffusion coefficient (D*). While under specific structural assumptions, IVIM can be used to estimate Cerebral Blood Flow (CBF), direct conversions from IVIM metrics to CBF are rarely validated. This study investigates the accuracy of the IVIM-based perfusion measures, exploring coherent flow influence on signal from voxel. To assess the relation between flow (ground truth CBF), IVIM parameters, and calculated CBF, a phantom, composed of agarose gel and tubes mimicking arterioles with regulated flow velocity, was constructed. Thus, a signal fraction from the “fast” compartment, described by D* in the IVIM model, is represented by flow in tubes occupying a fixed fraction of the imaged voxel, simulating desired Cerebral Blood Volume (CBV) and CBF values. The phantom was scanned using IVIM-optimized DWI protocol, and data were processed for the IVIM measures. Besides IVIM, we also propose a model based on extended Bloch-Torrey equations with coherent flow term. Results demonstrate that IVIM can yield reasonable estimates of CBF and CBV within physiologically relevant flow ranges (0.5–2 mm/s) observed in the brain vasculature. However, a consistent overestimation of flow (up to 200 %) was obscerved at higher velocities, especially in arterial or vein-like flow conditions.
定量、无创的灌注测量在MRI中仍然是一个挑战。基于弥散加权成像(DWI)的体素内非相干运动(IVIM)技术,通过将血流建模为微血管网络中的伪弥散过程,提供了一种在亚体素水平估计灌注的方法。关键的ivim衍生参数包括灌注分数(f)和伪扩散系数(D*)。虽然在特定的结构假设下,IVIM可用于估计脑血流量(CBF),但从IVIM指标到CBF的直接转换很少得到验证。本研究探讨了基于ivim的灌注测量的准确性,探讨了相干流对体素信号的影响。为了评估流量(地面真实CBF)、IVIM参数和计算CBF之间的关系,构建了一个由琼脂糖凝胶和管组成的模拟小动脉的模型,并调节流速。因此,IVIM模型中用D*表示的“快速”隔室的信号分数,由占据成像体素的固定分数的管中的流量表示,模拟所需的脑血容量(CBV)和CBF值。使用IVIM优化的DWI协议扫描假体,并处理数据以进行IVIM测量。除了IVIM,我们还提出了一个基于扩展Bloch-Torrey方程的模型。结果表明,IVIM可以在生理相关的血流范围(0.5-2 mm/s)内对脑血流和脑血流进行合理的估计。然而,在较高的速度下,特别是在动脉或静脉样流动条件下,观察到一致的流量高估(高达200 %)。
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引用次数: 0
期刊
Magnetic resonance imaging
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