Magnetic resonance imaging最新文献_第6页

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

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

Magnetic resonance imaging

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

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

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

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

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引用次数: 0

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

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

Magnetic resonance imaging

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

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

Background

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

Objective

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

Methods

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

Results

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

Conclusion

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

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

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引用次数: 0

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

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

Magnetic resonance imaging

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

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

Purpose

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

Methods

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

Results

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

d

,

v_{in}

,

{ADC}_{ex}

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

k_{in}

could not be reliably estimated.

Conclusion

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

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

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引用次数: 0

Application value of delayed contrast enhancement-T2-fluid-attenuated inversion recovery in traumatic brain injury 延迟对比增强- t2 -液体衰减反转恢复在颅脑外伤中的应用价值

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

Magnetic resonance imaging

Pub Date : 2025-11-12 DOI: 10.1016/j.mri.2025.110562

Dandan Sun , Kuntao Chen , Di Liang , Yuan Gui , Jing Zhang

Objective

Exploring the diagnostic value of the contrast-enhanced delayed enhancement-T2-fluid attenuation inversion recovery sequence (CE-T2-FLAIR) in traumatic brain injury (TBI).

Methods

Clinical and Magnetic resonance imaging (MRI) data of 30 patients with brain trauma who met the inclusion criteria were retrospectively collected, and the MRI images were classified into three groups: the MRI plain scan group, the contrast-enhanced T1-weighted imaging (CE-T1WI) group, and the delayed CE-T2-FLAIR group. The chi-square test was employed to analyze the differences among the three groups of images in terms of MRI-detected cerebral contusion and laceration, intracranial hematoma, and the number of positive imaging findings. The chi-square test was also used to analyze the differences among the three groups of images in terms of the presentation of cerebral contusion and laceration, intracranial hematoma, and the number of positive imaging results. The paired-samples t-test was utilized to analyze whether there were statistical differences in the meningeal enhancement scores, meningeal Enhancement Index (EI), and meningeal Normalized Signal Intensity (NSI) between delayed CE-T2-FLAIR and CE-T1WI. Spearman's rank correlation analysis was conducted to explore the correlations between the meningeal enhancement scores, meningeal EI, meningeal NSI from the two enhanced examinations and clinical symptoms, cerebral contusion and laceration, as well as intracranial hematoma.

Results

The number of positive imaging findings in the delayed CE-T2-FLAIR group was higher than that in the MRI plain scan group and the CE-T1WI group (p < 0.05). The meningeal enhancement score, meningeal EI, and meningeal NSI in the delayed CE-T2-FLAIR group were higher than those in the CE-T1WI group (p < 0.05). The meningeal enhancement scores of both delayed CE-T2-FLAIR and CE-T1WI were positively correlated with headache, cerebral contusion and laceration, and subdural hemorrhage (p < 0.05). The meningeal EI of delayed CE-T2-FLAIR was positively correlated with transient loss of consciousness and subdural hemorrhage (p < 0.05), while there was no correlation between the meningeal NSI of delayed CE-T2-FLAIR and transient loss of consciousness or subdural hemorrhage (p > 0.05). There was no significant correlation between the meningeal EI, meningeal NSI of CE-T1WI and clinical manifestations, cerebral contusion and laceration, or intracranial hematoma (p > 0.05).

Conclusion

Compared with MRI plain scan and CE-T1WI, delayed CE-T2-FLAIR has more advantages in TBI.

目的探讨对比增强延迟增强- t2 -液体衰减反转恢复序列（CE-T2-FLAIR）对外伤性脑损伤（TBI）的诊断价值。方法回顾性收集30例符合入选标准的脑外伤患者的临床及MRI资料，将MRI图像分为MRI平扫组、对比增强t1加权成像（CE-T1WI）组和延迟CE-T2-FLAIR组。采用卡方检验分析三组影像在mri检出的脑挫裂伤、颅内血肿及阳性影像数方面的差异。采用卡方检验分析三组图像在脑挫裂伤的表现、颅内血肿、阳性影像结果数等方面的差异。采用配对样本t检验分析延迟CE-T2-FLAIR与CE-T1WI脑膜增强评分、脑膜增强指数（EI）、脑膜归一化信号强度（NSI）是否存在统计学差异。采用Spearman秩相关分析，探讨两种增强检查的脑膜增强评分、脑膜EI、脑膜NSI与临床症状、脑挫伤、裂伤、颅内血肿的相关性。结果延迟CE-T2-FLAIR组的阳性影像数高于MRI平扫组和CE-T1WI组（p < 0.05）。延迟CE-T2-FLAIR组脑膜增强评分、脑膜EI、脑膜NSI均高于CE-T1WI组（p < 0.05）。延迟CE-T2-FLAIR和CE-T1WI脑膜增强评分与头痛、脑挫裂伤、硬膜下出血呈正相关（p < 0.05）。迟发性CE-T2-FLAIR脑膜损伤与一过性意识丧失、硬膜下出血呈正相关（p < 0.05），迟发性CE-T2-FLAIR脑膜损伤与一过性意识丧失、硬膜下出血无相关性（p > 0.05）。CE-T1WI脑膜EI、脑膜NSI与临床表现、脑挫裂伤、颅内血肿无显著相关性（p > 0.05）。结论与MRI平扫和CE-T1WI相比，延迟CE-T2-FLAIR对TBI有更大的优势。

{"title":"Application value of delayed contrast enhancement-T2-fluid-attenuated inversion recovery in traumatic brain injury","authors":"Dandan Sun , Kuntao Chen , Di Liang , Yuan Gui , Jing Zhang","doi":"10.1016/j.mri.2025.110562","DOIUrl":"10.1016/j.mri.2025.110562","url":null,"abstract":"<div><h3>Objective</h3><div>Exploring the diagnostic value of the contrast-enhanced delayed enhancement-T2-fluid attenuation inversion recovery sequence (CE-T2-FLAIR) in traumatic brain injury (TBI).</div></div><div><h3>Methods</h3><div>Clinical and Magnetic resonance imaging (MRI) data of 30 patients with brain trauma who met the inclusion criteria were retrospectively collected, and the MRI images were classified into three groups: the MRI plain scan group, the contrast-enhanced T1-weighted imaging (CE-T1WI) group, and the delayed CE-T2-FLAIR group. The chi-square test was employed to analyze the differences among the three groups of images in terms of MRI-detected cerebral contusion and laceration, intracranial hematoma, and the number of positive imaging findings. The chi-square test was also used to analyze the differences among the three groups of images in terms of the presentation of cerebral contusion and laceration, intracranial hematoma, and the number of positive imaging results. The paired-samples <em>t</em>-test was utilized to analyze whether there were statistical differences in the meningeal enhancement scores, meningeal Enhancement Index (EI), and meningeal Normalized Signal Intensity (NSI) between delayed CE-T2-FLAIR and CE-T1WI. Spearman's rank correlation analysis was conducted to explore the correlations between the meningeal enhancement scores, meningeal EI, meningeal NSI from the two enhanced examinations and clinical symptoms, cerebral contusion and laceration, as well as intracranial hematoma.</div></div><div><h3>Results</h3><div>The number of positive imaging findings in the delayed CE-T2-FLAIR group was higher than that in the MRI plain scan group and the CE-T1WI group (<em>p</em> < 0.05). The meningeal enhancement score, meningeal EI, and meningeal NSI in the delayed CE-T2-FLAIR group were higher than those in the CE-T1WI group (<em>p</em> < 0.05). The meningeal enhancement scores of both delayed CE-T2-FLAIR and CE-T1WI were positively correlated with headache, cerebral contusion and laceration, and subdural hemorrhage (<em>p</em> < 0.05). The meningeal EI of delayed CE-T2-FLAIR was positively correlated with transient loss of consciousness and subdural hemorrhage (<em>p</em> < 0.05), while there was no correlation between the meningeal NSI of delayed CE-T2-FLAIR and transient loss of consciousness or subdural hemorrhage (<em>p</em> > 0.05). There was no significant correlation between the meningeal EI, meningeal NSI of CE-T1WI and clinical manifestations, cerebral contusion and laceration, or intracranial hematoma (<em>p</em> > 0.05).</div></div><div><h3>Conclusion</h3><div>Compared with MRI plain scan and CE-T1WI, delayed CE-T2-FLAIR has more advantages in TBI.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"126 ","pages":"Article 110562"},"PeriodicalIF":2.0,"publicationDate":"2025-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145518938","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

Impact of RF saturation parameters and magnetization transfer contrast (MTC) signal model selection on amide proton transfer (APT) tumor contrast at 3 T RF饱和参数和磁化转移对比（MTC）信号模型选择对3 T下酰胺质子转移（APT）肿瘤对比的影响

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

Magnetic resonance imaging

Pub Date : 2025-11-09 DOI: 10.1016/j.mri.2025.110561

Munendra Singh , Sultan Z. Mahmud , Kevin Ju , Jinyuan Zhou , Hye-Young Heo

Purpose

To evaluate the effect of RF saturation parameters and different amide proton transfer (APT) quantification methods on human brain tumor contrast.

Methods

Chemical exchange saturation transfer (CEST) images were acquired with varied RF saturation strengths, saturation times, and duty cycles (DC) at 3 T from brain tumor patients with glioblastoma. Different quantification methods, including magnetization transfer ratio asymmetry (MTR_asym), apparent exchange-dependent relaxation (AREX), and extrapolated semisolid MT reference (EMR), were compared for measuring APT. The effects of different MT contrast (MTC) lineshape assumptions, such as Gaussian vs. Lorentzian or super-Lorentzian, and symmetric vs. asymmetric, were also evaluated with respect to APT contrast in human brain tumors.

Results

Overall, higher RF saturation strengths (> 1.5 μT) and longer saturation times with 100 % DC resulted in better enhancement of APT tumor contrast. The asymmetric super-Lorentzian MTC lineshape assumption was found to be the most accurate for in vivo brain tissue and provided the best fit for the acquired data. The EMR technique provided highly positive contrast for brain tumors, although still influenced by water relaxation effects.

Conclusions

RF saturation parameters and APT quantification methods can greatly influence brain tumor contrast. The choice of an APT quantification metric must be carefully considered according to RF saturation parameter settings. The EMR-based CEST calculation metric demonstrated high contrast for brain tumors, making it a powerful clinical biomarker for tumor detection.

目的：评价射频饱和度参数及不同酰胺质子转移（APT）定量方法对人脑肿瘤造影剂的影响。方法：获取脑肿瘤胶质母细胞瘤患者在3 T下不同RF饱和强度、饱和时间和占空比（DC）的化学交换饱和转移（CEST）图像。不同的量化方法，包括磁化传递比不对称（MTRasym）、表观交换依赖弛豫（AREX）和外推半固体MT参考（EMR），用于测量APT。不同的MT对比（MTC）线形假设，如高斯与洛伦兹或超洛伦兹，对称与不对称，也对人脑肿瘤的APT对比进行了评估。结果：总体而言，较高的RF饱和强度（> 1.5 μT）和较长的饱和时间（100 % DC）对APT肿瘤造影剂的增强效果较好。发现非对称超洛伦兹MTC线形假设对活体脑组织最准确，并提供了最佳的拟合数据。EMR技术为脑肿瘤提供了高度阳性的对比，尽管仍然受到水松弛效应的影响。结论：射频饱和度参数和APT定量方法对脑肿瘤造影有较大影响。APT量化度量的选择必须根据RF饱和参数设置仔细考虑。基于emr的CEST计算指标显示脑肿瘤的高对比度，使其成为肿瘤检测的强大临床生物标志物。

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引用次数: 0

Deep learning approach for DCE-MRI parameter estimation: Evaluating signal intensity and concentration-time curve-based convolution-neural-networks DCE-MRI参数估计的深度学习方法：评估信号强度和基于浓度-时间曲线的卷积神经网络。

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

Magnetic resonance imaging

Pub Date : 2025-11-07 DOI: 10.1016/j.mri.2025.110559

Piyush Kumar Prajapati , Rakesh Kumar Gupta , Anup Singh

Dynamic contrast-enhanced MRI (DCE-MRI) is common technique for assessing tissue perfusion and permeability in brain tumors (e.g., gliomas), using generalized tracer kinetic (GTK) analysis. However, conventional non-linear least squares (NLLS) methods are computationally expensive and sensitive to noise and protocol variations (e.g., temporal resolution, flip angle), leading to inconsistent parameter estimates. Most recent deep learning methods use signal-intensity and pre-contrast T1, without addressing acquisition protocol variation effects. We propose CNN_CON, a concentration curve-based convolutional neural network-based approach for GTK parameter estimation, designed to adapt to various DCE-MRI protocols with faster processing and investigate its accuracy and robustness to protocol variations. CNN_CON was trained on synthetic data with protocol variations, and fine-tuned on 72 glioma patients(grade 2–4). Validation was performed on 18 test patients and two external datasets: cross-scanner(n = 9, 1.5 T) and cross-institutional(n = 6, different hospital). Performance was compared against NLLS and AIF-TK Net. CNN_CON achieved mean absolute errors of 111 ± 70 × 10⁻⁵ min⁻¹, 134 ± 53 × 10⁻⁵, and 133 ± 57 × 10⁻⁴ for

K^{trans}

,

v_{p}

and

v_{e}

, respectively, with no significant difference from NLLS(p > 0.05), while reducing computational time from 15 min to 17 s. External validation demonstrated consistent performance across scanner and institutions. CNN_CON showed 2-3× better accuracy than AIF-TK Net and equivalent diagnostic capability for tumor grading (AUC = 0.89). Correlation with NLLS exceed 0.97 in normal tissues. The concentration-based approach provides superior robustness to protocol variations, validated across multiple centers, enabling consistent application of perfusion imaging biomarkers in clinical practice.

动态对比增强MRI （DCE-MRI）是评估脑肿瘤（如胶质瘤）组织灌注和通透性的常用技术，使用广义示踪动力学（GTK）分析。然而，传统的非线性最小二乘（NLLS）方法计算成本高，对噪声和协议变化（例如，时间分辨率，翻转角度）敏感，导致参数估计不一致。最近的深度学习方法使用信号强度和预对比T1，没有解决采集协议变化的影响。我们提出了CNNCON，一种基于浓度曲线的卷积神经网络的GTK参数估计方法，旨在以更快的处理速度适应各种DCE-MRI协议，并研究其对协议变化的准确性和鲁棒性。CNNCON是在方案变化的合成数据上进行训练的，并对72例胶质瘤患者（2-4级）进行了微调。对18名试验患者和两个外部数据集进行验证：跨扫描仪（n = 9,1.5 T）和跨机构（n = 6，不同医院）。与nls和AIF-TK Net进行性能比较。CNNCON实现111年平均绝对误差 ±70  × 纯 最低为1,134 ± 53 × 纯,和133年 ± 57 ×4 打败Ktrans, vp和ve、分别从附近无显著差异(p > 0.05),同时减少计算时间从15 分钟17 年代。外部验证证明了扫描仪和机构之间一致的性能。CNNCON的准确率比AIF-TK Net高2-3倍，具有同等的肿瘤分级诊断能力（AUC = 0.89）。正常组织与NLLS的相关性超过0.97。正常组织与NLLS的相关性超过0.97。基于浓度的方法为方案变化提供了卓越的稳健性，在多个中心验证，使灌注成像生物标志物在临床实践中的一致应用成为可能。

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引用次数: 0

R-index: A robust metric for IVIM parameter estimation on clinical MRI scanners R-index：临床MRI扫描仪上IVIM参数估计的稳健度量。

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

Magnetic resonance imaging

Pub Date : 2025-11-07 DOI: 10.1016/j.mri.2025.110560

Yan Dai , Xun Jia , Yen-peng Liao , Deng Jie

Purpose

Intravoxel Incoherent Motion (IVIM) model characterizes both water diffusion and perfusion in tissues, providing quantitative biomarkers valuable for tumor characterization. However, parameter estimation through nonlinear fitting of this bi-exponential model is challenging for its ill-posed nature, resulting in poor reproducibility, particularly at low signal to noise ratios (SNRs) in a clinic scenario. This study analyzes the uncertainty of IVIM model fitting, quantifies parameter collinearity, and introduces a new index with enhanced robustness to enhance clinical applicability of the IVIM model.

Methods

The probability distributions of estimated IVIM parameters were evaluated across a clinically relevant range. Collinearity among parameters was assessed and a metric, R-index, was proposed. The R-index linearly combines individual IVIM parameters to mitigate collinearity and reduce estimation uncertainty. Simulation, volunteer, and patient studies were conducted to validate the presence of parameter collinearity and to assess the robustness of the R-index.

Results

In simulations under typical clinical conditions (SNR = 20), normalized IVIM parameters exhibited mean standard deviations (Std) of 0.107–0.269 and the expected mean Std for R was 0.120, whereas the R-index showed a lower Std of 0.064. Same-day repeat scans in a healthy volunteer (1.5 T MRI) and multi-day scans in six brain tumor patients (1.5 T MR-Linac) confirmed parameter collinearity: Across the volunteer and patients, the mean Std of R-index was lower than the expected mean Std assuming independence between individual IVIM parameters.

Conclusions

The R-index provides a robust metric for IVIM model fitting under low SNR in typical clinical conditions, offering improved reproducibility and potential for broader clinical applicability.

目的：体素内非相干运动（IVIM）模型表征了水在组织中的扩散和灌注，为肿瘤表征提供了有价值的定量生物标志物。然而，通过这种双指数模型的非线性拟合进行参数估计是具有挑战性的，因为它的病态性质，导致再现性差，特别是在临床场景中的低信噪比（SNRs）下。本研究分析了IVIM模型拟合的不确定性，量化了参数共线性，并引入了一个增强鲁棒性的新指标，以提高IVIM模型的临床适用性。方法：在临床相关范围内评估估计IVIM参数的概率分布。评估了参数之间的共线性，并提出了度量r指数。r指数线性组合了单个IVIM参数，以减轻共线性并降低估计不确定性。进行了模拟、志愿者和患者研究，以验证参数共线性的存在并评估r指数的稳健性。结果：在典型临床条件下（信噪比 = 20）的模拟中，归一化IVIM参数的平均标准偏差（Std）为0.107-0.269，R的期望平均Std为0.120，而R指数的标准偏差较低，为0.064。一名健康志愿者的当日重复扫描（1.5 T MRI）和六名脑肿瘤患者的多日扫描（1.5 T MR-Linac）证实了参数共线性：在志愿者和患者中，r指数的平均Std低于假设个体IVIM参数之间独立的预期平均Std。结论：r指数为典型临床条件下低信噪比下的IVIM模型拟合提供了一个稳健的指标，提高了可重复性，并有可能更广泛的临床适用性。

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引用次数: 0

Correction of aliasing artifact in accelerated echo-planar imaging 加速回波平面成像中混叠伪影的校正。

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

Magnetic resonance imaging

Pub Date : 2025-11-03 DOI: 10.1016/j.mri.2025.110556

Silu Han , Chidi P. Ugonna , Nan-kuei Chen

Purpose

To develop a comprehensive reconstruction pipeline that simultaneously addresses 2D Nyquist and aliasing artifacts in echo-planar imaging (EPI) data acquired using various schemes, including single-shot, multi-shot, parallel, and multi-band EPI.

Methods

We introduce a novel 2D Nyquist artifact correction method that extends our previously reported phase-search reconstruction approach. A series of phase-corrected images are generated using a range of candidate phase values, and the corresponding coil sensitivity profiles are compared with known profiles to estimate an optimal 2D Nyquist phase correction map. In addition, we propose an integrated reconstruction procedure that corrects aliasing artifacts arising from 2D Nyquist effects, shot-to-shot motion-induced phase variations, and both in-plane and through-plane acceleration schemes. The proposed methods were evaluated using resting-state fMRI data from 30 healthy volunteers.

Results

The proposed method substantially reduced residual artifacts in EPI data, as measured by the ghost-to-signal ratio. The resulting default-mode network maps showed improved correspondence with known reference networks compared to those obtained using conventional 1D Nyquist artifact correction methods.

Conclusion

The developed reconstruction pipeline effectively corrects multiple sources of aliasing artifacts in EPI data, offering improved image quality and functional sensitivity across a wide range of EPI acquisition schemes.

目的：开发一个综合的重建管道，同时处理二维奈奎斯特和混叠伪影在回声平面成像（EPI）数据中，使用各种方案，包括单镜头、多镜头、并行和多波段EPI。方法：我们引入了一种新的二维奈奎斯特伪影校正方法，扩展了我们之前报道的相位搜索重建方法。使用一系列候选相位值生成一系列相位校正图像，并将相应的线圈灵敏度曲线与已知曲线进行比较，以估计最佳的2D奈奎斯特相位校正图。此外，我们提出了一个集成的重建程序，以纠正由二维奈奎斯特效应、镜头到镜头运动引起的相位变化以及平面内和平面内加速度方案引起的混叠伪影。利用30名健康志愿者的静息状态功能磁共振成像数据对所提出的方法进行了评估。结果：所提出的方法大大减少了EPI数据中的残余伪影，通过鬼信号比来测量。与使用传统1D Nyquist伪影校正方法获得的结果相比，得到的默认模式网络图与已知参考网络的对应关系得到了改善。结论：开发的重建管道有效地纠正了EPI数据中的多个混叠伪影来源，在各种EPI采集方案中提供了更高的图像质量和功能灵敏度。

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引用次数: 0

Histological validation of dark-blood LGE quantification methods in rat myocardial infarction models: A 3.0 T CMR study 大鼠心肌梗死模型暗血LGE定量方法的组织学验证：3.0 T CMR研究。

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

Magnetic resonance imaging

Pub Date : 2025-11-02 DOI: 10.1016/j.mri.2025.110557

Pei Liu , Xiaoying Zhao , Xiaodong Yuan, Lujing Wang, Yujiao Song, Siwen Chen, Mingtian Chen, Xinxiang Zhao

<div><h3>Rationale and objectives</h3><div>Current studies of cardiac magnetic resonance late gadolinium enhancement (CMR-LGE) in rat myocardial infarction (MI) models are mostly based on 7.0 T MRI, which is not widely available. In addition, differences in infarct volume detected by various quantification methods for dark-blood LGE remain unclear. This study is the first to systematically validate different dark-blood LGE quantification methods using 3.0 T MRI in an SD rat MI model. The aim was to assess the reliability, consistency, and agreement with histology, providing a methodological reference for in vivo quantification of myocardial fibrosis in rat MI models and offering experimental and theoretical support for optimizing quantitative analysis strategies in future clinical studies.</div></div><div><h3>Materials and methods</h3><div>Methods: Finally, 20 SPF male SD rats were included (5 in the control group and 15 in the myocardial infarction model group). MI models were created by open-chest ligation of the left anterior descending coronary artery. Four weeks later, 3.0 T CMR dark-blood LGE scans were performed. After heart excision, continuous 4–6 μm paraffin sections were prepared. Masson trichrome staining was used to determine collagen volume fraction as the histological standard. LGE images were analyzed with CVI42 software. Quantitative results were obtained using manual delineation, 2SD threshold, 3SD threshold, 5SD threshold, and full-width half-maximum (FWHM) methods. Consistency with histology was assessed using intraclass correlation coefficients (ICC), concordance correlation coefficients (CCC), Pearson correlation, and Bland–Altman analysis.</div></div><div><h3>Results</h3><div>Consistency analysis revealed significant differences among the five LGE postprocessing methods compared with the histological gold standard (<em>P</em> < 0.05). The manual method demonstrated excellent intra- and inter-observer consistency (ICC > 0.95) and significantly outperformed the automated methods. Lin's concordance correlation coefficient and Pearson correlation analyses indicated the highest agreement with histology for the manual method (CCC = 0.895, 95 % CI: 0.745–0.958; <em>r</em> = 0.926, <em>P</em> < 0.001), surpassing all automated threshold methods.Correlation analyses confirmed a strong agreement between the manual method and histology, consistent with the CCC results. Among the automated methods, FWHM (CCC = 0.689, 95 % CI: 0.393–0.856) and 5SD (CCC = 0.682, 95 % CI: 0.388–0.850) performed relatively well, whereas 3SD (CCC = 0.617) and 2SD (CCC = 0.474) showed poorer agreements. Bland–Altman analysis supported this trend: the manual method exhibited the smallest systematic bias (mean bias = −1.00) and narrowest 95 % limits of agreement (−5.88 to +3.88). Among the automated methods, 5SD had the smallest bias (mean bias = +0.18), whereas 2SD showed the largest bias (mean bias = +5.96) and the widest limits of agreement.</div><

理由与目的：目前对大鼠心肌梗死（MI）模型的心脏磁共振晚期钆增强（CMR-LGE）的研究大多基于7.0 T MRI，该技术尚未广泛应用。此外，各种定量方法检测的暗血LGE梗死面积差异尚不清楚。本研究首次使用3.0 T MRI在SD大鼠心肌梗死模型中系统验证了不同的暗血LGE定量方法。目的是评估可靠性、一致性和与组织学的一致性，为心肌梗死模型大鼠体内心肌纤维化定量提供方法学参考，并为今后临床研究中优化定量分析策略提供实验和理论支持。材料与方法：方法：选取SPF雄性SD大鼠20只（对照组5只，心肌梗死模型组15只）。采用左冠状动脉前降支结扎术建立心肌梗死模型。4周后，进行3.0 T CMR黑血LGE扫描。心脏切除后，连续制作4-6 μm石蜡切片。马松三色染色法测定胶原体积分数作为组织学标准。使用CVI42软件对LGE图像进行分析。采用人工圈定、2SD阈值、3SD阈值、5SD阈值和全宽半最大值（FWHM）方法获得定量结果。采用类内相关系数（ICC）、一致性相关系数（CCC）、Pearson相关和Bland-Altman分析评估与组织学的一致性。结果：一致性分析显示，5种LGE后处理方法与组织学金标准相比存在显著差异（P  0.95），且显著优于自动化方法。Lin的一致性相关系数和Pearson相关分析显示，手工方法与组织学吻合度最高（CCC = 0.895,95 % CI: 0.745-0.958; r = 0.926,P ）结论：3.0 T暗血LGE成像在体内评价SD大鼠心肌纤维化模型是可行的。人工圈定与组织学吻合度最高，定量准确度最高。在信号强度阈值方法中，FWHM和5SD具有较高的一致性和稳定性，为大鼠心肌梗死的体内评价提供了较好的参考数据。

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引用次数: 0

Association of white matter hyperintensities with cognitive impairment. 白质高信号与认知障碍的关系。

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

Magnetic resonance imaging

Pub Date : 2025-11-01 Epub Date: 2025-07-29 DOI: 10.1016/j.mri.2025.110464

Wen-Jun Feng, Yu-Meng Gu, Xiao-Shuang Xia, Xin Li

Objective: This study aimed to examine the characteristics of cognitive impairment in individuals with white matter hyperintensities (WMH) and to compare differences in cognitive dysfunction across varying levels of WMH severity.

Methods: A total of 100 participants were randomly recruited from inpatient and outpatient departments of a hospital between November 2018 and December 2022. The cohort included 55 patients with cerebral small vessel disease (CSVD) and 45 control participants without CSVD. Among the CSVD group, 37 individuals had WMH. Cognitive function assessments were conducted for both the WMH and control groups to evaluate the characteristics of WMH-related cognitive dysfunction. Furthermore, cognitive scale scores and fractional anisotropy (FA) values obtained from diffusion tensor imaging (DTI) were compared among patients with varying WMH severity levels to analyze variations in cognitive performance and lesion characteristics across multiple brain regions.

Results: Statistically significant differences were observed between the control and CSVD groups in age, hypertension, diabetes, coronary heart disease, smoking, and physical activity (P < 0.05). The WMH and control groups demonstrated significant differences in the Montreal Cognitive Assessment (MoCA) total score, Digit Span Test (DST)-forward, DST-backward, Color Trail Test (CTT)-A, and CTT-B scores (p < 0.05). Significant differences were also identified between the mild and severe WMH groups (p < 0.05). Analysis of moderate and severe WMH groups indicated significant differences in FA values of the anterior horn of the lateral ventricle (p < 0.05), along with significant differences in age, DST-forward, and CTT-B scores (p < 0.05).

Conclusion: Cognitive impairment in individuals with WMH is predominantly characterized by marked declines in executive function and attention, while memory and language impairments are less pronounced. Severe WMH is associated with greater damage to the anterior horn of the lateral ventricle.

目的：本研究旨在研究白质高强度（WMH）患者的认知功能障碍特征，并比较不同程度的WMH严重程度在认知功能障碍方面的差异。方法：2018年11月至2022年12月，从某医院住院部和门诊部随机招募100名参与者。该队列包括55名患有脑血管疾病（CSVD）的患者和45名没有脑血管疾病的对照组。在CSVD组中，有37人患有WMH。对WMH组和对照组进行认知功能评估，以评估WMH相关认知功能障碍的特征。此外，通过比较不同WMH严重程度患者的认知量表得分和弥散张量成像（DTI）获得的分数各向异性（FA）值，分析认知表现和多脑区病变特征的变化。结果：对照组和CSVD组在年龄、高血压、糖尿病、冠心病、吸烟和体力活动方面存在统计学差异（P ）。结论：WMH患者的认知功能障碍主要表现为执行功能和注意力的明显下降，而记忆和语言障碍则不太明显。严重的WMH与侧脑室前角的更大损伤相关。

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引用次数: 0