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[1]周娴,许强,李建瑞,等.MRI多指标空间相关性在弥漫性胶质瘤分级及预后中的效能[J].医学研究与战创伤救治(原医学研究生学报),2025,38(01):28-34.[doi:10.16571/j.cnki.2097-2768.2025.01.005]
　ZHOU Xian,XU Qiang,LI Jianrui,et al.MRI multi-index spatial correlation in the grading and prognosis of diffuse glioma[J].JOURNAL OF MEDICALRESEARCH —COMBAT TRAUMA CARE,2025,38(01):28-34.[doi:10.16571/j.cnki.2097-2768.2025.01.005]
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MRI多指标空间相关性在弥漫性胶质瘤分级及预后中的效能()
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《医学研究与战创伤救治》（原医学研究生学报）[ISSN:1672-271X/CN:32-1713/R]

卷:
38卷
期数:
2025年01期
页码:
28-34
栏目:
论著·临床研究
出版日期:
2025-01-20

文章信息/Info

Title:
MRI multi-index spatial correlation in the grading and prognosis of diffuse glioma
文章编号:
2097-2768（2025）01-0028-07
作者:
周娴; 许强; 李建瑞; 詹天亮; 张志强
作者单位：210002 南京，南京医科大学金陵临床医学院（东部战区总医院）放射诊断科（周娴、许强、李建瑞、张志强）；210002 南京，南京中医药大学金陵临床医学院（东部战区总医院）放射诊断科（詹天亮）
Author(s):
ZHOU Xian; XU Qiang; LI Jianrui; ZHAN Tianliang; ZHANG Zhiqiang
（1.Department of Radiology，Jinling Hospital，Nanjing Medical University / General Hospital of Eastern Theater Com?mand，PLA，Nanjing 210002，Jiangsu，China；2.Department of Radiology，Jinling Clinical Medical College，NanjingUniversity of Traditional Chinese Medicine / General Hospital of Eastern Theater Command，PLA，Nanjing 210002，Jiangsu，China）
关键词:
弥漫性脑胶质瘤; 多指标MR; 空间相关性; 组织学分级; 生存期; 支持向量机
Keywords:
diffuseglioma; multi-indexMR; spatialcorrelation; histologicalgrade; survivalperiod; supportvectormachine
分类号:
R445.2R739.41
DOI:
10.16571/j.cnki.2097-2768.2025.01.005
文献标志码:
A
摘要:
目的 探讨弥漫性脑胶质瘤磁共振成像（MRI）多指标空间相关性特征，并观察其在肿瘤分级及生存期预测中的效能。方法回顾性分析2017年1月至2020年1月东部战区总医院经病理证实的弥漫性胶质瘤患者198例（Ⅱ级71例、Ⅲ级42例、Ⅳ级85 例）的多序列［T1加权成像（T1WI）、T2 加权成像（T2WI）、T1WI 增强扫描（T1CE）、扩散加权成像（DWI）及动脉自旋标记（ASL）］MRI数据。定量分析肿瘤实性部分多指标：T1WI及T2WI相对信号强度、T1CE相对强化值、表观扩散系数（ADC）及脑血流量（CBF）间的空间相关性特征。观察多指标间空间相关性特征与病理分级及生存预后的关系。并利用支持向量机（SVM）分类器建立MRI多指标空间相关性特征模型，用于胶质瘤的病理分级及生存期的预测。结果弥漫性胶质瘤高、低级别间MRI多指标的空间相关性有显著差异，且T1CE_T2、T1CE_T1、T1CE_CBF、T1CE_ADC Z值ROC曲线下面积（AUC）>0.7，基于指标间空间相关性构建的SVM预测模型显示有较高的病理分级效能（AUC=0.9222），模型中T1CE_T2 Z值特征权重最高；长、短生存期中T1CE_ADC、T1CE_T2、T1CE_T1 指标间的空间相关性有显著差异（P<0.05），生存期预测模型中AUC 为0.6318 且T1CE_T1 Z值特征权重最高。结论MRI多指标间空间相关特征分析为胶质瘤异质性病理生理机制提供证据，并在肿瘤病理分级和生存期预测方面具有应用价值。
Abstract:
Objective This study aims at investigating the spatial correlation characteristics of MRI multi-index in diffuse gli?oma and evaluating its efficacy in predicting tumor grade and survival time. Methods A retrospective analysis was conducted on themulti-sequence MRI data of 198 patients with pathologically con?firmed diffuse glioma（71 cases of grade Ⅱ，42 cases of grade Ⅲ，85 cases of grade IV）from Jinling Hospital between January 2017and January 2020.T1 weighted imaging（T1WI），T2 weighted imag?ing（T2WI），contrast-enhanced MRI data（T1CE），diffusionweightedimaging（DWI），and arterial spin labeling（ASL）wereobtained. Quantitative analysis was performed on the spatial corre?lation betwe+N43en multiple indicators of the solid part of the tumor，in?cluding relative signal intensity on T1WI and T2WI，relative en?hancement value on T1WI，apparent diffusion coefficient（ADC）， and cerebral blood flow（CBF）. The relationship between the spatial correlation of multiple indicators and pathological grade as well assurvival time was observed. A support vector machine（SVM）classifier was used to establish an MRI multi-index spatial correlationfeature model for pathological grading and survival prediction of glioma. Results There was significant difference in the spatial cor?relation of MRI multiple indicators between high and low grade diffuse gliomas，and the area under the ROC curve（AUC）of T1CE_T2，T1CE_T1，T1CE_CBF，T1CE_ADC Z values was > 0.7. The SVM prediction model based on the spatial correlation between indicatorsshowed a high pathological grading efficiency（AUC=0.9222），and the T1CE_T2 Z score feature weight in the model was the highest.The spatial correlations among T1CE_ADC，T1CE_T2 and T1CE_T1 indicators in the long and short survival periods were significantlydifferen（t P<0.05）.The AUC ofthe survivalprediction modelwas 0.6318 and T1CE_T1 Z score feature weightwasthe highest. ConclusionThe spatial correlation feature analysis of multiple MRI indicators provides evidence for the heterogeneous pathophysiological mecha?nisms of glioma，and has application value in tumor pathological grading and survival prediction.

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备注/Memo

备注/Memo:
基金项目：国家重点研发计划（2018YFA0701703）；国家自然科学基金（81530054）
更新日期/Last Update: 2025-01-20