磁共振成像2026，Vol.17Issue(1)：175-181,7.DOI:10.12015/issn.1674-8034.2026.01.027
多模态MRI影像组学预测脑胶质瘤分子分型的研究进展
Research progress in multimodal MRI radiomics for predicting molecular typing of gliomas
摘要
Abstract
Glioma,as the most common primary malignant tumor in the central nervous system(CNS),is characterized by high heterogeneity.Accurate molecular subtyping is conducive to formulating treatment strategies and improving prognosis for glioma patients.Although glioma can be diagnosed through surgical procedures or biopsies,such methods are invasive,carrying risks of sampling bias and postoperative complications.Multimodal MRI radiomics,a prominent area of research in disease diagnosis,is capable of integrating the strengths of various MRI imaging techniques.By extracting high-throughput imaging features spanning morphology,texture,functional metabolism and other dimensions,and leveraging machine learning,deep learning as well as statistical analysis tools to build predictive models,this technique has demonstrated significant potential for non-invasive assessment of glioma molecular markers.This paper reviews the recent advances in multimodal MRI radiomics for non-invasively predicting glioma molecular subtypes,points out current research limitations,and suggests future research directions,with the aim of ultimately providing imaging evidence and clinical guidance for preoperative precise diagnosis and the formulation of personalized treatment regimens for glioma patents.关键词
脑胶质瘤/多模态/影像组学/磁共振成像/分子分型Key words
glioma/multimodal/radiomics/magnetic resonance imaging/molecular typing分类
医药卫生引用本文复制引用
唐元彪,狄宁宁,许昌..多模态MRI影像组学预测脑胶质瘤分子分型的研究进展[J].磁共振成像,2026,17(1):175-181,7.基金项目
Natural Science Foundation of Shandong Province(No.ZR2019BH025). 山东省自然科学基金项目(编号:ZR2019BH025) （No.ZR2019BH025）
