摘要
乳腺疾病对女性健康构成严重威胁,其中乳腺非肿块强化(non-mass enhancement,NME)病变因其病理类型繁杂且影像征象不典型,在诊断及鉴别方面一直存在困难。近年来,以体素内不相干运动(intravoxel incoherent motion,IVIM)、扩散峰度成像(diffusion kurtosis Imaging,DKI)为代表的功能成像技术及人工智能(artificial intelligence,AI)算法,显著提升了磁共振成像(magnetic resonance imaging,MRI)对NME病变的诊断效能。基于此,本文系统梳理了MRI技术在NME病变中的研究进展,重点探讨功能成像、多模态融合及AI模型在其诊断及鉴别方面的临床应用价值,并针对技术瓶颈提出未来优化方向,旨在为NME病变的临床及科研提供参考。
Breast diseases pose a serious threat to women's health.Among them,non-mass enhancement(NME) lesions of the breast have always been difficult to diagnose and differentiate due to their complex and diverse pathological types and atypical imaging features.In recent years,functional imaging techniques represented by intravoxel incoherent motion(IVIM) and diffusion kurtosis imaging(DKI),as well as artificial intelligence(AI) algorithms,have significantly improved the diagnostic efficiency of magnetic resonance imaging(MRI) for NME lesions.Based on this,this paper systematically reviews the research progress of MRI techniques in NME lesions,focuses on discussing the clinical application values of functional imaging,multimodal fusion,and AI models,and proposes future optimization directions in response to technical bottlenecks,aiming to provide references for the clinical practice and scientific research of NME lesions.
作者
赵盈
赵楠
王寅中
许永生
赵文慧
雷军强
ZHAO Ying;ZHAO Nan;WANG Yinzhong;XU Yongsheng;ZHAO Wenhui;LEI Junqiang(The First Clinical Medical College of Lanzhou University,Lanzhou 730000,China;Department of Radiology,the First Hospital of Lanzhou University,Lanzhou 730000,China)
出处
《磁共振成像》
北大核心
2025年第4期186-191,共6页
Chinese Journal of Magnetic Resonance Imaging
关键词
乳腺非肿块强化病变
诊断及鉴别
磁共振成像
人工智能
影像组学
多参数及多模态成像
non-mass enhancement lesions of the breast
diagnosis and differentiation
magnetic resonance imaging
artificial intelligence
radiomics
multi-parameter and multimodal imaging
