定量MRI技术预测宫颈癌淋巴结转移的研究进展  

Research progress on quantitative MRI techniques for predicting lymph node metastasis in cervical cancer

作　　者：张静[1] 庞雅萱 郭顺林[1] 殷亮(审校)[1] ZHANG Jing;PANG Yaxuan;GUO Shunlin;YIN Liang(The First Clinical Medicine College,Lanzhou University,Department of Radiology,The First Hospital of Lanzhou University,Lanzhou 730000,China)

机构地区：[1]兰州大学第一临床医学院兰州大学第一医院放射科,兰州730000

出　　处：《国际医学放射学杂志》2025年第1期102-106,共5页International Journal of Medical Radiology

基　　金：甘肃省自然科学基金(21JR1RA086)。

摘　　要：精准预测淋巴结转移是宫颈癌病人选择治疗方案及评估预后的关键因素。多种定量MRI技术,包括扩散加权成像(DWI)、体素内不相干运动(IVIM)、扩散峰度成像(DKI)、扩散张量成像(DTI)、酰胺质子转移加权(APTw)成像、动态增强MRI(DCE-MRI)等,已经逐渐用于宫颈癌淋巴结转移的预测中。基于MRI影像组学和深度学习的定量分析方法对预测宫颈癌淋巴结转移也具有较高效能。现就定量MRI技术、基于MRI影像组学和深度学习的定量分析方法在预测宫颈癌淋巴结转移方面的研究进展作一综述。Accurate prediction of lymph node metastasis is a key factor in selecting treatment options and evaluating the prognosis of patients with cervical cancer.Various quantitative MRI techniques,including DWI,IVIM,DKI,DTI,APTw,and DCE-MRI,have been increasingly applied to predict lymph node metastasis in cervical cancer.Moreover,quantitative analysis methods based on MRI radiomics and deep learning demonstrate high predictive efficacy for lymph node metastasis in cervical cancer.This article reviews the research progress in quantitative MRI technologies and quantitative analysis methods based on MRI radiomics and deep learning for predicting lymph node metastasis in cervical cancer.

关 键 词：宫颈癌 淋巴结转移 磁共振成像 影像组学 深度学习 

分 类 号：R445.2[医药卫生—影像医学与核医学] R737.33[医药卫生—诊断学]