MRI影像组学及深度学习在肝细胞癌中的应用  

Progress in the Application of MRI Radiomics and Deep Learning in Hepatocellular Carcinoma

作　　者：孙利娜 许永生[1,2] 王子圆 雷军强[1,2] SUN Li-na;XU Yong-sheng;WANG Zi-yuan;LEI Jun-qiang(The First School of Clinical Medine,Lanzhou University,Lanzhou 730000,Gansu Province,China;Department of Radiology,The First Hospital of Lanzhou University,Lanzhou 730000,Gansu Province,China)

机构地区：[1]兰州大学第一临床医学院,甘肃兰州730000 [2]兰州大学第一医院放射科,甘肃兰州730000

出　　处：《中国CT和MRI杂志》2025年第3期199-202,共4页Chinese Journal of CT and MRI

基　　金：兰州市城关区科技局项目(2020RCCX0053)。

摘　　要：肝细胞癌在全球具有高发病率和高死亡率,其预后不良,国家癌症中心发布中国肝癌患者的5年生存率仅为12.1%,5年生存率提升缓慢。因此,HCC的早诊、早治以及预后预测是当前的研究热点。近年来,影像组学和深度学习在HCC领域的研究和应用前景广阔。本文概述了这两项技术在HCC的影像学诊断、MVI预测、病理分期、预后判断、疗效评估方面的研究进展,并总结这些技术的局限性和发展前景。Hepatocellular carcinoma has a high incidence rate and mortality in the world,and its prognosis is still frustrating.The National Cancer Center announced that the 5-year survival rate of liver cancer patients in China is only 12.1%,and the 5-year survival rate is improving slowly.Therefore,early diagnosis,treatment,and prognosis prediction of HCC are current research hotspots.In recent years,radiomics and deep learning(DL)have broad research and application prospects in the field of HCC.This article provides an overview of the research progress of artificial intelligence technology in the imaging diagnosis,pathological staging,prognosis judgment,efficacy evaluation of HCC and summarizes the limitations and development prospects of these technologies.

关 键 词：影像组学 深度学习 磁共振成像 肝细胞癌 

分 类 号：R445.2[医药卫生—影像医学与核医学]