肝细胞癌影像基因组学的研究进展

Advances in the radiogenomics of hepatocellular carcinoma

肝细胞癌(hepatocellular carcinoma,HCC)是一种高发病率和致死率的恶性肿瘤,其早期诊断、精准治疗及预后评估一直是医学研究的热点。HCC的诊疗预后与肿瘤基因突变状态密切相关,但传统的HCC基因突变状态检测以有创方法为主。近年来,影像基因组学得到快速发展,能够将基因突变状态与肿瘤组织成像特征关联,为HCC基因突变状态的无创预测带来了希望。目前已有许多针对HCC相关基因突变的影像基因组学研究,但尚未对其研究方法及结果进行系统的梳理与总结。本文综述了基于机器学习和大数据技术的影像基因组学技术在无创性评估HCC的基因突变状态的研究现状,总结了目前面临的挑战并对未来进行展望,以期为进一步完善相关研究及HCC患者的高效临床决策与精准治疗提供参考。

Hepatocellular carcinoma(HCC)is a malignant tumor with high incidence and lethality,and its early diagnosis,precision treatment and prognosis evaluation have always been the focus of medical research.The prognosis of HCC diagnosis and treatment is closely related to the mutation status of the tumor gene,but the traditional detection of HCC gene mutation status is mainly based on invasive methods.In recent years,radiogenomics has developed rapidly,which can associate the gene mutation status with the imaging characteristics of tumor tissue,bringing hope for the non-invasive prediction of HCC gene mutation status.At present,there have been many radiogenomics studies on HCC related gene mutations,but still lacking systematic combing and summary of the research methods and results.This paper reviews the current research status of radiogenomics using machine learning and big data technology for non-invasive evaluation of HCC,discusses the existing challenges,and explores future directions to provide a reference for advancing research in this field,as well as for enhancing clinical decision-making and precision treatment for HCC patients.