Yao Shan, Ye Zheng, Wei Yi, Jiang Han-Yu, Song Bin
Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China.
World J Gastrointest Oncol. 2021 Nov 15;13(11):1599-1615. doi: 10.4251/wjgo.v13.i11.1599.
Hepatocellular carcinoma (HCC) is the most common cancer and the second major contributor to cancer-related mortality. Radiomics, a burgeoning technology that can provide invisible high-dimensional quantitative and mineable data derived from routine-acquired images, has enormous potential for HCC management from diagnosis to prognosis as well as providing contributions to the rapidly developing deep learning methodology. This article aims to review the radiomics approach and its current state-of-the-art clinical application scenario in HCC. The limitations, challenges, and thoughts on future directions are also summarized.
肝细胞癌(HCC)是最常见的癌症,也是癌症相关死亡的第二大主要原因。放射组学是一项新兴技术,能够从常规获取的图像中提供不可见的高维定量且可挖掘的数据,在HCC从诊断到预后的管理中具有巨大潜力,同时也为快速发展的深度学习方法做出贡献。本文旨在综述放射组学方法及其在HCC中的当前临床应用现状。还总结了其局限性、挑战以及对未来方向的思考。