Application of radiomics in hepatocellular carcinoma:A review

作     者：Zhi-Cheng Jin Bin-Yan Zhong 

作者机构：Center of Interventional Radiology and Vascular SurgeryDepartment of RadiologyZhongda HospitalMedical SchoolSoutheast UniversityNanjing 210009Jiangsu ProvinceChina Department of Interventional RadiologyThe First Affiliated Hospital of Soochow UniversitySuzhou 215006Jiangsu ProvinceChina 

出 版 物：《Artificial Intelligence in Medical Imaging》 (医学影像中的人工智能（英文）)

年 卷 期：2021年第2卷第3期

页      面：64-72页

学科分类：1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学] 

主　　题：Hepatocellular carcinoma Radiomics Machine learning Deep learning Radiogenomics 

摘      要：Hepatocellular carcinoma(HCC)is the most common form of primary liver cancer with low 5-year survival *** high molecular heterogeneity in HCC poses huge challenges for clinical practice or trial design and has become a major barrier to improving the management of ***,current clinical practice based on single bioptic or archived tumor tissue has been deficient in identifying useful *** concept of radiomics was first proposed in 2012 and is different from the traditional imaging analysis based on the qualitative or semiquantitative analysis by *** refers to high-throughput extraction of large amounts number of high-dimensional quantitative features from medical images through machine learning or deep learning *** the radiomics method could quantify tumoral phenotypes and heterogeneity,which may provide benefits in clinical decision-making at a lower ***,we review the workflow and application of radiomics in HCC.