机构：[1]Department of Radiology, Sichuan University West China Hospital, No. 37 GUOXUE Alley, Chengdu 610041, Sichuan, China.四川大学华西医院[2]Department of Radiology & Institute of Radiation Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul 03080, Republic of Korea.[3]Big data research center, University of Electronic Science and Technology of China, No. 2006 XIYUAN Avenue, West Hi-tech Zone, Chengdu 610000, Sichuan, China.[4]GE Healthcare, No.1 HUOTUO Road, Zhangjiang Hi-Tech Park, Pudong, Shanghai 200000, China.
The Liver Imaging Reporting and Data System (LI-RADS) and European Association for the Study of the Liver (EASL) criteria are widely used for diagnosing hepatocellular carcinoma (HCC). Radiomics allows further quantitative tumor heterogeneity profiling. This study aimed to compare the diagnostic accuracies of the version 2018 (v2018) EASL, LI-RADS criteria and radiomics models for HCC in high-risk patients.
Ethical approval by the institutional review board and informed consent were obtained for this study. From July 2015 to September 2018, consecutive high-risk patients were enrolled in our tertiary care hospital and underwent gadoxetic acid-enhanced magnetic resonance (MR) imaging and subsequent hepatic surgery. We constructed a multi-sequence-based three-dimensional whole-tumor radiomics signature by least absolute shrinkage and selection operator model and multivariate logistic regression analysis. The diagnostic accuracies of the radiomics signature was validated in an independent cohort and compared with the EASL and LI-RADS criteria reviewed by two independent radiologists.
Two hundred twenty-nine pathologically confirmed nodules (173 HCCs, mean size: 5.74 ± 3.17 cm) in 211 patients were included. Among them, 201 patients (95%) were infected with hepatitis B virus (HBV). The sensitivity and specificity were 73 and 71% for the radiomics signature, 91 and 71% for the EASL criteria, and 86 and 82% for the LI-RADS criteria, respectively. The areas under the receiver operating characteristic curves (AUCs) of the radiomics signature (0.810), LI-RADS (0.841) and EASL criteria (0.811) were comparable.
In HBV-predominant high-risk patients, the multi-sequence-based MR radiomics signature, v2018 EASL and LI-RADS criteria demonstrated comparable overall accuracies for HCC.
基金：
The National Natural Science Foundation 81771797.
语种：
外文
PubmedID：
中科院(CAS)分区：
出版当年[2019]版：
大类|3 区医学
小类|3 区核医学4 区肿瘤学
最新[2023]版：
大类|2 区医学
小类|2 区肿瘤学2 区核医学
第一作者：
第一作者机构：[1]Department of Radiology, Sichuan University West China Hospital, No. 37 GUOXUE Alley, Chengdu 610041, Sichuan, China.
共同第一作者：
通讯作者：
推荐引用方式(GB/T 7714)：
Jiang Hanyu,Liu Xijiao,Chen Jie,et al.Man or machine? Prospective comparison of the version 2018 EASL, LI-RADS criteria and a radiomics model to diagnose hepatocellular carcinoma.[J].Cancer imaging : the official publication of the International Cancer Imaging Society.2019,19(1):84.doi:10.1186/s40644-019-0266-9.
APA：
Jiang Hanyu,Liu Xijiao,Chen Jie,Wei Yi,Lee Jeong Min...&Song Bin.(2019).Man or machine? Prospective comparison of the version 2018 EASL, LI-RADS criteria and a radiomics model to diagnose hepatocellular carcinoma..Cancer imaging : the official publication of the International Cancer Imaging Society,19,(1)
MLA：
Jiang Hanyu,et al."Man or machine? Prospective comparison of the version 2018 EASL, LI-RADS criteria and a radiomics model to diagnose hepatocellular carcinoma.".Cancer imaging : the official publication of the International Cancer Imaging Society 19..1(2019):84
