Copyright
©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Aug 21, 2022; 28(31): 4376-4389
Published online Aug 21, 2022. doi: 10.3748/wjg.v28.i31.4376
Published online Aug 21, 2022. doi: 10.3748/wjg.v28.i31.4376
Preoperative contrast-enhanced computed tomography-based radiomics model for overall survival prediction in hepatocellular carcinoma
Peng-Zhan Deng, Bi-Geng Zhao, Xian-Hui Huang, Ting-Feng Xu, Zi-Jun Chen, Qiu-Feng Wei, Xiao-Yi Liu, Yu-Qi Guo, Sheng-Guang Yuan, Wei-Jia Liao, Laboratory of Hepatobiliary and Pancreatic Surgery, Affiliated Hospital of Guilin Medical University, Guilin 541001, Guangxi Zhuang Autonomous Region, China
Author contributions: Deng PZ, Zhao BG and Huang XH contributed equally to this work; Liao WJ was the guarantor and designed the study; Deng PZ, Zhao BG, Xu TF, Chen ZJ, Wei QF, and Liu XY participated in the acquisition, analysis, and interpretation of the data; Deng PZ and Huang XH drafted the initial manuscript; Guo YQ, Yuan SG, and Liao WJ revised the article critically for important intellectual content.
Supported by the National Natural Science Foundation of China , No. 81372163 ; the Science and Technology Planning Project of Guilin , No. 20190218-1 ; the Openin Project of Key laboratory of High-Incidence-Tumor Prevention & Treatment (Guangxi Medical University) , Ministry of Education, No. GKE-KF202101; the Program of Guangxi Zhuang Autonomous Region health and Family Planning Commission , No. Z20210706 ; and the Innovation and Entrepreneurship Project of University Students in Guangxi , No. 202110601002 .
Institutional review board statement: The study was reviewed and approved by the research ethics committee of Affiliated Hospital of Guilin Medical University (Approval NO. 2021WJWZC14).
Informed consent statement: Informed consent was obtained from all patients.
Conflict-of-interest statement: There are no conflicts of interest to report.
Data sharing statement: No additional data are available.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Wei-Jia Liao, MD, Chief Doctor, Professor, Laboratory of Hepatobiliary and Pancreatic Surgery, Affiliated Hospital of Guilin Medical University, No. 15 Lequn Road, Xiufeng District, Guilin 541001, Guangxi Zhuang Autonomous Region, China.
Received: April 20, 2022
Peer-review started: April 20, 2022
First decision: June 2, 2022
Revised: June 14, 2022
Accepted: July 20, 2022
Article in press: July 20, 2022
Published online: August 21, 2022
Processing time: 118 Days and 2.8 Hours
Peer-review started: April 20, 2022
First decision: June 2, 2022
Revised: June 14, 2022
Accepted: July 20, 2022
Article in press: July 20, 2022
Published online: August 21, 2022
Processing time: 118 Days and 2.8 Hours
Core Tip
Core Tip: The prognosis of hepatocellular carcinoma (HCC) patients remains poor even after radical resection. Therefore, a precise and reliable tool to predict the prognosis of HCC patients is urgently needed. We established a predictive model incorporating radiomics features extracted from preoperative contrast-enhanced computed tomography images, alpha-fetoprotein and neutrophil-to-lymphocyte ratio to predict the overall survival of patients with HCC, and the model was visualized via a nomogram. The nomogram showed good accuracy for survival prediction.