Retrospective Study
Copyright ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Jul 14, 2023; 29(26): 4186-4199
Published online Jul 14, 2023. doi: 10.3748/wjg.v29.i26.4186
Radiomics model based on contrast-enhanced computed tomography to predict early recurrence in patients with hepatocellular carcinoma after radical resection
Shu-Qun Li, Li-Li Su, Ting-Feng Xu, Li-Ying Ren, Dong-Bo Chen, Wan-Ying Qin, Xuan-Zhi Yan, Jia-Xing Fan, Hong-Song Chen, Wei-Jia Liao
Shu-Qun Li, Ting-Feng Xu, Li-Ying Ren, Wan-Ying Qin, Xuan-Zhi Yan, Jia-Xing Fan, Wei-Jia Liao, Laboratory of Hepatobiliary and Pancreatic Surgery, The Affiliated Hospital of Guilin Medical University, Guilin 541001, Guangxi Zhuang Autonomous Region, China
Li-Li Su, Department of Clinical Laboratory, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin 541002, Guangxi Zhuang Autonomous Region, China
Dong-Bo Chen, Hong-Song Chen, Peking University People’s Hospital, Peking University Hepatology Institute, Beijing Key Laboratory of Hepatitis C and Immunotherapy for Liver Disease, Beijing 100091, China
Author contributions: Li SQ, Su LL, Xu TF, and Ren LY contributed equally to this work; Liao WJ and Li SQ designed the study; Ren LY, Chen DB, Xu TF, and Su LL analyzed the data and wrote the manuscript; Yan XZ and Fan JX collected the data; Qin WY and Chen HS analyzed the images data; all authors have read and approved the final manuscript.
Supported by National Natural Science Foundation of China, No. 81773148; Natural Science Foundation of Guangxi, No. 2018GXNSFDA138001; Program of Guangxi Zhuang Autonomous Region Health and Family Planning Commission, No. Z20210706; Guangxi Medical and Healthcare Appropriate Technology Development and Promotion and Application Projects, No. S2022132; Guangxi Natural Science Foundation, No. 2022JJA140009; and Guangxi Zhuang Autonomous Region Health and Family Planning Commission Self-funded of Scientific Research Project, No. Z20170812.
Institutional review board statement: The study was reviewed and approved by the Medical Ethics Committee of the Affiliated Hospital of Guilin Medical University (Approval No. 2021WJWZC14).
Informed consent statement: Patients were not required to give informed consent to the study because the analysis used anonymous clinical data that were obtained after each patient agreed to treatment by written consent.
Conflict-of-interest statement: Liao WJ has received fees for serving as a speaker, a professor for the Affiliated Hospital of Guilin Medical University; Liao WJ has received research funding from the National Natural Science Foundation of China.
Data sharing statement: Technical appendix, statistical code, and dataset available from the corresponding author at liaoweijia288@163.com. Participants gave informed consent for data sharing.
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, BM BCh, Professor, Laboratory of Hepatobiliary and Pancreatic Surgery, The Affiliated Hospital of Guilin Medical University, No. 15 Lequn Road, Xiufeng District, Guilin 541001, Guangxi Zhuang Autonomous Region, China. liaoweijia288@163.com
Received: February 11, 2023
Peer-review started: February 11, 2023
First decision: March 20, 2023
Revised: March 25, 2023
Accepted: June 6, 2023
Article in press: June 6, 2023
Published online: July 14, 2023
Processing time: 141 Days and 19.8 Hours
ARTICLE HIGHLIGHTS
Research background

Hepatocellular carcinoma (HCC) seriously endangers human life and health, but there is still a lack of satisfactory treatment options. Even if it is diagnosed at early stage, the recurrence rate is still very high. The clinical monitoring strategy for HCC recurrence is limited, so there is a need to find a new and effective recurrence prediction model for HCC. And we developed a radiomics model based on preoperative contrast-enhanced computed tomography (CECT) to evaluate early recurrence in patients with a single tumour.

Research motivation

Due to the high malignancy and suppressive immune microenvironment of HCC, there are still high recurrence and metastasis rates even in HCC patients who have undergone radical resection. Therefore, it is of vital importance to conduct systematic surveillance of HCC recurrence, and there is an urgent need to precisely predict recurrence in patients with HCC. If tumour recurrence can be detected earlier, the survival and quality of life of HCC patients might be greatly improved.

Research objectives

Despite the rapid development in the treatment of HCC in recent decades, patients’ outcomes remain unsatisfactory. One of the reasons is that the early diagnosis system of HCC recurrence is not yet well developed, so our research team established a recurrence prediction model for HCC based on medical imaging such as computed tomography (CT) to predict HCC recurrence earlier, so that timely treatment measures can be taken.

Research methods

We collected CT images from 537 clinical patients in two institutions and extracted valuable CT image features with 3D Slicer (v4.11, https://www.slicer.org). SPSS18.0 (SPSS Inc., Chicago, IL, United States) and R (version 4.0.3, https://www.rproject.org/) were used for statistical analyses and the prediction model of HCC recurrence was established jointly with AFP.

Research results

The radiomics scores calculated herein revealed significant differences between early and nonearly recurrence HCC patients. We combined radiomics and serum indicators to evaluate the risk of early recurrence, which was validated in an independent cohort. Our findings showed the value of predicting early recurrence in HCC patients by noninvasive indicators and might guide clinical decisions making. However, this is a retrospective analysis, and inherent biases are inevitable. We would conduct prospective trials with multimodality radiomics to confirm our results in future.

Research conclusions

The preoperative radiomics model was shown to be effective for predicting early recurrence among patients with single HCC. Compared with pathological biopsy or other tests, this model is noninvasive and more convenient for HCC patients.

Research perspectives

For HCC diagnosis, treatment, or prognosis assessment, more non-invasive methods are of great significance and needed.