Retrospective Study
Copyright ©The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Mar 21, 2020; 26(11): 1208-1220
Published online Mar 21, 2020. doi: 10.3748/wjg.v26.i11.1208
Radiomics model based on preoperative gadoxetic acid-enhanced MRI for predicting liver failure
Wang-Shu Zhu, Si-Ya Shi, Ze-Hong Yang, Chao Song, Jun Shen
Wang-Shu Zhu, Si-Ya Shi, Ze-Hong Yang, Chao Song, Jun Shen, Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, Guangdong Province, China
Wang-Shu Zhu, Si-Ya Shi, Ze-Hong Yang, Chao Song, Jun Shen, Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, Guangdong Province, China
Author contributions: Zhu WS and Shi SY contributed equally to this work; Zhu W, Shi S, and Shen J designed the research; Zhu W and Shi S collected and analyzed the data, and wrote the manuscript; Yang Z and Song C analyzed and interpreted the data; Shen J wrote and revised the manuscript; All co-authors participated in writing and checking the manuscript, and approved the submitted manuscript.
Supported by the Guangdong Province Universities and Colleges Pearl River Scholar Funded Scheme (2017); and the Guangdong Natural Science Foundation, No. 2017A030313777.
Institutional review board statement: This study was reviewed and approved by the Ethics Committee of Sun Yat-Sen Memorial Hospital.
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: The authors declare no conflict of interest.
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: http://creativecommons.org/licenses/by-nc/4.0/
Corresponding author: Jun Shen, MD, Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou 501012, Guangdong Province, China. shenjun@mail.sysu.edu.cn
Received: October 12, 2019
Peer-review started: October 12, 2019
First decision: January 13, 2020
Revised: February 18, 2020
Accepted: February 21, 2020
Article in press: February 21, 2020
Published online: March 21, 2020
Processing time: 159 Days and 11.9 Hours
ARTICLE HIGHLIGHTS
Research background

Postoperative liver failure is the most serious complication for patients with hepatocellular carcinoma (HCC) after major hepatectomy. There are many methods for predicting postoperative liver failure after hepatectomy but not sufficiently accurate enough. This paper provides a radiomics model based on gadoxetic acid-enhanced magnetic resonance imaging (MRI), serve as a reliable predictive tool to reduce postoperative liver failure and mortality in cirrhotic patients with HCC after major hepatectomy.

Research motivation

In order to determine a new method to predict the postoperative liver failure after major hepatectomy and our radiomics model showed a favorable performance. However, the results obtained in this study need to be further verified in the population, and validation cohort need to be allocated.

Research objectives

The objective of this study is to determine the performance for predicting liver failure of a radiomics model based on preoperative gadoxetic acid-enhanced magnetic resonance imaging. The finding provides important information for medical decision making when surgery is required for a patient with HCC.

Research methods

The significant clinical variables were chosen and the radiomics signature was developed based on preoperative hepatobiliary phase gadoxetic acid-enhanced MRI in 101 patients with HCC from Sun Yat-Sen Memorial Hospital. The integrated radiomics-based model was presented as a radiomics nomogram. The performances for predicting post-operative liver failure were determined using receiver operating characteristics curve, calibration curve and decision curve analysis.

Research results

This study found that five radiomic features from hepatobiliary phase images were selected, and a radiomics-based model incorporating indocyanine green clearance rate at 15 min and radiomics signature showed favorable performance for predicting postoperative liver failure. The performance of radiomics model need to be further validated.

Research conclusions

The liver failure is very severe after liver resection. In this study, a radiomics signature based on preoperative gadoxetic acid–enhanced MRI was developed, which showed favorable performance in predicting liver failure in cirrhotic patients with HCC after major liver resection.

Research perspectives

This study confirmed the performance for predicting of our radiomics model. On this basis, future studies will further expand the sample size, and add the validation cohort.