Retrospective Study
Copyright ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Feb 14, 2023; 29(6): 1076-1089
Published online Feb 14, 2023. doi: 10.3748/wjg.v29.i6.1076
Clinical-radiomics nomogram for predicting esophagogastric variceal bleeding risk noninvasively in patients with cirrhosis
Rui Luo, Jian Gao, Wei Gan, Wei-Bo Xie
Rui Luo, Jian Gao, Department of Gastroenterology and Hepatology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, Chongqing, China
Wei Gan, Wei-Bo Xie, Department of Radiology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, Chongqing, China
Author contributions: Luo R was responsible for designing the study, collecting data, analyzing data, and writing the paper; Gao J was responsible for designing the study and guiding important content of the article; Gan W and Xie WB were responsible for providing technical support. All authors approved the final version of the manuscript for submission for publication.
Supported by Kuanren Talents Program of The Second Affiliated Hospital of Chongqing Medical University.
Institutional review board statement: The study was reviewed and approved by the Ethics Committee of the Second Affiliated Hospital of Chongqing Medical University (No. 2022-149).
Informed consent statement: Our study was a retrospective study conducted at a single center. We used data from patients at the time they were treated in the hospital, and these data were collected and analyzed anonymously. The informed consent waiver was granted by the Institutional Review Board.
Conflict-of-interest statement: The authors declare that the research was conducted in the absence of any commercial or financial relationships.
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: Jian Gao, MMed, PhD, Chief Doctor, Professor, Department of Gastroenterology and Hepatology, The Second Affiliated Hospital of Chongqing Medical University, No. 76 Linjiang Road, Yuzhong District, Chongqing 400010, Chongqing, China. gaojian@cqmu.edu.cn
Received: October 14, 2022
Peer-review started: October 14, 2022
First decision: December 1, 2022
Revised: December 13, 2022
Accepted: January 29, 2023
Article in press: January 29, 2023
Published online: February 14, 2023
Processing time: 119 Days and 7.1 Hours
ARTICLE HIGHLIGHTS
Research background

Esophagogastric variceal bleeding (EGVB) is a fatal complication of liver cirrhosis, which requires aggressive intervention. Prediction of bleeding risk in cirrhotic patients with esophagogastric varices (EGV) is beneficial to individualized treatment and improve prognosis. Radiomics, an emerging field, has a good performance in disease diagnosis and efficacy evaluation.

Research motivation

Currently, there is still a lack of noninvasive models that can be widely used in clinical practice to predict the risk of bleeding in liver cirrhosis.

Research objectives

Our study aimed to develop and validate a novel predictive model based on radiomics extracted from contrast-enhanced computed tomography (CT) and clinical indicators to noninvasively assess the risk of bleeding in cirrhotic patients with EGV.

Research methods

211 patients were divided into training and validation cohorts in a 7:3 ratio. Radiomics features were extracted from the portal venous phase CT images, and a radiomics signature (RadScore) was constructed through further feature dimension reduction and screening. The univariate and multivariate logistic regression analyses were preformed to select independent clinical predictors. Finally, a combined model was established based on RadScore and clinical variables. The receiver operating characteristic curves, calibration curves, clinical decision curves and clinical impact curves were applied to evaluate the performance of the model.

Research results

The RadScore was constructed from 8 radiomics features. Albumin, fibrinogen, portal vein thrombosis, aspartate aminotransferase, and spleen thickness were selected as independent predictors. The nomogram, combining RadScore and clinical variables, demonstrated good diagnostic performance in both the training and validation cohorts (area under the receiver operating characteristic curve (AUC) = 0.925 and 0.912, respectively), which outperformed existing non-invasive models such as ratio of aspartate aminotransferase to platelets and Fibrosis-4 scores (Delong test < 0.05).

Research conclusions

The combined model based on radiomics features and clinical indicators shows good predictive accuracy and can contribute to noninvasively assessing the risk of EGVB in patients with cirrhosis.

Research perspectives

Radiomics has shown good diagnostic performance in the assessment of portal hypertension and the identification of high-risk esophageal varices. Our study demonstrated that the model combined clinical variables and radiomics features has the potential utility for non-invasive prediction of EGVB. Further large-scale, multi-center prospective studies are still required to verify its performance in the future.