Retrospective Study
Copyright ©The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. May 21, 2025; 31(19): 104563
Published online May 21, 2025. doi: 10.3748/wjg.v31.i19.104563
Development and validation of a radiomics-based prediction model for variceal bleeding in patients with Budd-Chiari syndrome-related gastroesophageal varices
Ze-Dong Wang, Hui-Jie Nan, Su-Xin Li, Lu-Hao Li, Zhao-Chen Liu, Hua-Hu Guo, Lin Li, Sheng-Yan Liu, Hai Li, Yan-Liang Bai, Xiao-Wei Dang
Ze-Dong Wang, Su-Xin Li, Lu-Hao Li, Zhao-Chen Liu, Hua-Hu Guo, Lin Li, Sheng-Yan Liu, Xiao-Wei Dang, Department of Hepatopancreatobiliary Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan Province, China
Ze-Dong Wang, Su-Xin Li, Lu-Hao Li, Zhao-Chen Liu, Hua-Hu Guo, Lin Li, Sheng-Yan Liu, Xiao-Wei Dang, Key Laboratory of Precision Diagnosis and Treatment in General Surgical (Hepatobiliary and Pancreatic) Diseases of Health Commission of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan Province, China
Ze-Dong Wang, Su-Xin Li, Lu-Hao Li, Zhao-Chen Liu, Hua-Hu Guo, Lin Li, Sheng-Yan Liu, Xiao-Wei Dang, Henan Province Engineering Research Center of Minimally Invasive Diagnosis and Treatment of Hepatobiliary and Pancreatic Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan Province, China
Ze-Dong Wang, Su-Xin Li, Lu-Hao Li, Zhao-Chen Liu, Hua-Hu Guo, Lin Li, Sheng-Yan Liu, Xiao-Wei Dang, Budd-Chiari Syndrome Diagnosis and Treatment Center of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan Province, China
Hui-Jie Nan, Yan-Liang Bai, Department of Hematology, Zhengzhou University People's Hospital and Henan Provincial People's Hospital, Zhengzhou 450003, Henan Province, China
Hai Li, Department of Hepatopancreatobiliary Surgery, Zhengzhou University People's Hospital and Henan Provincial People's Hospital, Zhengzhou 450003, Henan Province, China
Co-first authors: Ze-Dong Wang and Hui-Jie Nan.
Co-corresponding authors: Yan-Liang Bai and Xiao-Wei Dang.
Author contributions: Wang ZD and Nan HJ contributed equally to this work as co-first authors; they were responsible for designing the study, collecting and analyzing data, and writing the manuscript; Dang XW and Bai YL contributed equally by guiding the overall content and ensuring the scientific rigor of the article as co-corresponding authors; Dang XW is designated as the primary corresponding author for journal communications; Li SX, Li LH, Liu ZC, Guo HH, Li L, Liu SY and Li H provided technical support; all authors have read and approve the final manuscript.
Supported by Natural Science Foundation of Henan Province, China, No. 232300420232; and Henan Provincial Key Research and Development Project, No. 231111313500.
Institutional review board statement: The study was reviewed and approved by the Ethics Committee of the First Affiliated Hospital of Zhengzhou University (No. 2021-KY-1137-002).
Informed consent statement: As a retrospective observational study, the requirement for informed consent was waived. To ensure confidentiality, all private patient information was deidentified before analysis.
Conflict-of-interest statement: The authors declare that the research was conducted in the absence of any commercial or financial relationships.
Data sharing statement: The data supporting the findings of this study are included in the article and its supplementary materials. Further inquiries can be directed to the corresponding authors.
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: Xiao-Wei Dang, PhD, Chief Physician, Professor, Department of Hepatopancreatobiliary Surgery, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe East Road, Erqi District, Zhengzhou 450052, Henan Province, China. dangxw1001@zzu.edu.cn
Received: December 28, 2024
Revised: March 24, 2025
Accepted: April 27, 2025
Published online: May 21, 2025
Processing time: 147 Days and 21.3 Hours
Abstract
BACKGROUND

Budd-Chiari syndrome (BCS) is caused by obstruction of the hepatic veins or suprahepatic inferior vena cava, leading to portal hypertension and the development of gastroesophageal varices (GEVs), which are associated with an increased risk of bleeding. Existing risk models for variceal bleeding in cirrhotic patients have limited applicability to BCS due to differences in pathophysiology. Radiomics, as a noninvasive technique, holds promise as a tool for more accurate prediction of bleeding risk in BCS-related GEVs.

AIM

To develop and validate a personalized risk model for predicting variceal bleeding in BCS patients with GEVs.

METHODS

We retrospectively analyzed clinical data from 444 BCS patients with GEVs in two centers. Radiomic features were extracted from portal venous phase computed tomography (CT) scans. A training cohort of 334 patients was used to develop the model, with 110 patients serving as an external validation cohort. LASSO Cox regression was used to select radiomic features for constructing a radiomics score (Radscore). Univariate and multivariate Cox regression identified independent clinical predictors. A combined radiomics + clinical (R + C) model was developed using stepwise regression. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analysis (DCA), with external validation to evaluate generalizability.

RESULTS

The Radscore comprised four hepatic and six splenic CT features, which predicted the risk of variceal bleeding. Multivariate analysis identified invasive treatment to relieve hepatic venous outflow obstruction, anticoagulant therapy, and hemoglobin levels as independent clinical predictors. The R + C model achieved C-indices of 0.906 (training) and 0.859 (validation), outperforming the radiomics and clinical models alone (AUC: training 0.936 vs 0.845 vs 0.823; validation 0.876 vs 0.712 vs 0.713). DCA showed higher clinical net benefit across the thresholds. The model stratified patients into low-, medium- and high-risk groups with significant differences in bleeding rates (P < 0.001). An online tool is available at https://bcsvh.shinyapps.io/BCS_Variceal_Bleeding_Risk_Tool/.

CONCLUSION

We developed and validated a novel radiomics-based model that noninvasively and conveniently predicted risk of variceal bleeding in BCS patients with GEVs, aiding early identification and management of high-risk patients.

Keywords: Budd-Chiari syndrome; Gastroesophageal varices; Variceal bleeding; Radiomics; Prognostic model

Core Tip: This study develops a personalized, noninvasive predictive model for variceal bleeding risk in Budd-Chiari syndrome (BCS) patients with gastroesophageal varices. By combining radiomic features from computed tomography imaging with clinical data, the model demonstrated superior predictive performance over traditional approaches, offering a promising tool for early risk assessment and improving patient management in BCS.