Skip to main content

ORIGINAL RESEARCH article

Front. Med.
Sec. Hepatobiliary Diseases
Volume 11 - 2024 | doi: 10.3389/fmed.2024.1308435
This article is part of the Research Topic Treatment and Prognostic Assessment of Liver Cirrhosis and Its Complications, Volume II View all 13 articles

A clinical-radiomics nomogram for the prediction of the risk of upper gastrointestinal bleeding in patients with decompensated cirrhosis

Provisionally accepted
Zhichun Li Zhichun Li 1Qian He Qian He 1Xiao Yang Xiao Yang 1Tingting Zhu Tingting Zhu 1Xinghui Li Xinghui Li 1Yan Lei Yan Lei 1Wei Tang Wei Tang 1*Song Peng Song Peng 2
  • 1 Affiliated Hospital of North Sichuan Medical College, Nanchong, China
  • 2 Department of Radiology, Chongqing Health Center for Women and Children, Chongqing, Chongqing, China

The final, formatted version of the article will be published soon.

    Objective: To develop a model that integrates radiomics features and clinical factors to predict upper gastrointestinal bleeding (UGIB) in patients with decompensated cirrhosis.: 104 decompensated cirrhosis patients with UGIB and 104 decompensated cirrhosis patients without UGIB were randomized according to a 7:3 ratio into a training cohort (n=145) and a validation cohort (n=63). Radiomics features of the abdominal skeletal muscle area (SMA) were extracted from the cross-sectional image at the largest level of the third lumbar vertebrae (L3) on the abdominal unenhanced multi-detector computer tomography (MDCT) images. Clinical-radiomics nomogram were constructed by combining a radiomics signature (Rad score) with clinical independent risk factors associated with UGIB. Nomogram performance was evaluated in calibration, discrimination, and clinical utility. Results: The radiomics signature was built using 11 features. Plasma prothrombin time (PT), sarcopenia, and Rad score were independent predictors of the risk of UGIB in patients with decompensated cirrhosis. The clinical-radiomics nomogram performed well in both the training cohort (AUC, 0.902; 95% CI, 0.850-0.954) and the validation cohort (AUC, 0.858; 95% CI, 0.762-0.953) compared with the clinical factor model and the radiomics model and displayed excellent calibration in the training cohort. Decision curve analysis (DCA) demonstrated that the predictive 2 efficacy of the clinical-radiomics nomogram model was superior to that of the clinical and radiomics model. Conclusion: Clinical-radiomics nomogram that combines clinical factors and radiomics features has demonstrated favorable predictive effects in predicting the occurrence of UGIB in patients with decompensated cirrhosis. This helps in early diagnosis and treatment of the disease, warranting further exploration and research.

    Keywords: Liver Cirrhosis, upper gastrointestinal bleeding, Sarcopenia, MDCT, Radiomics, nomogram

    Received: 06 Oct 2023; Accepted: 22 Jul 2024.

    Copyright: © 2024 Li, He, Yang, Zhu, Li, Lei, Tang and Peng. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Wei Tang, Affiliated Hospital of North Sichuan Medical College, Nanchong, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.