CT-Based Radiomics Score Can Accurately Predict Esophageal Variceal Rebleeding in Cirrhotic Patients

Front Med (Lausanne). 2021 Nov 4:8:745931. doi: 10.3389/fmed.2021.745931. eCollection 2021.

Abstract

Purpose: This study aimed to develop a radiomics score (Rad-score) extracted from liver and spleen CT images in cirrhotic patients to predict the probability of esophageal variceal rebleeding. Methods: In total, 173 cirrhotic patients were enrolled in this retrospective study. A total of 2,264 radiomics features of the liver and spleen were extracted from CT images. Least absolute shrinkage and selection operator (LASSO) Cox regression was used to select features and generate the Rad-score. Then, the Rad-score was evaluated by the concordance index (C-index), calibration curves, and decision curve analysis (DCA). Kaplan-Meier analysis was used to assess the risk stratification ability of the Rad-score. Results: Rad-scoreLiver, Rad-scoreSpleen, and Rad-scoreLiver-Spleen were independent risk factors for EV rebleeding. The Rad-scoreLiver-Spleen, which consisted of ten features, showed good discriminative performance, with C-indexes of 0.853 [95% confidence interval (CI), 0.776-0.904] and 0.822 (95% CI, 0.749-0.875) in the training and validation cohorts, respectively. The calibration curve showed that the predicted probability of rebleeding was very close to the actual probability. DCA verified the usefulness of the Rad-scoreLiver-Spleen in clinical practice. The Rad-scoreLiver-Spleen showed good performance in stratifying patients into high-, intermediate- and low-risk groups in both the training and validation cohorts. The C-index of the Rad-scoreLiver-Spleen in the hepatitis B virus (HBV) cohort was higher than that in the non-HBV cohort. Conclusion: The radiomics score extracted from liver and spleen CT images can predict the risk of esophageal variceal rebleeding and stratify cirrhotic patients accordingly.

Keywords: computed tomography; esophageal variceal rebleeding; non-invasive; portal hypertension; radiomics.