Radiomics-based ensemble model predicts postoperative recurrence of gastric cancer.

ABSTRACT:

Background

Early postoperative recurrence in locally advanced gastric cancer (LAGC) severely compromises patient outcomes, yet current predictive models are inadequate due to limited generalizability and insufficient validation. This study aimed to establish and robustly validate a multimodal Radiomics-Clinical Integrated Risk Stratification Assessment (RSA) model to accurately predict early recurrence.

Methods

We retrospectively analyzed 2,516 LAGC patients from six hospitals across northern and southern China, divided into training, internal validation, and external validation cohorts. Radiomics features were extracted from portal venous-phase abdominal CT images using nnU-Net-based segmentation, followed by a hierarchical feature-selection framework integrating the mRMR a

SUBMITTER: Ding P 

PROVIDER: S-EPMC12648815 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature