Machine learning based on body composition radiomics for predicting early recurrence in colorectal cancer: a multicenter study (opens in new tab)

BackgroundEarly recurrence (ER) in colorectal cancer (CRC) leads to dismal outcomes. Current pTNM staging fails to capture the host’s systemic pathophysiological status. We developed an interpretable machine learning (ML) model based on preoperative CT body composition radiomics to predict ER in CRC.MethodsThis multicenter study enrolled 917 patients who underwent radical resection across three independent institutions, and the cohort was partitioned into a training set (n = 548) and two exte...