CT semantic features of primary gastric cancer: a preoperative predictive model for peritoneal metastasis with superior efficacy to conventional direct CT assessment

OBJECTIVES: This study aims to evaluate the utility of CT semantic features of primary Gastric Cancer(GC) compared to conventional CT assessments for predicting Peritoneal Metastasis(PM) , and to construct a preoperative predictive model. METHODS: We conducted a retrospective analysis involving 257 pathologically confirmed GC patients (92 with PM and 165 without PM), utilizing preoperative contrast-enhanced abdominal CT alongside clinicopathological data. Univariate and multivariate logistic regression analyses were performed to identify risk factors for PM, leading to the development of three predictive models: one based on primary tumor CT signs, another on peritoneal CT signs, and a combined model integrating both sets of features. RESULTS: Independent PM predictors included the primary tumor's maximum size, serosal invasion, thickness, enhancement, and the presence of ascites. The primary tumor model demonstrated superior performance (AUC=0.920) compared to the peritoneal model (AUC=0.822, p