Establishment of the radiologic tumor invasion index based on radiomics splenic features and clinical factors to predict serous invasion of gastric cancer
1.The First School of Medicine, School of Information and Engineering, Wenzhou Medical University, Wenzhou 325035, China; 2.Department of Gastrointestinal Surgery, the Second Affiliated Hospital of Wenzhou Medical University, Wenzhou 325027, China; 3.Department of Gastrointestinal Surgery, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325027, China
SHEN Ningzhe,ZHENG Jingwei,PAN Bujian, et al. Establishment of the radiologic tumor invasion index based on radiomics splenic features and clinical factors to predict serous invasion of gastric cancer[J]. JOURNAL OF WEZHOU MEDICAL UNIVERSITY, 2023, 53(1): 15-21，28.
Abstract：Objective: To construct a model that can identify serosa infiltration in gastric cancer before surgery by combining clinical data and radiological features. Methods: A total 656 patients with pathologically confirmed gastric cancer were selected from the First Affiliated Hospital of Wenzhou Medical University between January 2015 and December 2019, who were randomly divided into the validation group (262 cases) and the modeling group (394 cases). The spleen imaging data of the patients in the modeling group were collected and analyzed by lasso regression, and the serosa infiltration prediction model was constructed on the selected significant features. Patients were divided into high-risk group (238 cases) and low-risk group (418 cases) by tumor infiltration risk score according to the cut-off value under the largest Yoden index, and then univariate and multivariate Logistic regression analysis was made with other infiltration-related factors to establish a visual prediction nomogram. Results: Patients with tumor infiltration score ≤-0.335 and > -0.335 were divided respectively into low-risk group and high-risk group. The diagnostic accuracy of the modeling and validation groups was consistent (P<0.001) when verified by the validation group (P<0.001). Univariate and multivariate Logistic analysis of infiltration risk factors showed that tumor radiomic infiltration score (OR=2.9, 95%CI=2.1-4.2, P<0.001), preoperative albumin (OR=1.3, 95%CI=1.2-3.1, P=0.003), platelet-lymphocyte ratio (OR=1.8, 95%CI=1.2-2.7, P=0.004) and tumor differentiation (OR=2.6, 95%CI=1.8-3.7, P<0.001) were independent influential factors for serosa invasion. The prediction model based on these four indicators accurately predicted the risk of serosa invasion, and its AUC value was 0.733. Conclusion: Tumor infiltration score based on spleen imaging combined with other clinical factors can accurately predict the serosal invasion of gastric cancer and improve the diagnostic precision.
