Objective To investigate the feasibility of predicting the capsular invasion in papillary thyroid carcinoma based on the support vector machine model and K-nearest neighbor model by dual-phase enhanced CT.Methods In total 160 cases from 157 patients with PTC confirmed by pathology in our hospital from January 2018 to December 2022 were retrospectively analyzed.According to the postoperative pathological results,the cases were divided into the capsular invasion group(84 cases)and the non-capsular invasion group(76 cases).The enroll cases were randomly divided into the training group(n=112)and the validation group(n=48)in a 7:3 ratio.Two machine algorithms were used to construct the models based on selected radiomic features.The models were validated internally by the validation group.Finally,the operating characteristic curve and the area under the curve were used to assess the prediction effectiveness of different models.Results In the validation group,the AUCs of the SVM model and KNN model based on venous phase were 0.752 and 0.698,the AUCs of the SVM model and KNN model based on arterial phase were 0.880 and 0.716,the AUCs of the SVM model and KNN model based on dual-phase were 0.936 and 0.764.The dual-phase model was significantly more effective in predicting the capsular invasion in papillary thyroid carcinoma than the single-phase model.Conclusion In this study,both SVM and KNN models based on enhanced CT can predict capsular invasion in papillary thyroid carcinoma to some extent,and the SVM model based on dual-phase shows the best prediction effectiveness among them,which has high application value in individualized diagnosis and treatment of papillary thyroid cancer.
万方数据
维普
