Different multiparametric MRI-based radiomics models for differentiating stage IA endometrial cancer from benign endometrial lesions: A multicenter study

In the study, age and irregular vaginal bleeding were the valid predictive parameters in clinical model. On the basis of several common machine learning algorithms, the diverse multiparametric MRI-based radiomics models were developed to differentiate stage IA EC from benign endometrial lesions, and LR algorithm model were selected as the optimal radiomics model with the highest AUC and accuracy. Compared with clinical model and radiologist, the optimal radiomics model and the compositive models combining clinical parameters with radiomics features, like the nomogram, stacking model, and ensemble model showed better diagnostic performance and achieved good clinical net benefits. The nomogram had a higher AUC than that of the optimal radiomics model, and revealed more stable discrimination efficiency and better generalization ability than stacking and ensemble modals.