Value of a combined magnetic resonance imaging-based radiomics-clinical model for predicting extracapsular extension in prostate cancer: a preliminary study.

Background: Extracapsular extension (ECE) of prostate cancer (PCa) is closely related to the treatment and prognosis of patients, and radiomics has been widely used in the study of PCa. This study aimed to evaluate the value of a combined model considering magnetic resonance imaging (MRI)-based radiomics and clinical parameters for predicting ECE in PCa. Methods: A total of 392 PCa patients enrolled in this retrospective study were randomly divided into the training and validation sets at a ratio of 7:3. Radiologists assessed all lesions by Mehralivand grade. Radiomics features were extracted and selected to build a radiomics model, while clinical parameters were noted to construct the clinical model. The combined model was constructed by the integration of the radiomics model and clinical model. Meanwhile, the nomogram for predicting ECE was constructed based on the combined model. Then, the area under the receiver operating characteristic (ROC) curve (AUC), Delong test and the decision curve analysis (DCA) were used to compare the performance among the combined model, radiomics model, clinical model and Mehralivand grade. Results: The AUC of the combined model in the validation set was comparable to that of the radiomics model [AUC =0.894 (95% confidence interval (CI): 0.837-0.950) Conclusions: The combined model has a satisfactory predictive value for ECE in PCa patients compared with the clinical model, Mehralivand grade of radiologists, and the radiomics model.