Radiomics: a Novel CT-Based Method of Predicting Postoperative Recurrence in Ovarian Cancer.

In order to predict the 3-year recurrence of advanced ovarian cancer before surgery, we retrospective collected 94 patients to analyze by using a novel radiomics method. A total of 575 3D imaging features used for radiomics analysis were extracted, and 7 features were selected from computed tomography (CT) images that were most strongly associated with 3-year clinical recurrence-free survival (CRFS) probability to build a radiomics signature. The area under the Receiver Operating Characteristic (ROC) curve (AUC) of 0.8567 (95% CI: 0.7251-0.9498) and 0.8533 (95% CI: 0.7231-0.9671) were obtained in the training cohort and validation cohort with the logistic regression classification model respectively. Experimental results show that CT-based radiomics features were closely associated with the recurrence of advanced ovarian cancer. It is possible to prejudge the recurrence of ovarian cancer before surgery.