Preoperative assessment of high-grade endometrial cancer using a radiomic signature and clinical indicators.

To develop and validate a radiomics-based combined model (Model) to predict the pathological grade of endometrial cancer. A total of 403 endometrial cancer patients from two independent centers were enrolled as training, internal validation and external validation sets. Radiomic features were extracted from T2-weighted images, apparent diffusion coefficient map and contrast-enhanced 3D volumetric interpolated breath-hold examination images. Compared with the clinical model and radiomics model, Model showed superior performance; the areas under the receiver operating characteristic curves were 0.920 (95% CI: 0.864-0.962), 0.882 (95% CI: 0.779-0.955) and 0.881 (95% CI: 0.815-0.939) for the training, internal validation and external validation sets, respectively. Model, which incorporated clinical and radiomic features, exhibited excellent performance in the prediction of high-grade endometrial cancer.