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Abstract
Magnetic resonance imaging (MRI) is central to the diagnostic algorithm for endometrial cancer (EC) as the most informative modality for assessing key prognostic factors such as the depth of myometrial invasion and local tumor extent, which are critical for treatment planning. The latest revision of the FIGO staging system (2023) stratifies risk based on factors including local extent, histological type, molecular genetic subtype, lymphovascular space invasion (LVSI), and lymph node micrometastases, which are typically determined postoperatively. The ability to preoperatively ascertain these risk factors could help optimize treatment strategies. Consequently, there is a global effort to develop new diagnostic approaches for EC based on the analysis of imaging data acquired during standard preoperative staging. Most studies evaluate the diagnostic value of radiomic features extracted via texture analysis (TA) from MRI scans of EC patients. This review synthesizes published research on the application of radiomic and radiogenomic analysis of MRI in EC diagnosis, highlighting promising results for predicting tumor histology, myometrial invasion depth, LVSI, lymph node metastasis, and molecular genetic subtype. However, it is currently not possible to determine the predictive value of specific radiomic parameters for determining the main EC prognostic factors. This is due to significant variability in the analyzed texture features, the use of diverse software applications for TA, and a lack of standardized protocols for selecting MRI sequences. Therefore, while radiomics remains a key area of scientific inquiry, its integration into clinical practice requires further study to standardize analysis protocols and validate findings.
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