[Other] Updated ESUR Guidelines for Endometrial Cancer: integrating MRI with the 2023 FIGO Staging Revolution" Copy

Objectives: To summarize the key updates introduced in the 2023 International Federation of Gynecology and Obstetrics (FIGO) classification for endometrial cancer (EC), and to highlight the role of MRI in aligning with these changes for improved staging and patient management.

Materials and methods: A review of the updated 2023 FIGO classification, which integrates molecular profiling and histopathological criteria, was conducted. Additionally, the revised European Society of Urogenital Radiology (ESUR) MRI recommendations were analyzed to assess their alignment with the new FIGO framework, focusing on their role in evaluating myometrial invasion (MI) and cervical stromal involvement.

Results: The updated FIGO classification incorporates molecular data to refine risk stratification and staging accuracy. MRI continues to play a pivotal role in distinguishing between stages, mapping disease extent, and guiding surgical planning. The updated ESUR recommendations emphasize standardized MRI protocols, particularly the use of multiphase contrast-enhanced imaging, to improve diagnostic confidence in assessing MI.

Conclusion: The integration of molecular classification into FIGO staging, supported by standardized and advanced MRI protocols as recommended by ESUR, enhances the management of endometrial cancer.

Key points: Question The 2023 FIGO update integrates molecular profiling into endometrial cancer staging, requiring MRI adaptations to improve accuracy in assessing disease extent, including myometrial invasion. Findings Updated ESUR MRI guidelines emphasize multiphase contrast-enhanced imaging, structured reporting, and integration with FIGO 2023 classification, enhancing diagnostic precision for staging and treatment planning. Clinical relevance Standardized MRI protocols aligned with FIGO 2023 system improve endometrial cancer staging, guiding optimal surgical and therapeutic strategies, reducing diagnostic variability, and enhancing patient outcomes through individualized risk stratification and personalized treatment.