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CC BY 4.0 · Journal of Gastrointestinal and Abdominal Radiology
DOI: 10.1055/s-0045-1815706
Review Article

Impact of FIGO 2023 Staging on MRI Evaluation of Endometrial Cancer: Highlighted Version

Authors

  • Seema Sud

    1   Department of Radiodiagnosis, Sir Ganga Ram Hospital, New Delhi, India

  • Ketki Mahendra Sarvankar 

    1   Department of Radiodiagnosis, Sir Ganga Ram Hospital, New Delhi, India

  • Samarjit Singh Ghuman 

    1   Department of Radiodiagnosis, Sir Ganga Ram Hospital, New Delhi, India
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Abstract

The 2023 revision of the International Federation of Gynecology and Obstetrics (FIGO) staging system for endometrial carcinoma (EC) has introduced significant updates, including refined anatomic definitions and the incorporation of molecular subtypes such as POLE mutations, mismatch repair deficiency, and p53 abnormalities. Magnetic resonance imaging (MRI) remains the preferred modality for preoperative staging of EC due to its superior soft tissue contrast and functional imaging capabilities. This review discusses the technical considerations for MRI acquisition, with particular emphasis on the impact of the revised staging system on imaging interpretation. It highlights the role of MRI in evaluating eligibility for fertility-sparing treatments and in posttreatment surveillance. Radiologists must be familiar with these changes to ensure accurate staging and optimal patient management. Lastly, it elucidates the utility of imaging biomarkers such as apparent diffusion coefficient values, tumor size, and patterns of spread as potential surrogates for histologic and molecular classification. Integrating molecular profiling with MRI interpretation represents a critical advancement toward risk-adapted therapeutic strategies in endometrial cancer.

Keywords

endometrial carcinoma - FIGO 2023 staging - magnetic resonance imaging (MRI) - molecular classification - radiogenomics


Publication History

Article published online:
16 January 2026

© 2026. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

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