Preoperative Imaging Evaluation of Endometrial Cancer in FIGO 2023

Aki Kido*, Yuki Himoto, Yasuhisa Kurata, Sachiko Minamiguchi, Yuji Nakamoto

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

7 Scopus citations

Abstract

The staging of endometrial cancer is based on the International Federation of Gynecology and Obstetrics (FIGO) staging system according to the examination of surgical specimens, and has revised in 2023, 14 years after its last revision in 2009. Molecular and histological classification has incorporated to new FIGO system reflecting the biological behavior and prognosis of endometrial cancer. Nonetheless, the basic role of imaging modalities including ultrasound, computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography, as a preoperative assessment of the tumor extension and also the evaluation points in CT and MRI imaging are not changed, other than several point of local tumor extension. In the field of radiology, it has also undergone remarkable advancement through the rapid progress of computational technology. The application of deep learning reconstruction techniques contributes the benefits of shorter acquisition time or higher quality. Radiomics, which extract various quantitative features from the images, is also expected to have the potential for the quantitative prediction of risk factors such as histological types and lymphovascular space invasion, which is newly included in the new FIGO system. This article reviews the preoperative imaging diagnosis in new FIGO system and recent advances in imaging analysis and their clinical contributions in endometrial cancer. Evidence Level: 4. Technical Efficacy: Stage 3.

Original languageEnglish
Pages (from-to)1225-1242
Number of pages18
JournalJournal of Magnetic Resonance Imaging
Volume60
Issue number4
DOIs
StatePublished - 2024/10

Keywords

  • MR imaging diagnosis
  • endometrial cancer
  • radiomics

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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