Preoperative Imaging Evaluation of Endometrial Cancer in FIGO 2023.
Aki KidoYuki HimotoYasuhisa KurataSachiko MinamiguchiYuji NakamotoPublished in: Journal of magnetic resonance imaging : JMRI (2023)
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.
Keyphrases
- endometrial cancer
- computed tomography
- magnetic resonance imaging
- positron emission tomography
- high resolution
- contrast enhanced
- deep learning
- risk factors
- patients undergoing
- dual energy
- machine learning
- lymph node
- artificial intelligence
- randomized controlled trial
- oxidative stress
- convolutional neural network
- total knee arthroplasty
- lymph node metastasis
- optical coherence tomography
- mass spectrometry
- photodynamic therapy
- clinical evaluation
- single molecule
- quantum dots
- data analysis