Preoperative risk assessment of invasive endometrial cancer using MRI-based radiomics: a systematic review and meta-analysis.

Journal: Abdominal radiology (New York)
Published Date: May 24, 2025

Abstract

OBJECTIVE: Image-derived machine learning (ML) is a robust and growing field in diagnostic imaging systems for both clinicians and radiologists. Accurate preoperative radiological evaluation of the invasive ability of endometrial cancer (EC) can increase the degree of clinical benefit. The present study aimed to investigate the diagnostic performance of magnetic resonance imaging (MRI)-derived artificial intelligence for accurate preoperative assessment of the invasive risk.

Authors

  • Yao Gao
    Shenzhen Institute of Building Research Co. Ltd, China.
  • Fan Liang
  • Xiaomei Tian
    Department of Radiology, Obstetrics & Gynecology Hospital of Fudan University, Yangtze River Delta Integration Demonstration Zone (QingPu), Shanghai, China.
  • GuoFu Zhang
    The Affiliated Mental Health Center of Jiangnan University, Wuxi Mental Health Center, Wuxi 214151, Jiangsu, China.
  • He Zhang
    College of Natural Resources and Environment, Northwest A&F University, Yangling, 712100, Shaanxi, PR China; Key Laboratory of Plant Nutrition and the Agri-environment in Northwest China, Ministry of Agriculture and Rural Affairs, Yangling, 712100, Shaanxi, PR China.

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