A prediction model based on deep learning and radiomics features of DWI for the assessment of microsatellite instability in endometrial cancer.

Journal: Cancer medicine
PMID: 39171859

Abstract

BACKGROUND: To explore the efficacy of a prediction model based on diffusion-weighted imaging (DWI) features extracted from deep learning (DL) and radiomics combined with clinical parameters and apparent diffusion coefficient (ADC) values to identify microsatellite instability (MSI) in endometrial cancer (EC).

Authors

  • Jing Wang
    Endoscopy Center, Peking University Cancer Hospital and Institute, Beijing, China.
  • Pujiao Song
    Department of Nuclear Medicine, The Affiliated Hospital of Guizhou Medical University, Guiyang, China.
  • Meng Zhang
    College of Software, Beihang University, Beijing, China.
  • Wei Liu
    Department of Radiation Oncology, Mayo Clinic, Scottsdale, AZ, United States.
  • Xi Zeng
  • Nanshan Chen
    Department of Nuclear Medicine, The Affiliated Hospital of Guizhou Medical University, Guiyang, China.
  • Yuxia Li
    Beijing Institute of Health Administration and Medical Information, Beijing 100850, China.
  • Minghua Wang
    School of Materials and Chemical Engineering, Zhengzhou University of Light Industry, No. 136, Science Avenue, Zhengzhou, 450001, China.

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