Deep learning models based on multiparametric magnetic resonance imaging and clinical parameters for identifying synchronous liver metastases from rectal cancer.

Journal: BMC medical imaging
Published Date: May 19, 2025

Abstract

OBJECTIVES: To establish and validate deep learning (DL) models based on pre-treatment multiparametric magnetic resonance imaging (MRI) images of primary rectal cancer and basic clinical data for the prediction of synchronous liver metastases (SLM) in patients with Rectal cancer (RC).

Authors

  • Jing Sun
    Department of Gastroenterology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Pu-Yeh Wu
    GE Healthcare, Beijing, China.
  • Fangmin Shen
    Department of Radiology, Fujian Cancer Hospital, Fujian Medical University Cancer Hospital, Fuzhou, Fujian Province, China.
  • Xingfa Chen
    Department of Urology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China.
  • Jieqiong She
    Department of Radiation Oncology, Fujian Medical University Union Hospital, Fuzhou, Fujian, China.
  • Mingcong Luo
    Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, Fujian, China.
  • Feifei Feng
    Department of Health Toxicology, College of Public Health, Zhengzhou University, Zhengzhou, China.
  • Dechun Zheng
    Department of Radiology, Fujian Cancer Hospital, Fujian Medical University Cancer Hospital, Fuzhou, Fujian Province, China.

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