A novel model for predicting postoperative liver metastasis in R0 resected pancreatic neuroendocrine tumors: integrating computational pathology and deep learning-radiomics.

Journal: Journal of translational medicine
PMID:

Abstract

BACKGROUND: Postoperative liver metastasis significantly impacts the prognosis of pancreatic neuroendocrine tumor (panNET) patients after R0 resection. Combining computational pathology and deep learning radiomics can enhance the detection of postoperative liver metastasis in panNET patients.

Authors

  • Mengke Ma
    The People's Hospital of Liaoning Province, Command Postgraduate Training Base, Jinzhou Medical University, Shenyang, China.
  • Wenchao Gu
    Department of Diagnostic and Interventional Radiology, University of Tsukuba, Ibaraki, Japan.
  • Yun Liang
    J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, United States.
  • Xueping Han
    Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China.
  • Meng Zhang
    College of Software, Beihang University, Beijing, China.
  • Midie Xu
    Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China.
  • Heli Gao
    Department of Oncology, Fudan University Shanghai Medical College, Shanghai, China. gaoheli@fudanpci.org.
  • Wei Tang
    Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • Dan Huang
    Department of Anesthesiology, The Second Affiliated Hospital of Soochow University, Suzhou 215004, China.; Department of Anesthesiology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200127, China.