A deep learning-based psi CT network effectively predicts early recurrence after hepatectomy in HCC patients.

Journal: Abdominal radiology (New York)
Published Date:

Abstract

BACKGROUND: Hepatocellular carcinoma (HCC) exhibits a high recurrence rate, and early recurrence significantly jeopardizes patient prognosis, necessitating reliable methods for early recurrence prediction.

Authors

  • Qianyun Yao
    The First Affiliated Hospital of Air Force Medical University, Xi'an, China.
  • Weili Jia
    The First Affiliated Hospital of Air Force Medical University, Xi'an, China.
  • Tianchen Zhang
    Department of Electrical and Computer Engineering, University of Toronto, 10 King's College Rd., Toronto, Ontario M5S 3G4, Canada.
  • Yan Chen
    Department of Respiratory and Critical Care Medicine, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.
  • Guangmiao Ding
    The First Affiliated Hospital of Shenzhen University, Shenzhen, China.
  • Zheng Dang
    The 940, Hospital of Joint Logistics Support Force of Chinese PLA, Lanzhou, China.
  • Shuai Shi
    Cardiovascular Department, Guang'anmen Hospital, China Academy of Chinese Medical Sciences.
  • Chao Chen
    Department of Neonatology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, China.
  • Shen Qu
    Endocrinology and Metabolism Center, National Metabolic Management Center, Division of Metabolic Surgery for Obesity and Diabetes, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
  • Zihao Zhao
    School of Information and Computer, Anhui Agricultural University, Hefei 230036, China.
  • Deng Pan
    Hefei National Laboratory for Physical Sciences at the Microscale, Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes, CAS Key Laboratory of Mechanical Behavior and Design of Materials, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China.
  • Wenjie Song