Contrast-enhanced ultrasound-based AI model for multi-classification of focal liver lesions.

Journal: Journal of hepatology
Published Date:

Abstract

BACKGROUND & AIMS: Accurate multi-classification is a prerequisite for appropriate management of focal liver lesions (FLLs). Ultrasound is the most common imaging examination but lacks accuracy. Contrast-enhanced ultrasound (CEUS) offers better performance but is highly dependent on operator experience. Therefore, we aimed to develop a CEUS-based artificial intelligence (AI) model for FLL multi-classification and evaluate its performance in multicenter clinical tests.

Authors

  • Wenzhen Ding
    Department of Interventional Ultrasound, Chinese PLA General Hospital, Beijing 100853, China.
  • Yaqing Meng
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.
  • Jun Ma
    State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150090, China.
  • Chuan Pang
    Department of Interventional Ultrasound, Chinese PLA General Hospital, Beijing 100853, China.
  • Jiapeng Wu
    Department of Interventional Ultrasound, Chinese PLA General Hospital, Beijing 100853, China.
  • Jie Tian
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
  • Jie Yu
    Institute of Animal Nutrition, Sichuan Agricultural University, Key Laboratory for Animal Disease-Resistance Nutrition of China Ministry of Education, Key Laboratory of Animal Disease-resistant Nutrition and Feed of China Ministry of Agriculture and Rural Affairs, Key Laboratory of Animal Disease-resistant Nutrition of Sichuan Province, Ya'an, 625014, China.
  • Ping Liang
    Department of Pharmacy, The Fourth Hospital of Hebei Medical University Shijiazhuang 050000, Hebei, China.
  • Kun Wang
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.