Detection and subtyping of hepatic echinococcosis from plain CT images with deep learning: a retrospective, multicentre study.

Journal: The Lancet. Digital health
PMID: 37770335

Abstract

BACKGROUND: Hepatic echinococcosis is a severe endemic disease in some underdeveloped rural areas worldwide. Qualified physicians are in short supply in such areas, resulting in low rates of accurate diagnosis of this condition. In this study, we aimed to develop and evaluate an artificial intelligence (AI) system for automated detection and subtyping of hepatic echinococcosis using plain CT images with the goal of providing interpretable assistance to radiologists and clinicians.

Authors

  • Zhan Wang
    Interdisciplinary Research Center of Smart Sensor, Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China.
  • Haiyang Bian
    MOE Key Laboratory of Bioinformatics and Bioinformatics Division of BNRIST, Department of Automation, Tsinghua University, Beijing 100084, China.
  • Jiaqi Li
    Department of Critical Care Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, 200120, People's Republic of China.
  • Jin Xu
    Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE, and School of Statistics, East China Normal University, Shanghai, China.
  • Haining Fan
    Department of Hepatopancreatobiliary Surgery, Qinghai University Affiliated Hospital, Xining, China.
  • Xinze Wu
    School of Pharmacy, Shenyang Medical College, Shenyang 110034, People's Republic of China.
  • Yuntai Cao
    Department of Radiology, Qinghai University Affiliated Hospital, Xining, China.
  • Bin Guo
  • Xiaolei Xu
    Department of Biochemistry and Molecular Biology, Division of Cardiovascular Diseases, Mayo Clinic, Rochester, MN 55905, USA. xu.xiaolei@mayo.edu.
  • Haijiu Wang
    Department of Hepatopancreatobiliary Surgery, Qinghai University Affiliated Hospital, Xining, China.
  • Lingqiang Zhang
    Department of Hepatopancreatobiliary Surgery, Qinghai University Affiliated Hospital, Xining, China.
  • Hu Zhou
    Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China.
  • Jianfeng Fan
    Department of Radiology, Zhenping People's Hospital, Nanyang, China.
  • Youyou Ren
    Department of Radiology, Nanyang Central Hospital, Nanyang, China.
  • Yunping Geng
    Department of Radiology, Nanyang Central Hospital, Nanyang, China.
  • Xiaobin Feng
    Hepato-pancreato-biliary Center, Beijing Tsinghua Changgung Hospital, Beijing, China.
  • Luming Li
    National Engineering Laboratory for Neuromodulation, Tsinghua University, Beijing, China.
  • Lei Wei
    MOE Key Laboratory of Bioinformatics and Bioinformatics Division of BNRIST, Department of Automation, Tsinghua University, Beijing 100084, China.
  • Xuegong Zhang
    MOE Key Laboratory of Bioinformatics and Bioinformatics Division of BNRIST, Department of Automation, Tsinghua University, Beijing 100084, China.

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