Improving Ki67 assessment concordance by the use of an artificial intelligence-empowered microscope: a multi-institutional ring study.

Journal: Histopathology
Published Date: Jun 24, 2021

Abstract

AIMS: The nuclear proliferation biomarker Ki67 plays potential prognostic and predictive roles in breast cancer treatment. However, the lack of interpathologist consistency in Ki67 assessment limits the clinical use of Ki67. The aim of this article was to report a solution utilising an artificial intelligence (AI)-empowered microscope to improve Ki67 scoring concordance.

Authors

  • Lijing Cai
    Heilongjiang Bayi Agricultural University, College of Information and Electrical Engineering, Daqing, Heilongjiang 163319, China.
  • Kezhou Yan
    AI Healthcare, Technology and Engineering Group, Tencent Inc, Tencent Building, Kejizhongyi Avenue, Hi-tech Park, Shenzhen, PR China.
  • Hong Bu
    Laboratory of Pathology Key Laboratory of Transplant Engineering and Immunology NHC, West China Hospital Sichuan University Chengdu China.
  • Meng Yue
    Department of Pathology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
  • Pei Dong
  • Xinran Wang
    Department of Pathology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
  • Lina Li
    Department of Pathology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
  • Kuan Tian
    AI Healthcare, Technology and Engineering Group, Tencent Inc, Tencent Building, Kejizhongyi Avenue, Hi-tech Park, Shenzhen, PR China.
  • Haocheng Shen
    Computing, School of Science and Engineering, University of Dundee, Dundee, UK.
  • Jun Zhang
    First School of Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China.
  • Jiuyan Shang
    Department of Pathology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
  • Shuyao Niu
    Department of Pathology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
  • Dandan Han
    School of Pharmacy, Shenyang Pharmaceutical University, Shenyang 110016, China.
  • Chen Ren
    Department of Pathology, Shenzhou Hospital of Hebei Province, Shenzhou, Hebei, China.
  • Junzhou Huang
  • Xiao Han
    College of Chemistry, Chemical Engineering and Materials Science, Collaborative Innovation Center of Functionalized Probes for Chemical Imaging in Universities of Shandong, Key Laboratory of Molecular and Nano Probes, Ministry of Education, Shandong Provincial Key Laboratory of Clean Production of Fine Chemicals, Shandong Normal University Jinan 250014 China cyzhang@sdnu.edu.cn.
  • Jianhua Yao
  • Yueping Liu
    Department of Pathology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China.

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