Diagnosing and grading gastric atrophy and intestinal metaplasia using semi-supervised deep learning on pathological images: development and validation study.

Journal: Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
PMID:

Abstract

OBJECTIVE: Patients with gastric atrophy and intestinal metaplasia (IM) were at risk for gastric cancer, necessitating an accurate risk assessment. We aimed to establish and validate a diagnostic approach for gastric biopsy specimens using deep learning and OLGA/OLGIM for individual gastric cancer risk classification.

Authors

  • Shuangshuang Fang
    Beijing Key Laboratory of Functional Gastrointestinal Disorders Diagnosis and Treatment of Traditional Chinese Medicine; Department of Gastroenterology, Wangjing Hospital, China Academy of Chinese Medical Sciences, No. 6, Zhonghuan South Road, Wangjing, Beijing, 100102, China.
  • Zhenyu Liu
    School of Electronic Information, Hangzhou Dianzi University, Hangzhou 310018, China.
  • Qi Qiu
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, China.
  • Zhenchao Tang
  • Yang Yang
    Department of Gastrointestinal Surgery, The Third Hospital of Hebei Medical University, Shijiazhuang, China.
  • Zhongsheng Kuang
    Department of Pathology, The First Affiliated Hospital of Guangdong University of Traditional Chinese Medicine, Guangzhou, 510405, China.
  • Xiaohua Du
    Department of Pathology, Guangdong Provincial Hospital of Traditional Chinese Medicine, Guangzhou, 510120, China.
  • Shanshan Xiao
    Department of Pathology, The First Affiliated Hospital of Guangdong University of Traditional Chinese Medicine, Guangzhou, 510405, China.
  • Yanyan Liu
    Linyi City Lanshan Economic and Information Technology Bureau, Linyi, Shandong, China.
  • Yuanbin Luo
    Department of Pathology, Gansu Provincial Hospital of Traditional Chinese Medicine, Lanzhou, 730050, China.
  • Liping Gu
    Department of Endocrinology and Metabolism, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai, China.
  • Li Tian
    Department of Gastroenterology, Third Xiangya Hospital, Central South University, Changsha 410013, China. tianlixy3@csu.edu.cn.
  • Xiaoxia Liang
    Natural Medicine Research Center, Pharmacy Department, Sichuan Agricultural University, Chengdu 611130, PR China. Electronic address: liangxiaoxia@sicau.edu.cn.
  • Guiling Fan
    Department of Pathology, Shanxi Provincial Hospital of Traditional Chinese Medicine, Taiyuan, 030012, China.
  • Yu Zhang
    College of Marine Electrical Engineering, Dalian Maritime University, Dalian, China.
  • Ping Zhang
    Department of Computer Science and Engineering, The Ohio State University, USA.
  • Weixun Zhou
    Department of Pathology, Peking Union Medical College Hospital, 100005, Beijing, China.
  • Xiuli Liu
    Washington University School of Medicine, St Louis, MO, USA.
  • Jie Tian
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
  • Wei Wei
    Dept. Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, USA.