Artificial intelligence-based model for lymph node metastases detection on whole slide images in bladder cancer: a retrospective, multicentre, diagnostic study.

Journal: The Lancet. Oncology
Published Date:

Abstract

BACKGROUND: Accurate lymph node staging is important for the diagnosis and treatment of patients with bladder cancer. We aimed to develop a lymph node metastases diagnostic model (LNMDM) on whole slide images and to assess the clinical effect of an artificial intelligence-assisted (AI) workflow.

Authors

  • Shaoxu Wu
    Departments of Urology, Radiology, Emergency Medicine, and Respiratory Medicine, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China.
  • Guibin Hong
    Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 107th Yanjiangxi Road, Guangzhou, China.
  • Abai Xu
    Department of Urology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
  • Hong Zeng
    School of Computer Science and Technology, Hangzhou Dianzi University, China.
  • Xulin Chen
    Cells Vision Medical Technology, Guangzhou, Guangdong, China.
  • Yun Wang
    Department of Anesthesiology, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, People's Republic of China.
  • Yun Luo
    Institute of Medicinal Plant Development, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
  • Peng Wu
    Department of Orthopedics, General Hospital of Ningxia Medical University, Yinchuan, China.
  • Cundong Liu
    Department of Urology, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China.
  • Ning Jiang
  • Qiang Dang
    Department of Urology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China.
  • Cheng Yang
    State Key Laboratory of Medicinal Chemical Biology and College of Pharmacy, Nankai University, Tianjin 300071, China.
  • Bohao Liu
    Sun Yat-sen Memorial Hospital and Department of Urology, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.
  • Runnan Shen
    Department of Urology, Sun Yat-sen University, Guangzhou, Guangdong, China.
  • Zeshi Chen
    Department of Urology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China.
  • Chengxiao Liao
    Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 107th Yanjiangxi Road, Guangzhou, China.
  • Zhen Lin
    Computer and Science School, Wuhan University, Wuhan, China.
  • Jin Wang
    Cells Vision (Guangzhou) Medical Technology Inc., Guangzhou, China. Electronic address: wangjin@cellsvision.com.
  • Tianxin Lin
    Departments of Urology, Radiology, Emergency Medicine, and Respiratory Medicine, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China. Electronic address: lintx@mail.sysu.edu.cn.