Predicting peritoneal recurrence and disease-free survival from CT images in gastric cancer with multitask deep learning: a retrospective study.

Journal: The Lancet. Digital health
Published Date: May 1, 2022

Abstract

BACKGROUND: Peritoneal recurrence is the predominant pattern of relapse after curative-intent surgery for gastric cancer and portends a dismal prognosis. Accurate individualised prediction of peritoneal recurrence is crucial to identify patients who might benefit from intensive treatment. We aimed to develop predictive models for peritoneal recurrence and prognosis in gastric cancer.

Authors

  • Yuming Jiang
    Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, China.
  • Zhicheng Zhang
  • Qingyu Yuan
    Nanfang PET Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China.
  • Wei Wang
    State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau 999078, China.
  • Hongyu Wang
    School of Information Science and Technology, Northwest University, Xi'an, Shaanxi, China.
  • Tuanjie Li
    Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, China. gzliguoxin@163.com caishirong@yeah.net ehbhltj@hotmail.com keekee77@126.com.
  • Weicai Huang
    Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, China.
  • Jingjing Xie
    Beijing University of Posts and Telecommunications, China.
  • Chuanli Chen
    Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China.
  • Zepang Sun
    Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, China.
  • Jiang Yu
    Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, China.
  • Yikai Xu
  • George A Poultsides
    Department of Surgery, Stanford University, Stanford, CA, USA.
  • Lei Xing
    Department of Radiation Oncology, Stanford University, CA, USA.
  • Zhiwei Zhou
    Interdisciplinary Research Center on Biology and Chemistry, and Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 200032, PR China; University of Chinese Academy of Sciences, Beijing 100049, PR China.
  • Guoxin Li
    Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, China. gzliguoxin@163.com caishirong@yeah.net ehbhltj@hotmail.com keekee77@126.com.
  • Ruijiang Li
    Global Station for Quantum Medical Science and Engineering, Global Institution for Collaborative Research and Education (GI-CoRE), Proton Beam Therapy Center, North 14 West 5 Kita-ku, Sapporo, Hokkaido, 060-8648, Japan.

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