Retrospective imaging studies of gastric cancer: Study protocol clinical trial (SPIRIT Compliant).

Journal: Medicine
Published Date: Feb 1, 2020

Abstract

INTRODUCTION: Peritoneal metastasis (PM) is a frequent condition in patients presenting with gastric cancer, especially in younger patients with advanced tumor stages. Computer tomography (CT) is the most common noninvasive modality for preoperative staging in gastric cancer. However, the challenges of limited CT soft tissue contrast result in poor CT depiction of small peritoneal tumors. The sensitivity for detecting PM remains low. About 16% of PM are undetected. Deep learning belongs to the category of artificial intelligence and has demonstrated amazing results in medical image analyses. So far, there has been no deep learning study based on CT images for the diagnosis of PM in gastric cancer.

Authors

  • Zixing Huang
    Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province 610000, China.
  • Dan Liu
    Department of Bioengineering, Temple University, Philadelphia, PA, United States.
  • Xinzu Chen
    Department of Gastrointestinal Surgery and Laboratory of Gastric Cancer, West China Hospital, Sichuan University, Chengdu.
  • Pengxin Yu
    Institute of Advanced Research, Infervision, Beijing, China.
  • Jiangfen Wu
    Department of Biomedical Engineering, College of Automation, Nanjing University of Aeronautics and Astronautics, No. 29, Yudao St., Qinhuai District, Nanjing, 210016, Jiangsu Province, China, wjfyunzhu@163.com.
  • Bin Song
    Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, China.
  • Jiankun Hu
  • Bing Wu
    Department of Radiology, West China Hospital.

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