Deep learning for colorectal cancer detection in contrast-enhanced CT without bowel preparation: a retrospective, multicentre study.

Journal: EBioMedicine
Published Date:

Abstract

BACKGROUND: Contrast-enhanced CT scans provide a means to detect unsuspected colorectal cancer. However, colorectal cancers in contrast-enhanced CT without bowel preparation may elude detection by radiologists. We aimed to develop a deep learning (DL) model for accurate detection of colorectal cancer, and evaluate whether it could improve the detection performance of radiologists.

Authors

  • Lisha Yao
    Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, 510080, China.
  • Suyun Li
    Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
  • Quan Tao
    Department of Rehabilitation Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
  • Yun Mao
    Department of Imaging, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
  • Jie Dong
    Department of Urology, Eastern Theater Command General Hospital, Nanjing,Jiangsu 210002, Chinia.
  • Cheng Lu
    Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, 100700, People's Republic of China. lv_cheng0816@163.com.
  • Chu Han
  • Bingjiang Qiu
    3D Lab, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713GZ, Groningen, The Netherlands. Department of Radiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713GZ, Groningen, The Netherlands.
  • Yanqi Huang
    Department of Radiology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan Er Road, Guangzhou, 510080, China.
  • Xin Huang
    Department of ophthalmology, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, China.
  • Yanting Liang
    Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China; Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, China; School of Medicine, South Medical University, Guangzhou, China.
  • Huan Lin
    Department of Radiology, Zhujiang Hospital of Southern Medical University, No. 253, Gong Ye Da Dao Zhong, Guangzhou, Guangdong, 510280, People's Republic of China.
  • Yongmei Guo
    Department of Radiology, Guangzhou First People's Hospital, South China University of Technology, Guangzhou, China.
  • Yingying Liang
    Department of Ophthalmology, Guangdong Provincial People's Hospital; Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China.
  • Yizhou Chen
    School of Computer Science and Artificial Intelligence, Wuhan University of Technology, Wuhan 430070, China.
  • Jie Lin
    Department of Reproductive Medicine, Zigong Hospital of Women and Children Health Care, Zigong, China.
  • Enyan Chen
    Department of Radiology, Puning People's Hospital, Southern Medical University, Jieyang, China.
  • Yanlian Jia
    Department of Radiology, Liaobu Hospital of Guangdong, Dongguan, China.
  • ZhiHong Chen
    College of Information Technology and Engineering, Chengdu University, Chengdu, China.
  • Bochi Zheng
    Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China.
  • Tong Ling
    Department of Gastrointestinal Surgery, Guangxi Medical University Cancer Hospital, Guangxi, China.
  • Shunli Liu
    Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, 266003, Shandong, China.
  • Tong Tong
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
  • Wuteng Cao
    Department of Colorectal Surgery, Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Department of Radiology, The Sixth Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China.
  • Ruiping Zhang
    State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100050, China.
  • Xin Chen
    University of Nottingham, Nottingham, United Kingdom.
  • Zaiyi Liu
    Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.