Deep learning model for the detection of prostate cancer and classification of clinically significant disease using multiparametric MRI in comparison to PI-RADs score.

Journal: Urologic oncology
Published Date:

Abstract

BACKGROUND: The Prostate Imaging Reporting and Data System (PI-RADS) is an established reporting scheme for multiparametric magnetic resonance imaging (mpMRI) to distinguish clinically significant prostate cancer (csPCa). Deep learning (DL) holds great potential for automating csPCa classification on mpMRI.

Authors

  • Chunguang Yang
    Research Center for Analytical Sciences, Department of Chemistry, College of Sciences, Northeastern University, Shenyang, Liaoning Province 110819, China.
  • Basen Li
    Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Yang Luan
    Clinical Medical College, Yangzhou University, Yangzhou 225009, China.
  • Shiwei Wang
    PTN Graduate Program, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, PR China.
  • Yang Bian
    Evomics Medical Technology Co., Ltd., Shanghai, China.
  • Junbiao Zhang
    Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Zefeng Wang
    CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, Shanghai 200031, China. Electronic address: wangzefeng@picb.an.cn.
  • Bo Liu
    Wuhan United Imaging Healthcare Surgical Technology Co., Ltd., Wuhan, China.
  • Xin Chen
    University of Nottingham, Nottingham, United Kingdom.
  • Marcus Hacker
    Division of Nuclear Medicine, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria.
  • Zhen Li
    PepsiCo R&D, Valhalla, NY, United States.
  • Xiang Li
    Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.
  • Zhihua Wang