Detecting Adverse Pathology of Prostate Cancer With a Deep Learning Approach Based on a 3D Swin-Transformer Model and Biparametric MRI: A Multicenter Retrospective Study.

Journal: Journal of magnetic resonance imaging : JMRI
Published Date:

Abstract

BACKGROUND: Accurately detecting adverse pathology (AP) presence in prostate cancer patients is important for personalized clinical decision-making. Radiologists' assessment based on clinical characteristics showed poor performance for detecting AP presence.

Authors

  • Litao Zhao
    School of Engineering Medicine, Beihang University, Beijing, 100191, China.
  • Jie Bao
    Pacific Northwest National Laboratory, Richland, WA, United States.
  • Ximing Wang
  • Xiaomeng Qiao
    Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
  • Junkang Shen
    Department of Radiology, The Second Affiliated Hospital of Soochow University, Suzhou, 215004, Jiangsu, China.
  • Yueyue Zhang
    Department of Radiology, The Second Affiliated Hospital of Soochow University, Suzhou, 215004, Jiangsu, China.
  • Pengfei Jin
    College of Environment and Plant Protection, Hainan University, Haikou 570228, China.
  • Yanting Ji
    Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, 215006, Jiangsu, China.
  • Ji Zhang
    Department of Neurology, Xiangya Hospital, Central South University, Jiangxi, Nanchang, 330006, Jiangxi, China.
  • Yueting Su
    Department of Radiology, The People's Hospital of Taizhou, Taizhou, 225399, Jiangsu, China.
  • Libiao Ji
    Department of Radiology, Changshu No.1 People's Hospital, Changshu, 215501, Jiangsu, China.
  • Zhenkai Li
    Department of Radiology, Suzhou Kowloon Hospital, Shanghai Jiaotong University School of Medicine, Suzhou, 215028, Jiangsu, China.
  • Jian Lu
    Key Laboratory of Microelectronic Devices & Integrated Technology, Institute of Microelectronics, Chinese Academy of Sciences, Beijing 100029, China.
  • Chunhong Hu
    Department of Oncology, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China.
  • Hailin Shen
    Department of Radiology, Suzhou Kowloon Hospital, Shanghai Jiaotong University School of Medicine, Suzhou, 215028, Jiangsu, China. hailinshen@163.com.
  • Jie Tian
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
  • Jiangang Liu
    School of Computer and Information Technology, Beijing Jiaotong University, Beijing, 100044, China.