Intralesional and perilesional radiomics strategy based on different machine learning for the prediction of international society of urological pathology grade group in prostate cancer.

Journal: BMC medical imaging
Published Date:

Abstract

OBJECTIVE: To develop and evaluate a intralesional and perilesional radiomics strategy based on different machine learning model to differentiate International Society of Urological Pathology (ISUP) grade > 2 group and ISUP ≤ 2 prostate cancers (PCa).

Authors

  • Zhiping Li
    Department of Clinical Pharmacy, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, China.
  • Liqin Yang
    Academy for Engineering and Technology, Fudan University, Shanghai, China.
  • Ximing Wang
  • Huijing Xu
    Department of Radiology, Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, China.
  • Wen Chen
    School of Cyber Science and Engineering, Sichuan University, Chengdu, Sichuan, China.
  • Shuchao Kang
    Department of Radiology, Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, China.
  • Yasheng Huang
    Department of Urology, Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, China.
  • Chang Shu
    Department of Pharmaceutical Analysis, School of Pharmacy, China Pharmaceutical University, Nanjing 211198, China.
  • Feng Cui
    Thomas H. Gosnell School of Life Sciences, Rochester Institute of Technology, 84 Lomb Memorial Drive, Rochester, New York, 14623, USA.
  • Yongsheng Zhang
    Department of Radiology, Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, China.