Machine learning-based multiparametric MRI radiomics for predicting the aggressiveness of papillary thyroid carcinoma.

Journal: European journal of radiology
Published Date:

Abstract

PURPOSE: To investigate the predictive capability of machine learning-based multiparametric magnetic resonance (MR) imaging radiomics for evaluating the aggressiveness of papillary thyroid carcinoma (PTC) preoperatively.

Authors

  • Hao Wang
    Department of Cardiology, Second Medical Center, Chinese PLA General Hospital, Beijing, China.
  • Bin Song
    Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, China.
  • Ningrong Ye
    Department of Diagnostic Radiology, City of Hope National Medical Center, Duarte, CA, United States.
  • Jiliang Ren
    Department of Radiology, Ninth People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
  • Xilin Sun
    Department of Radiology, Minhang Hospital, Fudan University, Shanghai, China.
  • Zedong Dai
    Department of Radiology, Minhang Hospital, Fudan University, Shanghai, China.
  • Yuan Zhang
    Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Bihong T Chen
    Department of Diagnostic Radiology, City of Hope National Medical Center, Duarte, CA, United States. Electronic address: Bechen@coh.org.