Predicting meningioma grades and pathologic marker expression via deep learning.

Journal: European radiology
Published Date:

Abstract

OBJECTIVES: To establish a deep learning (DL) model for predicting tumor grades and expression of pathologic markers of meningioma.

Authors

  • Jiawei Chen
  • Yanping Xue
    Department of Radiology, Beijing Chaoyang Hospital Affiliated to Capital Medical University, Beijing, China.
  • Leihao Ren
    Department of Neurosurgery of Huashan Hospital, State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science and Institutes of Brain Science, Fudan University, Shanghai, China.
  • Kun Lv
    Departments of1Radiology and.
  • Peng Du
    Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.
  • Haixia Cheng
    National Center for Neurological Disorders, Huashan Hospital Fudan University, Shanghai, China.
  • Shuchen Sun
  • Lingyang Hua
    Department of Neurosurgery of Huashan Hospital, State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science and Institutes of Brain Science, Fudan University, Shanghai, China.
  • Qing Xie
    Department of Infectious Disease, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Ruiqi Wu
    Department of Neurosurgery of Huashan Hospital, State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science and Institutes of Brain Science, Fudan University, Shanghai, China. ruiqiwu@fudan.edu.cn.
  • Ye Gong
    Department of Neurosurgery of Huashan Hospital, State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science and Institutes of Brain Science, Fudan University, Shanghai, China. gong_ye@fudan.edu.cn.