Can the preoperative CT-based deep learning radiomics model predict histologic grade and prognosis of chondrosarcoma?

Journal: European journal of radiology
PMID:

Abstract

BACKGROUND AND PURPOSE: Computed tomography (CT) and biopsy may be insufficient for preoperative evaluation of the grade and outcome of patients with chondrosarcoma. The aim of this study was to develop and validate a CT-based deep learning radiomics model (DLRM) for predicting histologic grade and prognosis in chondrosarcoma (CS).

Authors

  • Pei Nie
    Department of Radiology, Affiliated Hospital of Qingdao University, Qingdao, China.
  • Xia Zhao
    Stony Brook University, Stony Brook, NY.
  • Jinlong Ma
    School of Information Science and Engineering, Hebei University of Science and Technology, Shijiazhuang, China.
  • Yicong Wang
    Department of Nuclear Medicine, Binzhou Medical University Hospital, Binzhou, Shandong, China.
  • Ben Li
    School of Public Health, Shanxi Medical University, Taiyuan 030000, China. Electronic address: LBen@sxmu.edu.cn.
  • Xiaoli Li
    State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
  • Qiyuan Li
    National Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, China.
  • Yanmei Wang
    CAS Key Laboratory of Soft Matter Chemistry, Department of Polymer Science and Engineering, University of Science and Technology of China, Hefei 230026, PR China. Electronic address: wangyanm@ustc.edu.cn.
  • Yuchao Xu
    School of Nuclear Science and Technology, University of South China, Hengyang City 421001, China.
  • Zhengjun Dai
    Scientific Research Department, Huiying Medical Technology Co., Ltd, Beijing, China.
  • Jie Wu
    Center of Disease Control of Qingdao, 175 Shandong Road, Qingdao, Shandong, 266001, China.
  • Ning Wang
    Qilu Hospital of Shandong University Dezhou Hospital, Dezhou, Shandong, China.
  • Guangjie Yang
    Department of Nuclear Medicine, the Affiliated Hospital of Qingdao University, No. 59, Haier Road, Qingdao, 266061, Shandong, China.
  • Dapeng Hao
    Department of Radiology, The Affiliated Hospital of Qingdao University, Shinan Jiangsu 16 Rd, Qingdao, Shandong 266003, China.
  • Tengbo Yu
    Department of Sports Medicine, The Affiliated Hospital of Qingdao University, Qingdao, 266003, Shandong, China. ytb8912@163.com.