A deep learning MR-based radiomic nomogram may predict survival for nasopharyngeal carcinoma patients with stage T3N1M0.

Journal: Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Published Date:

Abstract

PURPOSE: To estimate the prognostic value of deep learning (DL) magnetic resonance (MR)-based radiomics for stage T3N1M0 nasopharyngeal carcinoma (NPC) patients receiving induction chemotherapy (ICT) prior to concurrent chemoradiotherapy (CCRT).

Authors

  • Lian-Zhen Zhong
    School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, PR China; CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, PR China.
  • Xue-Liang Fang
    State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, PR China.
  • Di Dong
    The Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
  • Hao Peng
    Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong, P. R. China.
  • Meng-Jie Fang
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, P. R. China.
  • Cheng-Long Huang
    State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, PR China.
  • Bing-Xi He
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, PR China; School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, PR China.
  • Li Lin
    Department of Cardiology, Lishui Central Hospital and the Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, China.
  • Jun Ma
    State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150090, China.
  • Ling-Long Tang
    From the Department of Radiation Oncology (L.L., G.Q.Z., J.Y.L., L.L.T., S.M.H., J.M., Y.S.) and Imaging Diagnosis and Interventional Center (C.M.X.), Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, 651 Dongfeng Rd East, Guangzhou 510060, China; Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong SAR (Q.D., Y.M.J., P.A.H., H.C.); Imsight Medical Technology, Shenzhen, China (H.C.); Divisions of Radiation Oncology (J.T.S.W., M.L.K.C.) and Medical Sciences (M.L.K.C.), National Cancer Center Singapore, Singapore; Oncology Academic Programme, Duke-NUS Medical School, Singapore (M.L.K.C.); Department of Radiation Oncology, Jiangxi Cancer Hospital, Nanchang, China (Y.Q.T.); Department of Radiation Oncology, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, China (W.L.C.); Department of Radiation Oncology, Quanzhou First Hospital Affiliated to Fujian Medical University, Quanzhou, China (B.A.S.); Department of Radiation Oncology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China (F.L.); Department of Radiation Oncology, Zhejiang Provincial Cancer Hospital, Key Laboratory of Radiation Oncology of Zhejiang Province, Hangzhou, China (C.J.T.); and Department of Radiation Oncology, Nanjing Medical University Affiliated Cancer Hospital, Jiangsu Cancer Hospital and Jiangsu Institute of Cancer Research, Nanjing, China (N.J.).
  • Jie Tian
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.