Deep learning for locally advanced nasopharyngeal carcinoma prognostication based on pre- and post-treatment MRI.

Journal: Computer methods and programs in biomedicine
PMID: 35397409

Abstract

PURPOSE: We aimed to predict the prognosis of advanced nasopharyngeal carcinoma (stage Ⅲ-Ⅳa) using Pre- and Post-treatment MR images based on deep learning (DL).

Authors

  • Song Li
    Department of Crop and Soil Environmental Sciences, Virginia Polytechnic Institute and State University Blacksburg, VA, USA.
  • Yu-Qin Deng
    Department of Otolaryngology-Head and Neck Surgery, Renmin Hospital of Wuhan University, Wuhan, China.
  • Hong-Li Hua
    Department of Otolaryngology-Head and Neck Surgery, Renmin Hospital of Wuhan University, Wuhan, China.
  • Sheng-Lan Li
    Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, China.
  • Xi-Xiang Chen
    Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, China.
  • Bao-Jun Xie
    Department of of Radiology, Renmin Hospital of Wuhan University, 238 Jie-Fang Road, Wuhan, Hubei 430060, PR China.
  • Zhiling Zhu
    Department of of Otolaryngology-Head and Neck Surgery, Tongji Hospital Affiliated to Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, PR China.
  • Ruoyun Liu
    Department of Electronic Engineering, Fudan University, No. 220, Handan Road, Yangpu District, Shanghai, 200433, China.
  • Jin Huang
    College of Life Science, Yangtze University, Jingzhou, Hubei 434023, P. R. China; Institute of Agricultural Products Processing, Jiangsu Academy of Agricultural Sciences, Nanjing, 210014, PR China.
  • Ze-Zhang Tao
    Department of Otolaryngology-Head and Neck Surgery, Renmin Hospital of Wuhan University, Wuhan, China.

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