A Prognostic Predictive System Based on Deep Learning for Locoregionally Advanced Nasopharyngeal Carcinoma.

Journal: Journal of the National Cancer Institute
PMID: 32970812

Abstract

BACKGROUND: Images from magnetic resonance imaging (MRI) are crucial unstructured data for prognostic evaluation in nasopharyngeal carcinoma (NPC). We developed and validated a prognostic system based on the MRI features and clinical data of locoregionally advanced NPC (LA-NPC) patients to distinguish low-risk patients with LA-NPC for whom concurrent chemoradiotherapy (CCRT) is sufficient.

Authors

  • Mengyun Qiang
    State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, China.
  • Chaofeng Li
    State Key Laboratory of Oncology in South China, Collaborative Innovation Center of Cancer Medicine, Guangzhou, 510060, P. R. China.
  • Yuyao Sun
    Ping An Technology, Beijing, China.
  • Ying Sun
    CFAR and I2R, Agency for Science, Technology and Research, Singapore.
  • Liangru Ke
    State Key Laboratory of Oncology in South China, Collaborative Innovation Center of Cancer Medicine, Guangzhou, 510060, P. R. China.
  • Chuanmiao Xie
    Department of Radiology, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China.
  • Tao Zhang
    Department of Traumatology, Chongqing Emergency Medical Center, Chongqing University Central Hospital, School of Medicine, Chongqing University, Chongqing, 40044, People's Republic of China.
  • Yujian Zou
    Department of Radiology, The People's Hospital of Dongguan, Dongguan, Guangdong, China.
  • Wenze Qiu
    State Key Laboratory of Oncology in South China, Collaborative Innovation Center of Cancer Medicine, Guangzhou, 510060, P. R. China.
  • Mingyong Gao
    Department of Medical Imaging, First People's Hospital of Foshan, Foshan 528000, PR China.
  • Yingxue Li
    Ping An Healthcare Technology, Beijing.
  • Xiang Li
    Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.
  • Zejiang Zhan
    Department of Radiotherapy, The Affiliated Cancer Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China.
  • Kuiyuan Liu
    State Key Laboratory of Oncology in South China, Collaborative Innovation Center of Cancer Medicine, Guangzhou, 510060, P. R. China.
  • Xi Chen
    Department of Critical care medicine, Shenzhen Hospital, Southern Medical University, Guangdong, Shenzhen, China.
  • Chixiong Liang
    State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, Guangzhou 510060, PR China.
  • Qiuyan Chen
    State Key Laboratory of Oncology in South China, Collaborative Innovation Center of Cancer Medicine, Guangzhou, 510060, P. R. China.
  • Haiqiang Mai
    State Key Laboratory of Oncology in South China, Collaborative Innovation Center of Cancer Medicine, Guangzhou, 510060, P. R. China.
  • Guotong Xie
    Ping An Health Technology, Beijing, China.
  • Xiang Guo
    State Key Laboratory of Oncology in South China, Collaborative Innovation Center of Cancer Medicine, Guangzhou, 510060, P. R. China. guoxiang@sysucc.org.cn.
  • Xing Lv
    State Key Laboratory of Oncology in South China, Collaborative Innovation Center of Cancer Medicine, Guangzhou, 510060, P. R. China. lvxing@sysucc.org.cn.

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