Robust deep learning-based PET prognostic imaging biomarker for DLBCL patients: a multicenter study.

Journal: European journal of nuclear medicine and molecular imaging
PMID:

Abstract

OBJECTIVE: To develop and independently externally validate robust prognostic imaging biomarkers distilled from PET images using deep learning techniques for precise survival prediction in patients with diffuse large B cell lymphoma (DLBCL).

Authors

  • Chong Jiang
  • Chunjun Qian
    School of Science, Nanjing University of Science and Technology, Jiangsu, China.
  • Zekun Jiang
    College of Computer Science, Sichuan University, Chengdu, Sichuan, China.
  • Yue Teng
    Haidian Maternal & Child Health Hospital Nutrition Clinic, Beijing 100080, China.
  • Ruihe Lai
    Department of Nuclear Medicine, Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School, Nanjing, China.
  • Yiwen Sun
    National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong, Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Department of Biomedical Engineering, School of Medicine, Shenzhen University, Shenzhen 518060, China.
  • Xinye Ni
    Radiotherapy Department, Second People's Hospital of Changzhou, Nanjing Medical University, Changzhou, 213003, China. nxy@njmu.edu.cn.
  • Chongyang Ding
    Department of Nuclear Medicine, the First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, China.
  • Yuchao Xu
    School of Nuclear Science and Technology, University of South China, Hengyang City 421001, China.
  • Rong Tian
    Department of Nuclear Medicine, West China Hospital, Sichuan University, Chengdu 610041, China. Electronic address: rongtiannuclear@126.com.