Application of a machine learning method to whole brain white matter injury after radiotherapy for nasopharyngeal carcinoma.

Journal: Cancer imaging : the official publication of the International Cancer Imaging Society
PMID: 30909974

Abstract

BACKGROUND: The purpose/aim of this study was to 1) use magnetic resonance diffusion tensor imaging (DTI), fibre bundle/tract-based spatial statistics (TBSS) and machine learning methods to study changes in the white matter (WM) structure and whole brain WM network in different periods of the nasopharyngeal carcinoma (NPC) patients after radiotherapy (RT), 2) identify the most discriminating WM regions and WM connections as biomarkers of radiation brain injury (RBI), and 3) supplement the understanding of the pathogenesis of RBI, which is useful for early diagnosis in the clinic.

Authors

  • Xi Leng
    Medical Imaging Center, The First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, Guangzhou, Guangdong, 510405, People's Republic of China.
  • Peng Fang
    Department of Psychology, The Fourth Military Medical University, Xi'an, Shaanxi, 710032, People's Republic of China.
  • Huan Lin
    Department of Radiology, Zhujiang Hospital of Southern Medical University, No. 253, Gong Ye Da Dao Zhong, Guangzhou, Guangdong, 510280, People's Republic of China.
  • Chunhong Qin
    Medical Imaging Center, The First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, Guangzhou, Guangdong, 510405, People's Republic of China.
  • Xin Tan
    School of Public Health, Chengdu Medical College, Chengdu 610500, China.
  • Yi Liang
    Medical Imaging Center, The First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, Guangzhou, Guangdong, 510405, People's Republic of China.
  • Chi Zhang
    Department of Thoracic Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Hongzhuo Wang
    Medical Imaging Center, The First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, Guangzhou, Guangdong, 510405, People's Republic of China.
  • Jie An
    Medical Imaging Center, The First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, Guangzhou, Guangdong, 510405, People's Republic of China.
  • Donglin Wu
    Medical Imaging Center, The First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, Guangzhou, Guangdong, 510405, People's Republic of China.
  • Qihui Liu
    Medical Imaging Center, The First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, Guangzhou, Guangdong, 510405, People's Republic of China.
  • Shijun Qiu
    Medical Imaging Center, The First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, Guangzhou, Guangdong, 510405, People's Republic of China. qiushijun666@163.com.

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