A machine learning-based prediction model of H3K27M mutations in brainstem gliomas using conventional MRI and clinical features.

Journal: Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Published Date: Jan 1, 2019

Abstract

BACKGROUND: H3K27M is the most frequent mutation in brainstem gliomas (BSGs), and it has great significance in the differential diagnosis, prognostic prediction and treatment strategy selection of BSGs. There has been a lack of reliable noninvasive methods capable of accurately predicting H3K27M mutations in BSGs.

Authors

  • Chang-Cun Pan
    Department of Neurosurgery/China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, China.
  • Jia Liu
    Department of Colorectal Oncology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin Key Laboratory of Digestive Cancer, Tianjin, China.
  • Jie Tang
    Department of Computer Science and Technology, Tsinghua University, Beijing, China jietang@tsinghua.edu.cn.
  • Xin Chen
    University of Nottingham, Nottingham, United Kingdom.
  • Fang Chen
  • Yu-Liang Wu
    Department of Neurosurgery/China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, China.
  • Yi-Bo Geng
    Department of Neurosurgery/China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, China.
  • Cheng Xu
    School of Photovoltaic and Renewable Energy Engineering, University of New South Wales, 2052 Sydney, Australia.
  • Xinran Zhang
  • Zhen Wu
    Department of Neurosurgery/China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, China.
  • Pei-Yi Gao
    Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
  • Jun-Ting Zhang
    Department of Neurosurgery/China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, China.
  • Hai Yan
    School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing, China.
  • Hongen Liao
  • Li-Wei Zhang
    Department of Ophthalmology, The Affiliated Hospital of Yunnan University, Second People's Hospital of Yunnan Province, The Eye Hospital of Yunnan Province, The Eye Disease Clinical Medical Research Center of Yunnan Province, The Eye Disease Clinical Medical Center of Yunnan Province, Kunming, China.

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