Development and validation of a machine learning algorithm for predicting diffuse midline glioma, H3 K27-altered, H3 K27 wild-type high-grade glioma, and primary CNS lymphoma of the brain midline in adults.

Journal: Journal of neurosurgery
Published Date: Dec 23, 2022

Abstract

OBJECTIVE: Preoperative diagnosis of diffuse midline glioma, H3 K27-altered (DMG-A) and midline high-grade glioma without H3 K27 alteration (DMG-W), as well as midline primary CNS lymphoma (PCNSL) in adults, is challenging but crucial. The aim of this study was to develop a model for predicting these three entities using machine learning (ML) algorithms.

Authors

  • Kun Lv
    Departments of1Radiology and.
  • Hongyi Chen
    Academy for Engineering and Technology, Fudan University, Shanghai, 200433, China.
  • Xin Cao
    Zhongshan Hospital, Institute of Clinical Science, Shanghai Medical College, Fudan University, Shanghai 200032, China.
  • Peng Du
    Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.
  • Jiawei Chen
  • Xiao Liu
  • Li Zhu
    Medical College, Yangzhou University, Yangzhou 225001, China.
  • Daoying Geng
    Department of Radiology, Huashan Hospital, Fudan University, 12 Wulumuqi Rd. Middle, Shanghai, 200040, China. GengdaoyingGDY@163.com.
  • Jun Zhang
    First School of Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China.

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