Intelligent cholinergic white matter pathways algorithm based on U-net reflects cognitive impairment in patients with silent cerebrovascular disease.

Journal: Stroke and vascular neurology
PMID: 38569895

Abstract

BACKGROUND AND OBJECTIVE: The injury of the cholinergic white matter pathway underlies cognition decline in patients with silent cerebrovascular disease (SCD) with white matter hyperintensities (WMH) of vascular origin. However, the evaluation of the cholinergic white matter pathway is complex with poor consistency. We established an intelligent algorithm to evaluate WMH in the cholinergic pathway.

Authors

  • Beini Fei
    Department of Neurology, Zhongshan Hospital Fudan University, Shanghai, China.
  • Yu Cheng
  • Ying Liu
    The First School of Clinical Medicine, Lanzhou University, Lanzhou, China.
  • Guangzheng Zhang
    Department of Neurology, Zhongshan Hospital Fudan University, Shanghai, China.
  • Anyan Ge
    Department of Neurology, Zhongshan Hospital Fudan University, Shanghai, China.
  • Junyi Luo
    University of Electronic Science and Technology of China, Chengdu, China.
  • Shan Wu
    Department of Endoscopy, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China.
  • He Wang
    Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, China International Neuroscience Institute, Beijing, China.
  • Jing Ding
    Zhejiang Pharmaceutical College, Ningbo, 15100.
  • Xin Wang
    Key Laboratory of Bio-based Material Science & Technology (Northeast Forestry University), Ministry of Education, Harbin 150040, China.

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