Machine learning prediction prior to onset of mild cognitive impairment using T1-weighted magnetic resonance imaging radiomic of the hippocampus.

Journal: Asian journal of psychiatry
Published Date: Jun 1, 2025

Abstract

BACKGROUND: Early identification of individuals who progress from normal cognition (NC) to mild cognitive impairment (MCI) may help prevent cognitive decline. We aimed to build predictive models using radiomic features of the bilateral hippocampus in combination with scores from neuropsychological assessments.

Authors

  • Shiqi Zhan
    National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China; College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China.
  • Jiawei Wang
    Biomedicine Discovery Institute, Monash University, VIC 3800, Australia.
  • Jie Dong
    Department of Urology, Eastern Theater Command General Hospital, Nanjing，Jiangsu 210002, Chinia.
  • Xinru Ji
    College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China.
  • Li Huang
    National Research Center for Resettlement (NRCR), Hohai University, 1 Xikang Road, Nanjing 210098, China. lily8214@hhu.edu.cn.
  • Qingqing Zhang
    Department of Statistics and Medical Record Management, Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, Shandong, China.
  • Daixuan Xu
    National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China.
  • Lixin Peng
    College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China.
  • Xiuxiu Wang
    Chemistry and Biomedicine Innovation Center (Chem BIC), School of Chemistry and Chemical Engineering Nanjing University, Nanjing, China.
  • Yusi Zhang
    Cancer Center, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China; Precision Medicine Center, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China; Department of Medical Oncology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
  • Shengxiang Liang
    National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China; Rehabilitation Industry Institute, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China; Fujian Key Laboratory of Cognitive Rehabilitation, Fuzhou 350122, China. Electronic address: sxliang@fjtcm.edu.cn.
  • Lidian Chen
    College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China.

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