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<p>To investigate the effectiveness of diffusion quantitative parameters in detecting microstructural changes in the brain of patients with Alzheimer’s disease (AD) and evaluate the relationship between diffusivity and cognitive function. The study enrolled 43 patients and 16 healthy controls. All participants underwent diffusion spectrum imaging (DSI) and conventional magnetic resonance imaging (MRI). The images were further processed to obtain diffusion MRI models and multi-parameter values. Pearson correlation analysis was used to assess the relationships between diffusion parameters and clinical cognitive scores. Receiver operating characteristic (ROC) analysis was conducted to evaluate the diagnostic performance of various parameters. Significant correlations were observed between neuropsychological scores and diffusion parameters across multiple brain regions. Specifically, the diffusion metrics most strongly related to MMSE and MoCA scores included RTOP, RTAP, ICVF, and FA, with RTOP and RTAP exhibiting the strongest relationship to cognitive function. ROC analysis of DTI, NODDI, and MAP parameters for diagnosing AD indicated satisfactory performance. DTI, NODDI, and MAP-MRI diffusion models are all suitable markers for studying AD. The detailed parameters provide more information about the brain’s microstructural changes in AD patients.</p>

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Analysis of advanced diffusion models assessing white matter microstructure in Alzheimer’s disease

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月19日

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  • Minli Lv,
  • Kongcai Zhan,
  • Jie Yang,
  • Yan Li,
  • Yutong Li,
  • Xiaoya Xu,
  • Limei Han,
  • Hao Feng,
  • Jianquan Zhong

摘要

To investigate the effectiveness of diffusion quantitative parameters in detecting microstructural changes in the brain of patients with Alzheimer’s disease (AD) and evaluate the relationship between diffusivity and cognitive function. The study enrolled 43 patients and 16 healthy controls. All participants underwent diffusion spectrum imaging (DSI) and conventional magnetic resonance imaging (MRI). The images were further processed to obtain diffusion MRI models and multi-parameter values. Pearson correlation analysis was used to assess the relationships between diffusion parameters and clinical cognitive scores. Receiver operating characteristic (ROC) analysis was conducted to evaluate the diagnostic performance of various parameters. Significant correlations were observed between neuropsychological scores and diffusion parameters across multiple brain regions. Specifically, the diffusion metrics most strongly related to MMSE and MoCA scores included RTOP, RTAP, ICVF, and FA, with RTOP and RTAP exhibiting the strongest relationship to cognitive function. ROC analysis of DTI, NODDI, and MAP parameters for diagnosing AD indicated satisfactory performance. DTI, NODDI, and MAP-MRI diffusion models are all suitable markers for studying AD. The detailed parameters provide more information about the brain’s microstructural changes in AD patients.