Multi-parameters diffusion MRI reveals microstructural changes with the progression of Alzheimer’s disease

Motivation: Alzheimer's disease (AD) is difficult to early diagnosis due to lack of precise biomarkers. Goal(s): This study aimed to detect brain microstructural changes with AD progression using multi-parameters diffusion MRI. Approach: Based on data from ADNI, we utilized two diffusional models, tensor and NODDI, to calculate multiple metrics and detect progressive brain microstructural changes. Results: We observed significant differences among A/T/N groups across different diffusional metrics. We discovered that different parameters exhibit varying sensitivities at different stages of AD. These findings suggest that diffusion MRI provides valuable insights into early AD diagnosis and monitoring, with different models offering complementary information across disease stages. Impact: Our findings demonstrate that multi-parameters diffusion MRI identify stage-specific biomarkers by revealing brain microstructural changes, and this may enhance accuracy of early diagnosis of Alzheimer's disease and further improve patients' outcomes.