Young Onset Alzheimer's disease (YOAD) is characterised by its syndromic diversity, which may be underpinned by different patterns of white matter (WM) network breakdown. This prompts considerable interest in studying WM. We have previously shown that NODDI, a multi-shell diffusion MRI technique, is more sensitive at detecting WM changes in YOAD than standard DTI and demonstrated unique profiles of WM deficits in its syndromic variants. Here we investigated longitudinal WM changes in YOAD patients using NODDI, and explored the patterns of longitudinal WM changes associated with syndromic variants using tract-based spatial statistics (TBSS).
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