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Title: Disentangling the relationship between white matter disease, vascular risk, Alzheimer's disease pathology and brain atrophy : timing of events and location of changes
Author: Fiford, Cassidy M.
ISNI:       0000 0004 7660 6770
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2019
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This thesis is an investigation into vascular risk, vascular brain lesions, and age contributions to brain atrophy and cognitive decline in Alzheimer's disease (AD). Associations of white matter hyperintensities (WMHs) to longitudinal hippocampal atrophy were explored in control, mild cognitive impairment (MCI) and AD participants enrolled in the Alzheimer's Disease Neuroimaging Initiative (ADNI1). Also using ADNI1 data, I identified differences in longitudinal brain atrophy patterns in younger vs. older AD patients. Blood pressure (BP), cognition and brain atrophy were jointly modelled to see how changes in each variable are correlated in ADNI1 and National Alzheimer's Coordinating Centre (NACC) participants. The independent associations of microbleeds (MBs), lacunes and WMHs to longitudinal atrophy were also explored in ADNIGo and ADNI2. Lastly, I developed a new protocol for semi-automated WMH segmentation and generated 'gold standard' segmentations with which to assess the performance of an automated WMH segmentation algorithm. WMHs were found to associate with hippocampal atrophy in controls and MCI, which survived correction for CSF biomarkers of amyloid and tau, and concurrent brain atrophy. Secondly, I found that younger AD patients have greater extra- hippocampal atrophy, with a prominent posterior atrophy pattern, and faster atrophy rates compared to older AD patients. Greater hippocampal atrophy rates were found in MCI and AD patients with higher baseline systolic BP. In ADNI2 and ADNIGo subjects MB presence and WMH volume were associated with increased longitudinal brain atrophy rate, whilst presence of a lacune was associated with a reduced atrophy rate. Lastly, I showed that the automated WMH segmentation algorithm compares well to the 'gold standard', and automated volumes were able to predict cognitive change across disease types. This work extends existing knowledge about how age, vascular risk and brain lesions with a presumed vascular aetiology, link with brain atrophy and cognitive decline in ageing and AD.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available