Neuroimaging offers a powerful strategy to chart the dynamic path of aging and Alzheimer's disease (AD) in the brain. This project will apply strategies with unprecedented sensitivity to detect, map, and analyze patterns of brain change (structural and functional) in AD and those at risk. Our novel brain maps will quantify disease progression to advance identification of early brain changes, and monitor treatment and gene effects. Using new mathematics and supercomputing technology, we will build on our work to create detailed 4D (dynamic) maps of brain changes based on serial magnetic resonance imaging (MRI). To increase sensitivity to detect and analyze drug and gene effects on brain changes, we will use (1) large cohorts scanned repeatedly over long intervals, and (2) improved image analyses using nonlinear deformation techniques and surface-based statistics. Algorithms will map the profiles, and rates, of cortical thinning, hippocampal change, gray matter loss, and volumetric atrophy. Collecting these maps from multiple populations, we will compare rates of brain change in patients with AD and FTD (Specific Aims 1 and 2), and MCI, CIND and healthy individuals with known risk genes (Aim 3). Probabilistic maps and statistics of these changes will be stored in a normative database, or brain atlas, and analyzed for group differences. We will stratify this population atlas by cohort, medication, symptom profiles, and risk genotype to help understand the dynamics of disease onset and progression, and how treatment affects these changes. We will determine how structural brain changes correlate with cognitive/metabolic decline (PET data) measured in the same subjects (Aim 4). In collaboration with an ongoing randomized, double-blind clinical trial (Aim 5), we will test whether drug treatment with donepezil and/or vitamin E decelerates atrophic rates in MCI subjects. The products of these efforts (engineering and neuroscience) will shed light on how dementia emerges in the brain and will improve our ability to track it. These tools will be publicly available, and will greatly expand our ability to investigate the dynamics of AD, detect its onset, compare patterns of therapeutic response, and understand its spatial/temporal selectivity.
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