The overall goal of the PITT-ADRC is to perform and promote research that increases our understanding of: 1) the etiology and pathogenesis of Alzheimer's disease (AD), 2) the mechanisms underlying the cognitive and behavioral symptoms of AD, and 3) to develop strategies that will result in effective early diagnoses and treatments for AD and related dementias. The Neuroimaging Core (NIC) will support these Center-wide goals by developing and applying cutting edge neuroimaging technology to studies that are focused on early and presymptomatic stages of the AD spectrum. As the search for preclinical biomarkers continues, it is becoming increasingly clear that functional and structural brain imaging data may hold the key to identifying the earliest pathological manifestations of AD prior to any meaningful clinical change. The NIC will continue to develop and distribute technology for acquiring and interpreting brain functional and structural imaging data in the support of AD research. The NIC will advance the Center goals by supporting and promoting research that increases our understanding of the etiology and pathogenesis of AD and facilitates the development of new therapies and methods for monitoring therapeutic efficacy. The NIC maintains data sets of structural imaging on individuals enrolled through the Clinical Core, and we continue to work on the expansion of leading-edge analytic technologies, and novel radiotracer ligands measured with Positron Emission Tomography (PET) (i.e., PiB, AV-1451 and GTP-1). The work of the NIC will accelerate efforts to identify early and presymptomatic AD by identifying imaging biomarkers to monitor the natural and treated history of the disease. The curated, ?trial-ready? participant database will allow PITT-ADRC researchers to track biomarker-based clinical progression and to identify risk and protective factors. This database will also uniquely position the PITT-ADRC to identify potential participants based on specific biomarker characteristics. Finally, the NIC?s focus on quality assurance will ensure that neuroimaging methods are generating data measuring what they purport to measure and that the analysis stream retains the integrity of these data, ensuring that the statistical methodologies generate model that are biologically meaningful.
