Exploring Perivascular spaces in Alzheimer's disease using an automated Frangi filter technique - PROJECT SUMMARY/ABSTRACT: Increasing evidence suggests that brain perivascular spaces play important roles in intracerebral fluid transport and brain homeostasis. Enlarged perivascular spaces (PVS) have reported associations with aging, mild cognitive impairment (MCI), and Alzheimer’s disease (AD). However, the utility of this biomarker as an imaging predictor of AD is not fully known. To advance progress in AD, early disease biomarkers must be developed. PVS are linked with biological changes that occur early during the course of AD, including dysfunctional intracerebral fluid regulation, neuroinflammation, and small vessel disease. Yet, substantial gaps in knowledge persist with regard to optimal methods of PVS detection and quantitation in live humans. To advance knowledge on PVS effects in humans, a harmonized, non-biased, and time-efficient technique of PVS quantification must be employed in diseased cohorts. In this project, an open-source automated Frangi filter technique of PVS detection will be used to detect PVS and assess their associations with AD in a large, well characterized, underserved Appalachian community cohort. PVS will be analyzed globally and in specific brain regions in aging, MCI, and AD and PVS longitudinal changes will be examined. This work will leverage a rich resource of existing clinical and imaging material available from the Rockefeller Neuroscience Institute Memory Health Clinic and will produce novel data pertaining to PVS metrics. The hypothesis is that PVS serve as a predictor for AD. In Aim 1, we will examine the associations of static PVS metrics with a diagnosis of AD and cognitive decline. In Aim 2, we will examine the associations of longitudinal PVS metrics with a diagnosis of AD and cognitive decline. In both aims, we will investigate how relationships of PVS metrics differ by age, sex, education history, and comorbid diseases. Overall, these studies have the potential to uncover new knowledge regarding optimal methods of PVS measurement, interpretation, and detection in persons at risk of developing AD. This project may reveal new diagnostic and prognostic factors for AD while elucidating appropriate methods for studying PVS in the setting of other age-related neurological conditions.
