Quantitative cerebral blood vessel imaging biomarkers for AD and VCID

Alzheimer’s disease (AD) and Vascular Cognitive Impairment and Dementia (VCID) are two leading causes of cognitive decline and dementia in the elderly and are both associated with cerebrovascular disease (CVD). Postmortem findings show that the underlying type of vascular pathology differs in AD and VCID. In AD, Aβ often accumulates in leptomeningeal and cortical arterioles (known as cerebral amyloid angiopathy (CAA)), while in VCID, atherosclerosis or arteriolosclerosis (ASCVD) affects large feeding and small perforating arteries (e.g., lenticulostriate arteries (LSA)), respectively. However, to complicate matters, mixed AD/VCID pathologies are common, especially with increasing age. To date, the investigations of vascular pathology in AD/VCID are mainly limited to indirect measures of vascular brain injury in brain parenchyma (e.g., white matter hyperintensity, infarcts, and microbleeds), which lack specificity vis a vis the severity and type of underlying vascular pathology. Arterial stiffness and arterial pulsatility are important indicators of blood vessel dysfunction. Increased arterial stiffness or elevated arterial pulsatility can result in transmission of excessive pulsatile energy into downstream microvasculature, and lead to endothelial dysfunction and vascular inflammation. Currently, these assessments are mostly carried out on central or major cerebral arteries. Cerebral vascular morphology also reflects the health of brain vessels, but individual variation in branching of cerebral vessels has made it difficult to provide reliable quantitative morphological metrics across subjects. Therefore, directly assessing the health and functional status of cerebral blood vessels (e.g., arterial stiffness, pulsatility, and morphology) at various levels of the cerebral vascular tree could provide a more comprehensive understanding of the vascular pathology in AD/VCID and help differentiate CAA/ASCVD. The goal of this application is to develop a class of cerebral blood vessel hemodynamic and morphological metrics and to characterize cerebral blood vessel dysfunction in AD and VCID. Aim1 will develop and validate quantitative hemodynamic and morphological vascular metrics (VM) using advanced MRI technologies and novel image-processing algorithm pipelines at different levels of cerebrovascular tree. Aim2 will derive these vascular metrics in a sample of 100 elderly subjects enriched for apoE genotype and cardiovascular risk factors. In Aim 2a, we will correlate VM with cerebral blood flow, vascular brain injury, and cognitive impairment. In Aim 2b, we will correlate VM in leptomeningeal arteries or lenticulostriate arteries with uptake of amyloid PET ligands and cardiovascular risk profile to determine whether alterations in site-specific VM can help differentiate CAA vs. ASCVD. Successful completion of the proposed research would deliver a class of reliable cerebral vascular biomarkers to characterize and differentiate vascular pathology in AD/VCID.