Cerebral small vessel disease: Enhancing the diagnostic precision of MRI

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DESCRIPTION (provided by applicant): Cerebrovascular disease is one of the most common causes of dementia in aging humans. With the growing elderly population in Western societies, vascular cognitive impairment (VCI) will become a significant healthcare burden in the 21st century. Recent advances in magnetic resonance imaging (MRI) are continually lowering the threshold for detection of vascular anomalies in the brain, leading to a growing awareness that small vessel disease and microinfarcts can cumulatively lead to VCI. However, the power of MRI currently is limited by the inability to link anomalous MR signals unambiguously to specific lesion types. Valid animal models would greatly accelerate diagnostic and therapeutic approaches to cerebrovascular disease. The explicit identification of MR anomalies has been a particular problem in investigating cerebral A¿-amyloid angiopathy (CAA), a disease of the elderly in which misfolded A¿ peptide accumulates in the walls of brain blood vessels. Investigators have increasingly employed novel imaging protocols to analyze CAA non-invasively. However, there is a critical need for information that will enable the interpretation of neuroimaging data on CAA and other vascular disorders in patients. The aged squirrel monkey is a unique animal model of naturally occurring CAA that is highly similar to the disorder in humans. The overarching goal of our research program is to clarify the role of CAA in vascular dysfunction and cognitive decline in the elderly. The objective of this proposal is to employ this exceptional primate model to optimize the power of MRI to non-invasively identify and characterize CAA-related lesions in living patients. To achieve this goal, we first will investigate a unique sample of archived brains from aged squirrel monkeys with CAA, along with postmortem tissue samples from humans with CAA, in a powerful (7T) MRI scanner. In this way, we can detect a variety of vascular lesions under optimal conditions. Next, we will use the information gained from these ex vivo imaging studies to image a small cohort of aged squirrel monkeys in vivo. The brains then will be examined microscopically to identify and characterize the MRI anomalies unambiguously, and to determine the cellular and molecular features of the lesions. We predict that MRI signal anomalies will be linked to specific histopathological indicators of CAA and associated lesions. The findings from this novel primate model will establish a foundation for future non-invasive studies of the pathogenesis, diagnosis and treatment of CAA in aged humans.