Beta-Amyloid Clearance Mapping in Alzheimer’s Disease

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PROJECT SUMMARY Alzheimer’s disease (AD) is the most common form of dementia that can be characterized by brain imaging methods such as magnetic resonance imaging (MRI) and positron emission tomography (PET). MRI explains the structural changes, while PET measures represent plaque deposits in the brain according to the disease progression. The plaque deposition reflects early AD pathophysiology and presumably caused by a decrease in the removal rate of beta-amyloid through the cleaning systems of the brain. Recent studies have suggested the potential role of cerebrospinal fluid (CSF) in carrying waste from brain tissue to the cleaning system. However, it is still not well understood how CSF flow in the brain affects waste removal. Therefore, the proposed multidisciplinary research project will involve the collaboration of investigators from diverse and complementary backgrounds (a biomechanical engineer, an MR physicist, a neuroradiologist, and cognitive neuroscientists) to address CSF flow-related AD pathophysiology. To analyze CSF flow in the narrow space between the skull and brain tissue (subarachnoid space [SAS]), we will employ computational fluid dynamic (CFD) modeling technique and correlate CSF flow with neuroimaging markers measured by MRI and PET. Here, the overarching hypothesis is, “Disturbed CSF flow in the SAS leads to the deposition of Amyloid plaque.” To test the hypothesis, we will take the following two steps: 1) Fifty healthy older adults will be recruited for an MRI scan. Based on anatomical and CSF velocity information measured by MRI, three-dimensional flow dynamic properties in SAS will be analyzed through CFD simulation, 2) The simulated CSF properties will be correlated with local amyloid plaque deposition by taking advantage of PET imaging data from the NIH-funded parent study (Wake Forest Alzheimer’s Disease Research Center). Here, we will propose a new imaging marker for amyloid removal for each functional brain region by combining imaging, CFD, and clinical measures. As an alternative approach, in case the new imaging markers are not useful in healthy older adults due to the small sample size, we will apply the CFD model to larger datasets for early AD adults. At the completion of this project, a new imaging tool to quantify CSF flow in the SAS and evaluate its effects on amyloid deposition and removal will be proposed. AD pathophysiology at an early stage in older adults can be analyzed using the proposed approach. Ultimately, this project will provide a biomechanical framework for the design and test of interventional and surgical procedures for the treatment of AD. The developed software programs and imaging protocols will be shared through a public software development/sharing platform.