Aging is accompanied by increasing vulnerability to cardiovascular disease (CVD) and Alzheimer?s disease (AD). The ongoing rise in both AD and CVD has been ascribed to the increasing adoption of a Western sedentary lifestyle accompanied by a diet rich in fats and sugars. To understand the links between AD and CVD in human subjects, non-invasive imaging methods such X-ray computed tomography (CT) and magnetic resonance (MR) are essential. Cardiac CT is one of the most powerful applications of these methodologies at both clinical and preclinical levels, but it is currently limited by its low contrast resolution. Our primary objective in this proposal is to improve the current status of cardiac CT based on photon counting detector technology and demonstrate its capabilities in preclinical studies focused on studying the interaction between CVD and AD. Our central hypothesis is that cardiac photon counting CT will provide low dose spectral characterization of atherosclerotic plaques together with cardiac function, while enabling longitudinal monitoring of interventions such as exercise. We will pursue three specific aims.
In specific aim 1, we will develop the theoretical foundation and GPU optimized tools for reconstruction of cardiac 5D (3D + Time + Energy) photon counting CT data. We will incorporate deep learning solutions to overcome fundamental barriers to the advancement of this technology: regularization to deal with image noise associated with photon binning, robust material decomposition to combat spectral distortion, and automated cardiac function and plaque analysis to handle data dimensionality. During the second specific aim, we will characterize the performance of our novel cardiac photon counting CT imaging using simulations, phantoms and animal experiments to show its benefits for atherosclerotic plaque characterization and cardiac function estimation. Finally, in specific aim 3 we will investigate if cardiovascular risk impacts brain phenotypes in animal models of genetic risk for AD. CVD and AD share a genetic link via the ApoE gene and its isomorphic allele 4 (APOE4). We will use APOE3/HN and APOE4/HN mouse strains that express the corresponding specific targeted-replacement human APOE allele, on a humanized Nitric Oxide Synthase 2 (denoted here as HN) background. Using these models, we will first assess the impact of a high fat, high sugar diet on cardiovascular phenotypes (atherosclerotic plaque size, numbers; cardiac function measured with CT) and how these genetic differences are reflected in behavior and brain MR based biomarkers compared with control mice in the same background. Finally, we will also investigate the potential to rescue these phenotypes using exercise as the intervention. The impact of the proposed research will validate the usage of photon counting CT technology to enhance routine cardiac CT imaging applications. Our project will enable new powerful integrative approaches to examine the impact of environmental stressors to alter APOE genotype- specific vulnerability, or resilience to CVD and AD.

Public Health Relevance

Clinical, pathological and epidemiological evidence clearly show overlap between cardiovascular and Alzheimer?s diseases caused by a critical genetic link: the apolipoprotein E gene. We will develop novel photon counting cardiac CT imaging and use it in combination with brain MR imaging and behavior assessments to study the impact of APOE genotype in mouse models and to provide data on phenotypic differences in these mice when exposed to a high fat/high sugar diet and the role of exercise in protecting against Alzheimer?s and cardiovascular diseases.

National Institute of Health (NIH)
National Institute on Aging (NIA)
Multi-Year Funded Research Project Grant (RF1)
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Emerging Imaging Technologies and Applications Study Section (EITA)
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Kerr, Candace L
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Duke University
Schools of Medicine
United States
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