PROJECT SUMMARY/ABSTRACT
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.