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Human Atherosclerotic Plaque Inflammation Imaged Using PDG-PET/CT

National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) · 2009
ClinicalTrials.gov · Datasets · License: Public Domain · 2009
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atherosclerosiscardiovascular-diseasediabeteshivhiv-aidshiv-infectionsinsulin-resistance
People with diabetes are at increased risk for atherosclerosis and have high CVD morbidity and mortality rates. Tools for detecting and quantifying atherosclerotic pro/regression in people with diabetes and other CVD risk factors lack sensitivity and specificity for molecular level events that occur during the early stages of atherogenesis. Inflammatory macrophage infiltration in the vessel endothelium is an early, molecular level proatherogenic event. Activated macrophages consume glucose at a high rate. Novel in vivo radiotracer PET/CT techniques have been developed to detect, image and quantify molecular level events like macrophage inflammation and glucose utilization (18FDG) in human vessels. We propose to develop and test this novel technique in the Center for Clinical Imaging Research (CCIR) at WUMS. We propose that HIV-infected people with significant CVD risk profiles are a suitable, unique human model for testing these novel imaging techniques. HIV-infected people taking anti-HIV medications develop insulin resistance, T2DM, dyslipidemia, central adiposity, and hypertension. HIV replicates in macrophages and represents a chronic proinflammatory condition. Recent data indicate that HIV+ CVD risk have greater risk for atherosclerosis and MI than HIV-negative people. To test feasibility, we hypothesize that: a.18FDG-PET/CT imaging will detect more macrophage glucose uptake and inflammation in the carotid and aorta arteries of HIV-infected people with CVD risk than in HIV-negative controls; b. radiotracer PET/CT measures of proatherogenic processes will correlate with carotid intima media thickness; a standard measure of carotid atherosclerotic burden. We propose to obtain pilot data that shows feasibility for a novel analytical approach that will expand capabilities for researchers interested in studying the links between diabetes, inflammation, and CVD in humans.
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