Integrating 3-D Micro-Electrode Sensing with Fractional Flow Reserve for Lipid-Rich Plaques Atherosclerosis and metabolic diseases are on the rise in our veterans returning from battlefields in Afghanistan and the Middle East. Atherosclerosis is a systemic disease; however, its manifestations tend to be focal and eccentric, and rupture of individual plaques is the primary underlying mechanism of myocardial infarction and stroke. Plaques prone to rupture contain high levels of oxidative stress and inflammatory activity in part due to oxidized lipids and foam cells. Based on randomized clinical trials, American Heart Association guidelines recommend the routine measurement of Fraction Flow Reserve (FFR), defined as the ratio of pressure across the stenotic lesions (Pdownstream/Pupstream), to determine the indication for coronary revascularization in patients with coronary artery disease (CAD). For FFR > 0.8, patients are treated with medical optimization; for FFR ? 0.8, patients are referred for coronary revascularization, e.g., stent deployment and antiplatelet therapy. Nevertheless, the recent five-year outcomes of the FAME (Fractional Flow Reserve versus Angiography for Multivessel Evaluation) 2 trial revealed no difference in death or myocardial infarction between FFR-guided percutaneous coronary intervention (PCI) and optimal medical therapy in patients with stable CAD. Thus, real-time detection of the metabolically unstable plaque prone to rupture remains an unmet clinical challenge. Our previous studies demonstrated that endoluminal electrochemical impedance spectroscopy (EIS) distinguishes pre-atherogenic lesions associated with oxidative stress in fat-fed New Zealand White (NZW) rabbits. Specifically, vessel walls harboring oxidized low density lipoprotein (oxLDL) exhibit high EIS magnitude. In parallel, intimal monocytes and oxLDL are deleterious at all stages of atherosclerosis, destabilizing calcific vascular nodules via induction of matrix metalloproteinases (MMP). In this context, we seek to develop an electrochemical strategy to identify apparently stable, but metabolically active (with FFR > 0.8) lesions containing oxLDL-laden monocyte-macrophages (foam cells), during diagnostic angiography. We hypothesize that integrating 3-D electrochemical impedance spectroscopy with FFR pressure sensors allows for detection of oxLDL-rich lesions to improve the accuracy of necessary intervention. To test our hypothesis, we have three Specific Aims.
In Aim 1, we will integrate a 12-point 3-D electrode array permitting high spatial and angular resolution with pressure sensors to enhance detection of oxLDL-laden plaque.
In Aim 2, we will determine the sensitivity and specificity of 3-D EIS mapping for oxLDL- laden, foam cell-rich atherosclerotic lesions in fat-fed vs. D-4F (an apolipoprotein A-I mimetic peptide) + fat-fed NZW rabbits.
In Aim 3, we will establish 3-D EIS mapping in rupture-prone plaque in the carotid arteries of a pig model. Overall, establishing 3-D electrochemical mapping of active lipid-laden lesions with animal models of atherosclerosis provides a new strategy to identify metabolically active lesions for personalized intervention, and improve the accuracy of necessary intervention for our veterans.

Public Health Relevance

Cardiovascular disease and metabolic syndromes are a rising health risk factor to our veterans returning from the Afghanistan and Gulf Wars. Atherosclerosis is a systemic disease; however, its manifestations tend to be focal and eccentric, and rupture of individual plaques is the primary underlying mechanism of myocardial infarction and stroke. We seek to develop an electrochemical strategy to identify metabolically active lesions containing lipid-laden macrophages during diagnostic angiography.

Agency
National Institute of Health (NIH)
Institute
Veterans Affairs (VA)
Type
Non-HHS Research Projects (I01)
Project #
1I01BX004558-01A2
Application #
9892828
Study Section
Special Emphasis Panel (ZRD1)
Project Start
2020-01-01
Project End
2023-12-31
Budget Start
2020-01-01
Budget End
2020-12-31
Support Year
1
Fiscal Year
2020
Total Cost
Indirect Cost
Name
VA Greater Los Angels Healthcare System
Department
Type
DUNS #
066689118
City
Los Angeles
State
CA
Country
United States
Zip Code
90073