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Integrating Coronary Atherosclerosis with Physiologic Features for Optimized Risk Stratification


PROJECT SUMMARY Coronary artery disease (CAD) is the principal basis of morbidity and mortality worldwide, and more than half of individuals experiencing acute myocardial infarction (AMI) have no premonitory symptoms. Coronary CT angiography is a non-invasive technique that permits low-dose volumetric imaging of the coronary arteries in a single heartbeat. CT is accurate compared to invasive angiography, and angiographic severity of coronary artery disease (CAD) by CT enables prognostication of ACS and death. Beyond luminal narrowing, CT enables quantitative evaluation of an array of atherosclerotic plaque characteristics (APCs). Further, application of computational fluid dynamics to CT enables determination of an array of coronary physiologic characteristics (CPCs), such as fractional flow reserve, endothelial wall shear stress, vorticity, particle resident time, axial plaque stress and plaque structural stress. To date, among CPCs, only ESS?in studies performed by our group?has been evaluated for its influence on future ACS risk, and was done so in select post-ACS populations of patients undergoing invasive imaging. Yet, the remainder of CPCs has not been evaluated for their prognostic importance to ACS risk, and none has been assessed in a stable population without known CAD. Further, combining CPCs with APCs for improved risk stratification of future ACS remains virtually unexplored. The OVERALL HYPOTHESIS of this proposal is that integration of coronary atherosclerosis with coronary physiologic features will improve identification of stable individuals who will subsequently experience ACS beyond any coronary feature alone. We propose 3 aims: AIM 1. To characterize CPCs associated with future ACS. Hypothesis: CPCs within arteries and exerted on plaques that will be implicated in future ACS will differ from CPCs within arteries and exerted on plaques that will not be implicated in future ACS. AIM 2. To integrate CPCs with APCs for enhanced identification of stable individuals who will experience future ACS. Hypothesis: A multi-dimensional framework that integrates the entirety of coronary atherosclerosis and pathophysiologic features will be superior to frameworks that do not integrate coronary atherosclerosis and pathophysiologic features for identification of individuals who will experience future ACS. AIM 3. To validate the clinical tool developed in Aim 2 in stable individuals with suspected CAD. Hypothesis: Applied to a general population of stable individuals with suspected but without known CAD enrolled in the randomized controlled SCOT-HEART trial, a clinical tool that integrates coronary atherosclerosis and coronary pathophysiologic features will be effective for prediction of ACS. If successful, the work in this proposal will provide the rationale for a novel diagnostic and prognostic paradigm that can be readily applied in clinical care of patients with suspected CAD. Further, this work will offer unique insights into the pathophysiology of CAD.

Funded by the NIH National Center for Advancing Translational Sciences through its Clinical and Translational Science Awards Program, grant number UL1TR002541.