CCTA-derived high-risk endothelial shear stress metrics at baseline identified plaques that caused future acute coronary syndromes in 101 patients over 3.4 years.
Do CCTA-derived high-risk endothelial shear stress metrics predict future acute coronary syndromes in stable patients without known CAD?
Non-invasive CCTA-derived high-risk endothelial shear stress metrics can identify coronary plaques at risk of causing future acute coronary syndromes.
Absolute Event Rate: 0% vs 0%
Abstract Introduction Local hemodynamic blood flow patterns (endothelial shear stress, ESS) surrounding coronary plaques drive atherosclerosis behaviour to progress, destabilize, or remain quiescent. While presence of high-risk ESS and anatomic metrics derived from invasive intravascular imaging synergistically enhance risk-stratification of plaques likely to cause acute coronary syndromes (ACS), these prognostic insights have not been investigated in non-invasive coronary computed tomography angiography (CCTA) with its potential for broader screening. Purpose We therefore investigated if CCTA-derived ESS metrics accurately predict plaques causing future ACS. Methods We evaluated 452 patients, with 3,480 lesions, from 1,996 arteries, from the ICONIC study, a nested case-control study within the CONFIRM registry of stable patients without known CAD, who had a CCTA at baseline, and subsequently did/did not experience a blinded core lab-adjudicated ACS at 3.4 years follow-up. ESS metrics were calculated by computational fluid dynamics (CFD) on segmented CCTA images using validated AI-QCT software (Figure): ESS (min/max), max ESSG (gradient, low ESS immediately adjacent to high ESS), axial plaque stress (APS, slope of plaque topography), vorticity (swirling of blood). Results The propensity matched cohort included 101 ACS patients with 101 culprit lesions vs 101 control patients with 807 non-culprit lesions. Plaques that displayed high-risk ESS metrics were at greater risk to become culprit plaques. Prognostic values of CFD metrics alone or in combination with a representative anatomic metric are shown in Table. Conclusions We demonstrate here, for the first time, that CCTA-derived high-risk ESS metrics at baseline identify plaques and patients associated with future ACS. Our future studies will assess prediction of adverse clinical outcomes combining high-risk biomechanical metrics with high-risk atherosclerotic plaque anatomic characteristics to optimize risk-stratification of individual coronary plaques.Figure Table
Ahmed et al. (Sat,) reported a other. CCTA-derived high-risk endothelial shear stress metrics at baseline identified plaques that caused future acute coronary syndromes in 101 patients over 3.4 years.
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