Computed tomography-based high-risk coronary plaque score to predict acute coronary syndrome among patients with acute chest pain – Results from the ROMICAT II trial

Abstract

BackgroundCoronary computed tomography angiography (CTA) can be used to detect and quantitatively assess high-risk plaque features. ObjectiveTo validate the ROMICAT score, which was derived using semi-automated quantitative measurements of high-risk plaque features, for the prediction of ACS. Material and methodsWe performed quantitative plaque analysis in 260 patients who presented to the emergency department with suspected ACS in the ROMICAT II trial. The readers used a semi-automated software (QAngio, Medis medical imaging systems BV) to measure high-risk plaque features (volume of <60HU plaque, remodeling index, spotty calcium, plaque length) and diameter stenosis in all plaques. We calculated a ROMICAT score, which was derived from the ROMICAT I study and applied to the ROMICAT II trial. The primary outcome of the study was diagnosis of an ACS during the index hospitalization. ResultsPatient characteristics (age 57 ± 8 vs. 56 ± 8 years, cardiovascular risk factors) were not different between those with and without ACS (prevalence of ACS 7.8%). There were more men in the ACS group (84% vs. 59%, p = 0.005). When applying the ROMICAT score derived from the ROMICAT I trial to the patient population of the ROMICAT II trial, the ROMICAT score (OR 2.9, 95% CI 1.4–6.0, p = 0.003) was a predictor of ACS after adjusting for gender and ≥50% stenosis. The AUC of the model containing ROMICAT score, gender, and ≥50% stenosis was 0.91 (95% CI 0.86–0.96) and was better than with a model that included only gender and ≥50% stenosis (AUC 0.85, 95%CI 0.77–0.92; p = 0.002). ConclusionsThe ROMICAT score derived from semi-automated quantitative measurements of high-risk plaque features was an independent predictor of ACS during the index hospitalization and was incremental to gender and presence of ≥50% stenosis.