Abstract 17650: Coronary Plaque Burden and Left Ventricular Mass Assessed by Cardiac Computed Tomography Angiography in Prediction of Cardiovascular Events

Abstract

Background: Coronary artery calcium score (CACS) measured by plain computed tomography (CT) is shown to be an important prognostic factor for subsequent cardiovascular events (CVEs). Recently, cardiac CT angiography (CTA) enables us to evaluate coronary plaque burden (CBP), and simultaneously left ventricular myocardial mass (LVM) which is considered to be associated with CVEs. However, it is not well known whether CBP and LVM assessed by cardiac CTA have additional value in prediction of future CVEs compared to CACS.

Methods: We studied 464 patients (65 ± 10 years, 60% men) referred for cardiac CT. CACS was measured using Agatston method. From CTA images, CPB was evaluated in accordance with 17 coronary segments. The LVM was measured using commercial software, and indexed to the body surface area (LVMI). Patients were followed up as to the occurrence of CVEs (cardiac death, acute coronary syndrome, late coronary revascularization, stroke, aortic disease, and heart failure requiring hospitalization).

Results: During a 3.1 ± 1.1 years follow-up period, 47 CVEs were documented.The LVMI was positively correlated with CACS (r = 0.29, p < 0.001) and CPB (r = 0.29, p < 0.001), respectively. Cox-proportional hazards analyses revealed that higher log-transformed CACS (hazard ratio [HR] 1.76 per 1.00, 95% confident interval [CI] 1.27-2.49, p < 0.001), larger CBP (HR 1.19 per 1 segment, 95% CI 1.09-1.31, p < 0.001), and high LVMI (median: >76.9 g/m³, HR 2.58, 95% CI 1.31-5.48, p = 0.006) were associated with CVEs after adjustment of clinical parameters (age, gender, and traditional cardiovascular risk factors). On the receiver operator characteristic analyses, the area under the curves (AUCs) of the addition of clinical parameters to CACS, CBP, or LVMI in prediction of CVEs were 0.74, 0.75, and 0.72, respectively. There was no significant difference in predictive power of CVEs between CACS and CBP. However, the AUC (0.78) of the addition of clinical parameters to both CBP and LVMI in prediction of CVEs was significantly larger than that of the addition of clinical parameters to CACS (p = 0.044).

Conclusions: CPB and LVMI were independent predictors of CVEs. Furthermore, the simultaneous evaluation of CPB and LVM assessed by cardiac CTA can help predict future CVEs over CACS.