Cardiac computed tomography imaging biomarkers for prediction of new-onset heart failure: Multi-ethnic study of atherosclerosis

Abstract

Background

Heart failure (HF) is associated with a large socioeconomic burden. The growth of cardiac computed tomography (CT) has allowed for investigation of new applications in predicting risk of cardiovascular disease.

Objective

To determine if cardiac CT imaging biomarkers could predict new-onset HF and improve discrimination in a current HF prediction model.

Methods

Participants of the Multi-Ethnic Study of Atherosclerosis (MESA) were included to evaluate new-onset HF during a median follow-up period of 17.7 years. Cardiac CT imaging biomarkers measured include left ventricular size indexed (LVSi) and calcification of the coronary arteries (CAC), aortic valve (AVC), mitral annulus (MAC), and thoracic aorta (TAC). We evaluated if cardiac CT variables improved the 10-year risk prediction of new-onset HF by the Pooled Cohort equations to Prevent HF (PCP–HF) score.

Results

Among 6,667 MESA participants (52.7 ​% female), 426 events of new-onset HF occurred. Cox model analysis revealed log transformed CAC (HR 1.11; 95 ​% CI 1.06–1.16; p ​< ​0.001), log transformed AVC (HR 1.06; 95 ​% CI 1.01–1.12; p ​= ​0.014), and LVSi (HR 1.17; 95 ​% CI 1.12–1.21; p ​< ​0.001) were significantly associated with new-onset HF. Area under the curve (AUC) discrimination of new-onset HF by the PCP-HF score was improved with incorporation of cardiac CT imaging biomarkers.

Conclusion

Cardiac CT imaging biomarkers provide anatomic risk factors that improve the prediction of new-onset HF. Coronary and valvular calcifications may signal comorbidities associated with HF. LVSi may reflect left ventricular remodeling associated with HF.