Ethnic differences in coronary plaque and epicardial fat volume quantified using computed tomography
- 26 September 2016
- journal article
- research article
- Published by Springer Nature in The International Journal of Cardiovascular Imaging
- Vol. 33 (2) , 241-249
Abstract
Epidemiological studies observed a higher prevalence of coronary atherosclerosis in South Asians when compared to Caucasians, but quantitative computed tomography differences in aggregate plaque volume (APV) and epicardial fat volume (EFV) between South Asians, Southeast or East Asians (SEEAs) and Caucasians remain unknown. We aimed to compare APV and EFV quantified on computed-tomographic-coronary-angiography (CTCA) between South Asian, SEEA and Caucasian populations residing in Australia. Age, gender and body-mass-index matched subjects from three ethnic groups who underwent clinically indicated 320-detector CTCA were retrospectively analysed. Percentage APV in the first 5 cm of the left anterior descending artery (LAD) and EFV were quantified using dedicated software (Vital Images, USA). One-hundred-and-fifty subjects (average age = 57.7 years, 56 % male, n = 50 in each ethnic group) were analysed. Mean LAD percentage APV was highest in South Asians (44.5 ± 8.4 % vs. 37.5 ± 6.5 % in SEEAs and 39.5 ± 6.4 % in Caucasians, P = 0.00001). South Asian ethnicity predicted LAD APV above traditional risk factors on multivariate analysis (P = 0.000002). EFV was significantly higher in both South Asians (103.2 ± 41.7 cm3 vs. 85.8 ± 39.4 cm3, P = 0.035) and SEEAs (110.8 ± 36.9 cm3 vs. 85.8 ± 39.4 cm3, P = 0.001) when compared with Caucasians. In this cohort LAD percentage APV and EFV, as quantified on CTCA, differs between South Asians, SEEA and Caucasian populations, with higher LAD APV observed in South Asians and lower EFV in Caucasians. Atherosclerotic volume in LAD was best predicted by South Asian ethnicity above traditional risk factors and EFV. Further research is required to establish whether APV and EFV quantification can improve cardiac risk prediction in the South Asian population.Keywords
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