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J Thorac Imaging ; 32(6): 378-382, 2017 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-28817459

RESUMO

PURPOSE: Excessive quantity of epicardial adipose tissue (EAT) is considered a risk factor for coronary artery disease (CAD). There are limited data, however, on the relationship between the quality of EAT and CAD. We investigated the association between the density and volume of EAT and subclinical CAD defined by positive coronary artery calcification (CAC), using computed tomography (CT). MATERIALS AND METHODS: We reviewed 609 consecutive CT scans of patients with a mild to moderate risk for CAD to assess the EAT volume, which was measured manually by tracing the parietal pericardial sac on axial images. Fat density was recorded in mean Hounsfield units (HU), and CAC was measured using the Agatston method. RESULTS: The mean patients' age was 50±11 years, and 393 (64.5%) were men. Overall, CAC was present in 135 (22%) patients, of whom 97 (72%) were men and 38 (28%) were women. The mean EAT volume and density were 65±27 cm and -87.0±3.4 HU, respectively. Patients with CAC had significantly higher EAT volume (74±27 vs. 62±26 cm, P<0.001) and lower EAT density (-88±3 vs. -87±3.4 HU, P<0.001) compared with patients without CAC. Multivariate regression analysis showed that both EAT density (hazard ratio, 0.879; 95% confidence interval, 0.817-0.946; P=0.001) and EAT volume >100 cm (hazard ratio, 1.693; 95% confidence interval, 1.256-2.999; P=0.029) predicted the presence of CAC. CONCLUSIONS: Both the quality and quantity of EAT derived from noncontrast CT scan predict subclinical CAD, with lower density and higher volume of epicardial fat associated with higher CACs.


Assuntos
Tecido Adiposo/diagnóstico por imagem , Aterosclerose/diagnóstico por imagem , Doença da Artéria Coronariana/diagnóstico por imagem , Pericárdio/diagnóstico por imagem , Tomografia Computadorizada por Raios X/métodos , Estudos Transversais , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Reprodutibilidade dos Testes , Fatores de Risco , Índice de Gravidade de Doença
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