The role of coronary artery calcium scoring in the prediction of coronary artery disease based on non-contrast non-cardiac chest CT scans in airline pilots

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Background The aim of the present study was to explore the value of coronary artery calcium score (CACS) using non-gated, non-contrast chest computed tomography (NCCT) to predict coronary artery disease (CAD) in airline pilots. Methods Pilots with coronary calcification found on NCCT were consecutively enrolled into this study. All received a coronary computed tomography angiography (CCTA) examination. The coronary artery calcium score (CACS) was evaluated on NCCT using the Agatston method. CCTA images were analyzed using a semi-automated software. Coronary Artery Disease Reporting and Data System (CAD-RADS) scoring categorized coronary stenosis. Results A total of 217 male pilots were included, of which 49 were diagnosed with significant CAD (CAD-RADS category 3 or higher). Pilots with significant CAD had much higher CACS (324.28 ± 389.02 vs. 39.16 ± 68.88; p < 0.001). Plaque volumetric measurements showed that total plaque volume (1,103.50 ± 285.51 mm3 vs. 913.18 ± 277.45 mm3; p < 0.001) and calcified plaque volume (149.77 ± 160.71 mm3 vs. 36.42 ± 26.86 mm3; p < 0.001) were more pronounced in individuals in the significant CAD group than those in the non-significant CAD group. A multivariate analysis demonstrated that CACS (odds ratio 1.01; 95% confidence interval 1.005–1.014; p < 0.001) was the only independent risk factor of significant CAD but traditional cardiovascular risk factors, pre-existing medication regimens, or prolonged flight duration were not. CACS positively correlated with total plaque volume (r = 0.156; p = 0.027) and calcified plaque volume (r = 0.434; p < 0.001). Receiver operating characteristic curve analysis showed the area under the curve for the CACS in diagnosing significant CAD was 0.891 (p < 0.001). Conclusions CACS assessed using NCCT was significantly associated with CAD-RADS category 3 or higher, as confirmed by CCTA, which indicates that it may serve as a robust predictor for diagnosing significant CAD among airline pilots.

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