PURPOSE To understand the reliability of low-dose chest computed tomography (LDCT) in coronary artery calcification (CAC) assessment and evaluate the performance of different reconstruction kernels against the standard cardiac computed… Click to show full abstract
PURPOSE To understand the reliability of low-dose chest computed tomography (LDCT) in coronary artery calcification (CAC) assessment and evaluate the performance of different reconstruction kernels against the standard cardiac computed tomography (CaCT) as reference. MATERIALS AND METHODS Patients from the NELCIN-B3 screening program who underwent CaCT and LDCT scans were analyzed retrospectively. LDCT were reconstructed with smooth, standard, and sharp kernels (Group B1, B2 and B3) to compare against standard CaCT (Group A). The image quality was evaluated by noise value, signal-to-noise ratio (SNR), and contrast to noise ratio (CNR); moreover, radiation dose was recorded for both scans. Coronary artery calcification scores (CACS) were measured with volume, mass and Agatston standards. Agatston score was divided into four cardiovascular risk categories (0, 1-99, 100-399, and >400). The agreement in CACS and risk classification between LDCT and CaCT was analyzed by intra-group correlation coefficient (ICC) and Kappa test. RESULTS The sensitivity of diagnosing CAC with LDCT was 98.5% (330/335) regardless of reconstruction kernels. Group B1 demonstrated the highest agreement in raw CACS (ICC volume 0.932; mass 0.904; Agatston 0.906; all p < 0.001) and risk classification (kappa 0.757, 95% CI 0.70-0.82). Smooth-kernel reconstruction achieved lower image noise, better SNR and CNR than other kernels. The effective radiation dose in of LDCT was 41.2% lower than that of the calcium scan (p < 0.001). CONCLUSION Reconstructing LDCT with a smooth kernel in LDCT could provide a reliable imaging method to detect and quantitatively evaluate CAC, potentially expanding the application of LDCT lung screening to incidental findings of cardiovascular disease.
               
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