Abstract
RATIONALE AND OBJECTIVES: To investigate the relationship between the pericoronary adipose tissue CT mean attenuation (PCAT(MA)) measurement and image reconstruction parameters (adaptive statistical iterative reconstruction-veo (ASIR-V) percentage, kernel, and slice thickness). MATERIALS AND METHODS: One hundred and ninety-eight consecutive patients underwent CT coronary angiography at 100 kilovoltage peak (kVp) (n = 102) and 120 kVp (n = 96) were included. All scans were reconstructed by three means: 1. with 11 different ASIR-V percentages, standard kernel and 0.625 mm; 2. with soft, standard, detail, and bone kernels, 60 % ASIR-V, and 0.625 mm; 3. at 0.625 mm and 1.25 mm slice thickness, standard kernel and 60 % ASIR-V. PCAT(MA) of the three main coronary arteries was calculated using a dedicated software. Linear regression, analysis of variance (ANOVA), Friedman test, and paired t-test were used for statistical analysis. RESULTS: Linear regression of pooled average data showed that the PCAT(MA) was positively and linearly correlated with the ASIR-V percentage (all R squared >0.99). Regression analysis of individual data showed that most R squared were greater than 0.8 or 0.9, but their slope consisted of a relatively wide range. The difference of PCAT(MA) among different kernels for each coronary artery reached statistically significant levels (P < 0.001), particularly for the difference between standard and bone kernel. Most of the differences between 0.625 mm and 1.25 mm for LAD, LCX, and RCA at 100 kVp and 120 kVp reached statistical significance (P < 0.001). CONCLUSIONS: PCAT(MA) correlates linearly with the strength of ASIR-V. Reconstruction kernel and slice thickness also affect PCAT(MA), especially for the sharp kernels.