Optimized categorization algorithm of coronary artery calcification score on non-gated chest low-dose CT screening using iterative model reconstruction technique.

Abstract Objectives To investigate the optimized categorization algorithm of coronary artery calcification score (CACS) for more accurate risk assessment on non-gated chest low-dose CT (LDCT) screening using iterative model reconstruction (IMR) technique. Methods We enrolled 102 patients who required coronary artery CTA examination and had coronary artery calcification (CAC) in this study. The CACS on non-gated LDCT and ECG-gated CT images were both measured by Agatston analysis software on Philips workstation. Results According to the original algorithm (1–100, 100–400 and >400), the CACS measured by non-gated LDCT scan showed a good agreement with ECG-gated CT scan (weighted kappa value of 0.602, P  Conclusions The CACS on non-gated LDCT may have been underestimated. We therefore developed an optimized categorization algorithm of non-gated CACS in this study.