Quantification of aortic valve calcification in contrast enhanced computer tomography

Abstract Introduction Aortic valve calcification (AVC) is linked to higher gradients and worse prognosis in aortic stenosis. Current guidelines recommend calcium scoring of the as additional factor for decision making low-flow, low-gradient Calcium Scoring performed by native computed tomography (CT). For planning interventional replacement (TAVR) a second scan with contrast agent (CECT) needed at cost radiation exposure work up time. The aim this study assess validate an estimate conversion quantification using CECT without imaging. Methods Agatston score was measured on CT 45 patients used reference. In enhanced CT, mean attenuation values Hounsfield units (HU) were determined placement region interest ascending aorta standard deviation 4xHU threshold. AVC segmented semi-automatically. A formula created plotting versus linear regression. Validation calculated established Intra-class coefficient (ICC) Bland Altman analysis. Results regression model yielded 691 + 1.83 × AVCCECT. validation cohort (n=20) showed high agreement (r2=0.802, ICC 0.915 (CI 95%: 0.786–0.966) p<0.001, p=0.055). Conclusion Approximation our from has shown excellent reliability determine calcification. Further studies are extend finding larger cohorts diverse clinical environments. Funding Acknowledgement Type funding sources: None.