A revised methodology for aortic-valvar complex calcium quantification for transcatheter aortic valve implantation

Aims We sought to optimize a method for quantification of the calcium in the aortic-valvar complex for the prediction of significant paravalvular leak (PVL) after transcatheter aortic valve implantation (TAVI). Methods and results All patients had severe symptomatic aortic stenosis and were treated with balloon-expandable TAVI (Sapien/Sapien-XT, Edwards Lifesciences LLC, Irvine, CA, USA). In order to correct for precise annular sizing, only patients with available contrast computed tomography (CT) data for measurements were included (n = 198). Paravalvular leak was quantified using peri-procedural transoesophageal echocardiography by Valve Academic Research Consortium-2 (VARC-2) criteria (grade >= moderate was considered significant). Adetailed region-of-interest methodology separated quantification of calcium in each of the aortic leaflets to that in the left ventricular outflow tract (LVOT) and was used to predict PVL in receiver operator characteristic curve analyses. For non-contrast scans, the greatest discriminatory value for PVL was seen at the 450 Hounsfield Unit (HU) threshold for detection (volume >= 626 mm(3)), whereas for contrast scans it was at 850 HU (>= 235 mm3). Left ventricular outflow tract calcium predicted PVL but only as a binary variable with no incremental value of quantification. In a multivariable binary logistic regression model, annulus area >= prosthesis area (OR 3.5, 95% CI 1.5-8.2, P = 0.005), contrast leaflet calcium volume (850-HU threshold) >= 235 mm(3) (OR 2.8, 95% CI 1.2-6.7, P = 0.023), and presence of LVOT calcium (OR 2.8, 95% CI 1.2-7.0, P = 0.022) were independent predictors for PVL >= moderate. Conclusion Both leaflet and LVOT calcium are significant predictors of PVL and exert an important synergistic influence on this complication, even in appropriately sized valves. With careful attention to thresholds for detection, clinically relevant leaflet calcium volumes can be identified with either non-contrast or contrast CT scans.