To evaluate the diagnostic accuracy of aortic valve area (AVA) assessment with 320-detector Computed Tomography (MDCT) compared to transthoracic echocardiography (TTE) in a population with mild to severe aortic valve stenosis. AVA was estimated in 169 patients by planimetry on MDCT images (AVA(MDCT)) and by the continuity equation with TTE (AVA(TTE)). To generate a reference AVA (AVA(REF)) we used the stroke volume from MDCT divided by the velocity time integral from CW Doppler by TTE (according to the continuity equation: stroke volume in LVOT = stroke volume passing the aortic valve). AVA(REF) was used as the reference to compare both measures against, since it bypasses the assumption of LVOT being circular in the continuity equation and the potential placement error of PW Doppler in the LVOT. The mean (±SD) age of the patients was 71 (±9) years, 113 (67%) were males. Mean AVA(TTE) was 0.93 (±0.33) cm(2), mean AVA(MDCT) was 0.99 (±0.36) cm(2) and mean AVA(REF) was 1.00 (±0.39) cm(2). The mean difference between AVA(TTE) and AVA(MDCT) was -0.06 cm(2), p = 0.001, mean difference between AVA(TTE) and AVA(REF) was -0.06 cm(2), p < 0.001, and mean difference between AVA(MDCT) and AVA(REF) was -0.01 cm(2), p = 0.60. Calcification of the aortic valve quantified by Agatston score, significantly decreased the correlation between AVA(MDCT) and AVA(REF), (r low Agatston = 0.90, r high Agatston = 0.57). MDCT measured AVA is slightly larger than AVA measured by TTE (0.06 cm(2)). The accuracy and precision errors on AVA measurements are comparable for MDCT and TTE. Valvular calcification may primarily affect the accuracy of AVA(MDCT).
International Journal of Cardiovascular Imaging, 2014, Vol 30, Issue 1, p. 165-173
Comparative Study; Evaluation Studies; Journal Article; Research Support, Non-U.S. Gov't; Aged; Aged, 80 and over; Aortic Valve; Aortic Valve Stenosis; Calcinosis; Echocardiography, Doppler; Female; Humans; Male; Middle Aged; Multidetector Computed Tomography; Predictive Value of Tests; Radiographic Image Interpretation, Computer-Assisted; Severity of Illness Index