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  • Title: Evaluation of aortic valve stenosis using cardiovascular magnetic resonance: comparison of an original semiautomated analysis of phase-contrast cardiovascular magnetic resonance with Doppler echocardiography.
    Author: Defrance C, Bollache E, Kachenoura N, Perdrix L, Hrynchyshyn N, Bruguière E, Redheuil A, Diebold B, Mousseaux E.
    Journal: Circ Cardiovasc Imaging; 2012 Sep 01; 5(5):604-12. PubMed ID: 22798520.
    Abstract:
    BACKGROUND: Accurate quantification of aortic valve stenosis (AVS) is needed for relevant management decisions. However, transthoracic Doppler echocardiography (TTE) remains inconclusive in a significant number of patients. Previous studies demonstrated the usefulness of phase-contrast cardiovascular magnetic resonance (PC-CMR) in noninvasive AVS evaluation. We hypothesized that semiautomated analysis of aortic hemodynamics from PC-CMR might provide reproducible and accurate evaluation of aortic valve area (AVA), aortic velocities, and gradients in agreement with TTE. METHODS AND RESULTS: We studied 53 AVS patients (AVA(TTE)=0.87±0.44 cm(2)) and 21 controls (AVA(TTE)=2.96±0.59 cm(2)) who had TTE and PC-CMR of aortic valve and left ventricular outflow tract on the same day. PC-CMR data analysis included left ventricular outflow tract and aortic valve segmentation, and extraction of velocities, gradients, and flow rates. Three AVA measures were performed: AVA(CMR1) based on Hakki formula, AVA(CMR2) based on continuity equation, AVA(CMR3) simplified continuity equation=left ventricular outflow tract peak flow rate/aortic peak velocity. Our analysis was reproducible, as reflected by low interoperator variability (<4.56±4.40%). Comparison of PC-CMR and TTE aortic peak velocities and mean gradients resulted in good agreement (r=0.92 with mean bias=-29±62 cm/s and r=0.86 with mean bias=-12±15 mm Hg, respectively). Although good agreement was found between TTE and continuity equation-based CMR-AVA (r>0.94 and mean bias=-0.01±0.38 cm(2) for AVA(CMR2), -0.09±0.28 cm(2) for AVA(CMR3)), AVA(CMR1) values were lower than AVA(TTE) especially for higher AVA (mean bias=-0.45±0.52 cm(2)). Besides, ability of PC-CMR to detect severe AVS, defined by TTE, provided the best results for continuity equation-based methods (accuracy >94%). CONCLUSIONS: Our PC-CMR semiautomated AVS evaluation provided reproducible measurements that accurately detected severe AVS and were in good agreement with TTE.
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