Quantification of functional hemodynamics in aortic valve disease using cardiac computed tomography angiography

Cardiac computed tomography angiography (CTA) is the preferred modality for preoperative planning in aortic valve stenosis. However, it cannot provide essential functional hemodynamic data, specifically the mean transvalvular pressure gradient (MPG). This study aims to introduce a computational fluid dynamics (CFD) approach for MPG quantification using cardiac CTA, enhancing its diagnostic value.

Twenty patients underwent echocardiography, cardiac CTA, and invasive catheterization for pressure measurements. Cardiac CTA employed retrospective electrocardiographic gating to capture multi-phase data throughout the cardiac cycle. We segmented the region of interest based on mid-systolic phase cardiac CTA images. Then, we computed the average flow velocity into the aorta as the inlet boundary condition, using variations in end-diastolic and end-systolic left ventricular volume. Finally, we conducted CFD simulations using a steady-state model to obtain pressure distribution within the computational domain, allowing for the derivation of MPG.

The mean value of MPG, measured via invasive catheterization (MPG_Inv), echocardiography (MPG_Echo), and cardiac CTA (MPG_CT), were 51.3 ± 28.4 mmHg, 44.8 ± 19.5 mmHg, and 55.8 ± 25.6 mmHg, respectively. In comparison to MPG_Inv, MPG_CT exhibited a higher correlation of 0.91, surpassing that of MPG_Echo, which was 0.82. Moreover, the limits of agreement for MPG_CT ranged from -27.7 to 18.7, outperforming MPG_Echo, which ranged from -40.1 to 18.0.

The proposed method based on cardiac CTA enables the evaluation of MPG for aortic valve stenosis patients. In future clinical practice, a single cardiac CTA examination can comprehensively assess both the anatomical and functional hemodynamic aspects of aortic valve disease.