Coronary flow reserve (CFR) is markedly reduced in patients with severe aortic valve stenosis (AS), but the exact mechanisms underlying this impairment of CFR in AS remain unclear. Reduced CFR is the key mechanism leading to myocardial ischemia symptoms and adverse outcomes in AS patients. The objective of this study was to develop an explicit mathematical model formulated with a limited number of parameters that describes the effect of AS on left coronary inflow patterns and CFR. We combined the mathematical V(3) (ventricular-valvular-vascular) model with a new lumped-parameter model of coronary inflow. One thousand Monte-Carlo computational simulations with AS graded from mild up to very severe were performed within a wide range of physiological conditions. There was a good agreement between the CFR values computed with this new model and those measured in 24 patients with isolated AS (r = 0.77, P < 10(-4)). A global sensitivity analysis showed that the valve effective orifice area (EOA) was the major physiological determinant of CFR (total sensitivity index = 0.87). CFR was markedly reduced when AS became severe, i.e., when EOA was <1.0 cm(2), and was generally exhausted when the EOA was <0.5-0.6 cm(2). The reduction of CFR that is associated with AS can be explained by the concomitance of 1) reduced myocardial supply as a result of decreased coronary perfusion pressure, and 2) increased myocardial metabolic demand as a result of increased left ventricular workload.

Early detection and accurate estimation of aortic stenosis (AS) severity are the most important predictors of successful long-term outcomes in patients. Current clinical parameters used for evaluation of the AS severity have several limitations including flow dependency. Estimation of AS severity is specifically challenging in patients with low-flow and low transvalvular pressure gradient conditions. A proper diagnosis in these patients needs a comprehensive evaluation of the left ventricle (LV) hemodynamic loads. This study has two objectives: (1) developing a lumped-parameter model to describe the ventricular-valvular-arterial interaction and to estimate the LV stroke work (SW); (2) introducing and validating a new index, the normalized stroke work (N-SW), to assess the global hemodynamic load imposed on the LV. N-SW represents the global hemodynamic load that the LV faces for each unit volume of blood ejected. The model uses a limited number of parameters which all can be measured non-invasively using current clinical imaging modalities. The model was first validated by comparing its calculated flow waveforms with the ones measured using Cardiovascular Magnetic Resonance (CMR) in 49 patients and 8 controls. A very good correlation and concordance were found throughout the cycle (median root mean square: 12.21 mL/s) and between the peak values (r = 0.98; SEE = 0.001, p<0.001). The model was then used to determine SW using the parameters measured with transthoracic Doppler-echocardiography (TTE) and CMR. N-SW showed very good correlations with a previously-validated index of global hemodynamic load, the valvular arterial impedance (), using data from both imaging modalities (TTE: r = 0.82, SEE = 0.01, p<0.001; CMR: r = 0.74, SEE = 0.01, p<0.001). Furthermore, unlike , N-SW was almost independent from variations in the flow rate. This study suggests that considering N-SW may provide incremental diagnostic and prognostic information, beyond what standard indices of stenosis severity and provide, particularly in patients with low LV outflow.

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BackgroundValve effective orifice area EOA and transvalvular mean pressure gradient (MPG) are the most frequently used parameters to assess aortic stenosis (AS) severity. However, MPG measured by cardiovascular magnetic resonance (CMR) may differ from the one measured by transthoracic Doppler-echocardiography (TTE). The objectives of this study were: 1) to identify the factors responsible for the MPG measurement discrepancies by CMR versus TTE in AS patients; 2) to investigate the effect of flow vorticity on AS severity assessment by CMR; and 3) to evaluate two models reconciling MPG discrepancies between CMR/TTE measurements.MethodsEight healthy subjects and 60 patients with AS underwent TTE and CMR. Strouhal number (St), energy loss (EL), and vorticity were computed from CMR. Two correction models were evaluated: 1) based on the Gorlin equation (MPGCMR-Gorlin); 2) based on a multivariate regression model (MPGCMR-Predicted).ResultsMPGCMR underestimated MPGTTE (bias = −6.5 mmHg, limits of agreement from −18.3 to 5.2 mmHg). On multivariate regression analysis, St (p = 0.002), EL (p = 0.001), and mean systolic vorticity (p < 0.001) were independently associated with larger MPG discrepancies between CMR and TTE. MPGCMR-Gorlin and MPGTTE correlation and agreement were r = 0.7; bias = −2.8 mmHg, limits of agreement from −18.4 to 12.9 mmHg. MPGCMR-Predicted model showed better correlation and agreement with MPGTTE (r = 0.82; bias = 0.5 mmHg, limits of agreement from −9.1 to 10.2 mmHg) than measured MPGCMR and MPGCMR-Gorlin.ConclusionFlow vorticity is one of the main factors responsible for MPG discrepancies between CMR and TTE.

The Doppler-echocardiographic parameters and criteria proposed in the guidelines lack sensitivity for the detection of BMV dysfunction. The utilization of a DVI < 0.35 or an EOA-D > 1 SD improved the sensitivity (>90%) for the detection of moderate-to-severe dysfunction, but the sensitivity remained suboptimal (<65%) for detection of mild dysfunction.