Validation of CTA-based closed-loop coronary artery flow simulations against intravascular Doppler velocity and pressure measurements.

The modeling assumptions involved in computational fluid dynamics (CFD) simulations of coronary arteries using coronary computed angiography (CTA) have not been thoroughly validated. These modeling assumptions can lead to uncertainties in simulated velocities and pressure, and consequently, other hemodynamic markers, such as wall shear stresses. In this study, we validated a state-of-the-art coronary CTA-CFD simulation strategy against intravascular Doppler velocity and pressure measurements. 3D coronary models were reconstructed using coronary CTA in 13 patients. Intravascular Doppler velocities and pressures were obtained in 18 arteries over 120 ± 55 cardiac cycles to validate CTA-CFD simulations. A lumped parameter network (LPN) was tuned to capture each patient's heart and distal coronary circulation, and coupled to the CFD solver. For each patient, Murray's Law coefficient was varied from 2.0 to 3.0 in increments of 0.2. The simulated velocities and pressures were compared to intravascular measurements. The correlation between intravascular and CTA-CFD parameters showed no statistically significant correlation for velocity (r=-0.13 and p = 0.60), while both flow rates (r = 0.77, p < 0.01) and pressures (r = 0.88, p < 0.01) demonstrated strong correlation and statistical significance. When considering the intra-patient cycle-to-cycle variabilities in invasive measurements, velocity in 11 of 18 and pressures in 7 of 18 coronary arteries were within one standard deviation of intravascular measurement variability. CTA-CFD simulations showed statistically significant correlations for intravascular flows and pressures, whereas no meaningful correlation was observed for velocity. These findings highlight the influence of measurement variability and modeling assumptions. Future studies should consider the inherent uncertainties in CTA-CFD, especially when estimating absolute hemodynamic parameters such as velocity and pressure, and aim to refine boundary conditions and validation strategies to improve accuracy.