Inflow boundary conditions for image-based computational hemodynamics: impact of idealized versus measured velocity profiles in the human aorta.

Here we analyse the influence of assumptions made on boundary conditions (BCs) extracted from phase-contrast magnetic resonance imaging (PC-MRI) in vivo measured flow data, applied on hemodynamic models of human aorta. This study aims at investigating if the imposition of BCs based on defective information, even when measured and specific-to-the-subject, might lead to misleading numerical representations of the aortic hemodynamics. In detail, we focus on the influence of assumptions regarding velocity profiles at the inlet section of the ascending aorta, incorporating phase flow data within the computational model. The obtained results are compared in terms of disturbed shear and helical bulk flow structures, when the same measured flow rate is prescribed as inlet BC in terms of 3D or 1D (axial) measured or idealized velocity profiles. Our findings clearly indicate that: (1) the imposition of PC-MRI measured axial velocity profiles as inflow BC may capture disturbed shear with sufficient accuracy, without the need to prescribe (and measure) realistic fully 3D velocity profiles; (2) attention should be put in setting idealized or PC-MRI measured axial velocity profiles at the inlet boundaries of aortic computational models when bulk flow features are investigated, because helical flow structures are markedly affected by the BC prescribed at the inflow. We conclude that the plausibility of the assumption of idealized velocity profiles as inlet BCs in personalized computational models can lead to misleading representations of the aortic hemodynamics both in terms of disturbed shear and bulk flow structures.