In the context of aortic hemodynamics, uncertainties affecting blood flow simulations hamper their translational potential as supportive technology in clinics. Computational fluid dynamics (CFD) simulations under rigid-walls assumption are largely adopted, even though the aorta contributes markedly to the systemic compliance and is characterized by a complex motion. To account for personalized wall displacements in aortic hemodynamics simulations, the moving-boundary method (MBM) has been recently proposed as a computationally convenient strategy, although its implementation requires dynamic imaging acquisitions not always available in clinics.

In this study we aim to clarify the real need for introducing aortic wall displacements in CFD simulations to accurately capture the large-scale flow structures in the healthy human ascending aorta (AAo). To do that, the impact of wall displacements is analyzed using subject-specific models where two CFD simulations are performed imposing (1) rigid walls, and (2) personalized wall displacements adopting a MBM, integrating dynamic CT imaging and a mesh morphing technique based on radial basis functions. The impact of wall displacements on AAo hemodynamics is analyzed in terms of large-scale flow patterns of physiological significance, namely axial blood flow coherence (quantified applying the Complex Networks theory), secondary flows, helical flow and wall shear stress (WSS).

From the comparison with rigid-wall simulations, it emerges that wall displacements have a minor impact on the AAo large-scale axial flow, but they can affect secondary flows and WSS directional changes. Overall, helical flow topology is moderately affected by aortic wall displacements, whereas helicity intensity remains almost unchanged. We conclude that CFD simulations with rigid-wall assumption can be a valid approach to study large-scale aortic flows of physiological significance.