A parametric model for studying the aorta hemodynamics by means of the computational fluid dynamics

Perturbed aorta hemodynamics, as for the carotid and the coronary artery, has been identified as potential predicting factor for cardiovascular diseases. In this study, we propose a parametric study based on the computational fluid dynamics with the aim of providing information regarding aortic disease. In particular, the blood flow inside a parametrized aortic arch is computed as a function of morphological changes of baseline aorta geometry. Flow patterns, wall shear stress, time average wall shear stress and oscillatory shear index were calculated during the cardiac cycle. The influence of geometrical changes on the hemodynamics and on these variables was evaluated. The results suggest that the distance between inflow and aortic arch and the angle between aortic arch and descending trunk are the most influencing parameters regarding the WSS-related indices while the effect of the inlet diameter seems limited. In particular, an increase of the aforementioned distance produces a reduction of the spatial distribution of the higher values of the time average wall shear stress and of the oscillatory shear index independently on the other two parameters while an increase of the angle produce an opposite effect. Moreover, as expected, the analysis of the wall shear stress descriptors suggests that the inlet diameter influences only the flow intensity. As conclusion, the proposed parametric study can be used to evaluate the aorta hemodynamics and could be also applied in the future, for analyzing pathological cases and virtual situations, such as pre- and/or post-operative cardiovascular surgical states that present enhanced changes in the aorta morphology yet promoting important variations on the considered indexes.The authors gratefully acknowledge the research support of the Spanish Ministry of Econ339 omy and Competitiveness through the research projects DPI-2016-76630-C2-1-R and DPI2017-83259-R (AEI/FEDER,UE). The support of the Instituto de Salud Carlos III (ISCIII) through 341 the CIBER-BBN initiative and the project Patient-Specific Modelling of the Aortic valve replacement: Advance towards a Decision Support System (DeSSAValve) is highly appreciated