Mechanical & Materials Engineering, Department of

 

ORCID IDs

0000-0001-8151-1897

0000-0003-2637-0299

Date of this Version

2019

Citation

Appl. Sci. 2019, 9, 807

Comments

© 2019 by the authors.

Open access

doi:10.3390/app9040807

Abstract

Graft repair of aortic coarctation is commonly used to mimic the physiological aortic arch shape and function. Various graft materials and shapes have been adopted for the surgery. The goal of this work is to quantitatively assess the impact of graft materials and shapes in the hemodynamics and wall mechanics of the restored aortic arch and its correlation with clinical outcomes. A three-dimensional aortic arch model was reconstructed from magnetic resonance images. The fluid–structure interaction (FSI) analysis was performed to characterize the hemodynamics and solid wall mechanics of the repaired aortic arch. Two graft shapes (i.e., a half-moon shape and a crescent one) were considered. Material choices of the aortic arch repair included three commonly used graft materials (i.e., polytetrafluoroethylene (PTFE) synthetic graft, CorMatrix extracellular matrix, and pulmonary homograft) as well as one native tissue serving as a control. The pathological hemodynamic parameters, in terms of the percentage area of low wall shear stress (WSS), high oscillatory shear index (OSI), and high relative residence time (RRT), were quantified to be associated with potential clinical outcomes. Results have shown that the peak von Mises stress for the aortic arch repaired by the crescent graft was 76% less than that of the half-moon graft. Flow disturbance and recirculation were also minimized with the crescent graft. Moreover, pathological hemodynamic parameters were significantly reduced with the crescent graft. The graft material mismatch with the surrounding tissue aggregated the stress concentration on the aortic wall, but had minimal impact on flow dynamics. The present work demonstrated the role and importance of the graft geometry and materials on hemodynamics and wall mechanics, which could guide optimal graft decisions towards better clinical outcomes.

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