A recent focus in the biomedical engineering field has been on developing models of in-vivo tissue responses to help better predict aortic wall mechanics, through numerical methods and simulation, towards improved prediction of aortic wall rupture. The structural influence of both collagen and elastin, integral components within the aortic wall, has been studied and is largely understood, but the contribution of glycosaminoglycans (GAGs) is still unclear. While it has been suggested that the swelling properties of GAGs may participate in the regulation of residual stresses in the aortic wall, whether or not GAGs affect the mechanical properties of the aortic wall is completely unknown. The present study was divided into two experiments: Experiment 1 (n=9) utilized planar biaxial testing to characterize arterial wall mechanics in native porcine aortas. The results of Experiment 1 highlight: (i) decreased tissue thickness moving distally, away from the heart;
(ii) increased stiffness from the ascending aorta to the thoracic descending aorta; (iii) no difference in morphometry or stress-strain behaviour between samples excised from the anterior, posterior, and/or left and right lateral walls. Experiment 2 (n=8) employed identical testing parameters to characterize partial and fully enzymatically GAG-depleted tissue, to determine the influence of this macromolecule on aortic wall mechanics. The results of Experiment 2 highlight: (i) GAG content in the porcine aorta does not affect tissue mechanical properties measured from biaxial testing; (ii) enzymatic removal of GAGs does not influence morphometric parameters, including thickness and area. These findings will contribute to improving the fundamental understanding of aortic tissue mechanics by helping to determine the relationship between spatial dependency and mechanical response, and the relationship between individual aortic wall constituents and the overall mechanical behaviour of the aorta.
Identifer | oai:union.ndltd.org:uottawa.ca/oai:ruor.uottawa.ca:10393/42904 |
Date | 12 November 2021 |
Creators | Zunder, Dayna |
Contributors | Labrosse, Michel |
Publisher | Université d'Ottawa / University of Ottawa |
Source Sets | Université d’Ottawa |
Language | English |
Detected Language | English |
Type | Thesis |
Format | application/pdf |
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