Experimental and Computational Analyses of Pathological Soft Tissues – Towards a Better Understanding of the Pathogenesis of AAA

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In this thesis a novel hypothesis on abdominal aortic aneurysm pathogenesis is proposed. It was derived by the systematic collection of histological, biaxial mechanical and structural data obtained by second harmonic generation imaging and its subsequent evaluation by constitutive modeling and finite element analysis.
The arterial wall can be seen as a fiber-reinforced composite material, consisting of collagen fibers embedded in an elastic matrix. During the pathogenesis of diseases such as abdominal aortic aneurysms (AAA), changes in the structural components have been shown to play a significant role. In this thesis a non-symmetric collagen fiber dispersion model was introduced, considering both in- and out-of-plane distributions separately using a bivariate von Mises distribution. Healthy aortas (AA) and AAA were tested utilizing biaxial tensile tests and second harmonic generation imaging. Significant differences in both mechanics and structure were found between AA and AAA samples after fitting to the proposed dispersion model.  The data set was then used to study its influence on the mechanical behavior. Three different fiber dispersions were studied using finite element analysis, revealing significant differences of stress distributions and magnitudes. Finally, histology was additionally investigated. It was possible to define three stages of disease progression based on mechanical data and find significant differences in structure and histology between stages. The study resulted in a novel AAA pathogenesis hypothesis derived directly from the comparison of the gained data.

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Justyna Anna Niestrawska

Themen in »Experimental and Computational Analyses of Pathological Soft Tissues – Towards a Better Understanding of the Pathogenesis of AAA«

arterial wall mechanics constitutive modeling layer-specific biaxial data healthy human aorta abdominal aortic aneurysm

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