The current clinical management of abdominal aortic aneurysm (AAA) disease is based on measuring the aneurysm maximum diameter to decide when timely intervention can be recommended to a patient. However, other parameters may also play a role in causing or predisposing the AAA to either an early or delayed rupture relative to its size. Therefore, patient-specific assessment of rupture risk based on physical principles such as individualized biomechanics can be conducive to the development of a vascular tool with translational potential. To that end, the present doctoral research materialized into a framework for image based patient-specific vascular biomechanics assessment.
A robust generalized approach is described herein for image-based volume mesh generation of complex multidomain bifurcated vascular trees with the capability of incorporating regionally varying wall thickness. The developed framework is assessed for geometrical accuracy, mesh quality, and optimal computational performance. The relative influence of the shape and the constitutive wall material property on the AAA wall mechanics was explored. This study resulted in statistically insignificant differences in peak wall stress among 28 AAA geometries of similar maximum diameter (in the 50 – 55 mm range) when modeled with five different hyperelastic isotropic constitutive equations. Relative influence of regionally varying vs. uniform wall thickness distribution on the AAA wall mechanics was also assessed to find statistically significant differences in spatial maxima of wall stresses, strains, and strain energy densities among the same 28 AAA geometries modeled with patient-specific non-uniform wall thickness and two uniform wall thickness assumptions. Finally, the feasibility of estimating in vivo wall strains from individual clinical images was evaluated. Such study resulted in a framework for in vivo 3D strain distributions based on ECG gated, unenhanced, dynamic magnetic resonance images acquired for 20 phases in the cardiac cycle. Future efforts should be focused on further development of the framework for in vivo estimation of regionally varying hyperelastic, anisotropic constitutive material models with active mechanics components and the integration of such framework with an open source finite element solver with the goal of increasing the translational potential of these tools for individualized prediction of AAA rupture risk in the clinic.
| Identifer | oai:union.ndltd.org:cmu.edu/oai:repository.cmu.edu:dissertations-1202 |
| Date | 01 August 2012 |
| Creators | Raut, Samarth Shankar |
| Publisher | Research Showcase @ CMU |
| Source Sets | Carnegie Mellon University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Dissertations |
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