On the use of clinical imaging in patient specific abdominal aortic aneurysm hemodynamics and wall mechanics
Peak wall stress is better marker for predicting the rupture of an Abdominal Aortic Aneurysm (AAA) than aneurysm maximum diameter. The standard procedure for calculating wall stress is through finite element analysis (FEA) on patient-specific AAA models generated from computer tomography (CT) images. While the image-based models used for these simulations are essentially in a pressurized state, the application of physiologic pressures to compute stresses and strains is debatable. Therefore, the derivation of a "simulation ready" computational geometry is of great importance to the research community. An experimental framework for the validation of the zero-pressure (ZP) computational algorithm is presented with the objective of proving that it is successful in reconstructing the zero-pressure geometry of blood vessels. The results show that the ZP algorithm is successful in reconstructing the unloaded geometry of an AAA silicone phantom of known material properties at various physiologically realistic intraluminal pressures. The other parameter that can affect peak wall stress is the constitutive equation used to define the wall tissue properties, which is currently a population-based model used for all patient-specific AAA geometries. A patient-specific material model would be an asset, especially if it is derived non-invasively. We present a method to obtain a patient-specific constitutive material model derived from the pulse wave velocity (PWV). A computer code was developed to segment the phase-contrast magnetic resonance (PC-MR) images and estimate PWV. To validate the feasibility of the method, three imaging follow-ups of an AAA patient were used and fluid-structure interactions (FSI) simulations were conducted with the population-based material model and the proposed patient-specific constitutive material model. The latter outperformed the population-based material model in predicting the individual's PWV.