|Two-dimensional (plane strain) dynamic immersed boundary FSI simulation of aortic dissection induced by fluid loading using a layer-specific, fiber-reinforced hyperelastic model of the human thoracic aorta with residual stresses: (a) initial configuration; (b) aortic dissection induced by supra-physiological pressure load (~750 mmHg).||
During aortic dissection an intimal tear in the aortic wall propagates into the media to form a false lumen within the vessel wall, which can quickly lead to death. Surgical treatment for aortic dissection consists of either replacement of a portion of the aorta or endovascular stent implantation to cover the affected segment. Both approaches carry significant risks, and determining the optimal choice and timing of an intervention is challenging.
While aortic dissections can be induced in animal models such models do not replicate the clinical pathology. Consequently, modeling studies of aortic dissection must use physical and/or computational models. Existing computational models of aortic dissection use conventional CFD approaches (vessel wall and flap are treated as rigid). Although CFD models are able to predict wall shear stress distributions, they are unable to account for the interactions between the blood and the vascular tissues or for the effects of such interactions on the dynamics of the dissected aorta.
This NIH project is in cooperation with the School of Medicine at New York University, USA. It develops fluid-structure interaction models of both the dissected and dissecting aorta that overcome the limitations of CFD models. Realistic patient anatomical geometries are derived from computed tomography and/or magnetic resonance imaging studies. To characterize the mechanical response and the damage and failure characteristics of human aortic tissues, experimental tests are performed using tissue samples collected from both normal and diseased human aortas. Experimental data are then used to develop healthy and disease-specific constitutive models that include innovative models of tissue damage and failure. The impact of these characterizations is not limited to aortic dissection; this work has potential applications to a range of arterial pathologies, including aneurysmal rupture.
These predictive models are used to perform patient-specific simulations that ultimately aid the clinical decision making. Finally, these models are used to study the surgical and medical management of patients who require or who have undergone partial repair of a Stanford Type A dissection.
Funding: National Institutes of Health (NIH)