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Background: The establishment of in vivo, patient-specific, and regionally resolved techniques to quantify aortic properties is key for improving risk assessment in clinical practice and scientific understanding of cardiovascular growth and remodeling. Many in vivo studies quantify vascular stiffness using Pulse Wave Velocity. This method provides an averaged measure of stiffness for the entire aorta, ignoring variations in wall stiffness and boundary conditions. Previous studies using Displacement Encoding with Stimulated Echoes Magnetic Resonance Imaging (DENSE-MRI) suggested that the infrarenal abdominal aorta (IAA) deforms heterogeneously throughout the cardiac cycle.

Method: Herein, we hypothesize that the aortic wall strain heterogeneity is driven in healthy aortas by adventitial tethering to perivascular tissues that can be modeled with elastic foundation boundary conditions (EFBC) using a collection of linear-springs with a circumferential distribution of stiffness. Nine healthy-human IAAs were modeled using patient-specific imaging and displacement fields from SSFP and DENSE MRI, followed by assessment of aortic wall properties and heterogeneous EFBC parameters using inverse Finite Element Method (FEM).

Results: In contrast to traction-free boundary condition, prescription of EFBC reduced the nodal displacement error by 60% and reproduced the DENSE-derived strain distribution. Estimated aortic stiffness was in agreement with previously reported experimental test data. The distribution of normalized EFBC stiffness was consistent among all patients and spatially correlated to standard peri-aortic anatomical features.

Conclusion: Results suggest that EFBCs can be generalized for human adults with normal anatomy. This approach is computationally inexpensive, making it ideal for large-population clinical research and incorporation into computational cardiovascular fluid-structure analyses.

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Mechanical Engineering | Nuclear Engineering

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VCU Graduate Research Posters

Elastic Foundations as Heterogeneous Adventitial Boundary Condition for the Assessment of Aortic Wall and Peri-Aortic Stiffness from Dense-MRI Data Using Inverse FEM Approach