Inverse finite element identification of murine aortic material properties: in vivo and ex vivo comparisons.

Abstract

Inverse finite element (FE) models can non-invasively estimate aortic mechanical properties from in vivo imaging. However, few studies have compared model predictions with direct mechanical characterization in the same samples. To address this, we used a mouse model of thoracic aneurysm to develop (from in vivo ultrasound imaging) and validate (from ex vivo biomechanical testing) an inverse FE approach to estimate material properties of the ascending thoracic aorta. The proposed inverse FE model was constructed based on a combination of image-based tracking of tissue deformation in 4D ultrasound images (4DUS; volumetric images over time) and non-invasive hemodynamic measures (pulsed wave Doppler velocity and tail-cuff blood pressure). Following an optimization scheme to estimate the biaxial pre-stretches that best represent the in vivo radii obtained from 4DUS images, material properties were identified, and aortic stiffness was calculated for each mouse included in the study (n = 8 total). Inverse FE predictions were compared with paired ex vivo material characterization results for each ascending aortic sample. Multiple assumptions related to boundary conditions and unloaded tissue geometry were required to constrain the inverse identification procedure; sensitivity analysis was performed for each simplifying assumption and uncertainty in the estimated axial pre-stretch was identified as a primary contributor to the observed discrepancies between in vivo and ex vivo material property estimates. Findings from two material models (neo-Hookean and four-fiber family) were compared and all data has been provided as a benchmark for future inverse FE studies.