Patient-Specific Finite Element Analysis of Ascending Thoracic Aortic Aneurysm

Background and aim of the study: Rupture/dissection of ascending thoracic aortic aneurysm (aTAA) is a cardiovascular emergency. Elective surgical repair is primarily based on maximum diameter, but complications have occurred under the size limits for surgical intervention. aTAA wall stress may be a better predictor of patient-specific rupture risk, but cannot be directly measured in vivo. The study aim was to develop an aTAA computational model associated with tricuspid aortic valve (TAV) to determine patient-specific wall stresses. Methods: A TAV-associated aTAA was excised intact during surgery. Zero-pressure geometry was generated from microcomputed tomography, and an opening angle was used to calculate residual stress. Material properties determined from stress-strain data were incorporated into an Ogden hyperelastic model. Wall stress distribution and magnitudes at systemic pressure were determined using finite element analyses (FEA) in LS-DYNA. Results: Regional material property differences were noted: the left aTAA region had a higher stiffness compared to the right, and anterior/posterior walls. During systole, the mean principal wall stresses were 172.0 kPa (circumferential) and 71.9 kPa (longitudinal), while peak wall stresses were 545.1 kPa (circumferential) and 430.1 kPa (longitudinal). Elevated wall stress pockets were seen in anatomic left and right aTAA regions. Conclusion: A validated computational approach was demonstrated to determine aTAA wall stresses in a patient-specific fashion, taking into account the required zero-stress geometry, wall thickness, material properties and residual stress. Regions of maximal wall stress may indicate the sites most prone to rupture. The creation of a patient-specific aTAA model based on a surgical specimen is necessary to serve as the 'gold standard' for comparing models based on in-vivo data alone. Validated data using the surgical specimen are essential for establishing wall stress and rupture-risk relationships.