Impact of Patient-Specific Material Properties on Aneurysm Wall Stress: Finite Element Study.

BACKGROUND

Finite element analysis (FEA) can be used to determine ascending thoracic aortic aneurysm (aTAA) wall stress as a potential biomechanical predictor of dissection. FEA is dependent upon zero-pressure three-dimensional geometry, patient-specific material properties, wall thickness, and hemodynamic loading conditions. Unfortunately, determining material properties on unoperated patients using non-invasive means is challenging; and we have previously demonstrated significant material property differences among aTAA patients. Our study objective was to determine the impact of patient-specific material properties on aTAA wall stress. Using FEA, we investigated if patient-specific wall stress could be reasonably predicted using population-averaged material properties, which would greatly simplify dissection prediction.

METHODS

ATAA patients (n=15) with both computed tomography (CT) imaging and surgical aTAA specimens were recruited. Patient-specific aTAA CT geometries were meshed and pre-stress geometries determined as previously described. Patient-specific material properties were derived from biaxial stretch testing of aTAA tissue and incorporated into a fiber-enforced hyper-elastic model, while group-averaged material properties were estimated using mean values of each parameter. Population-averaged material properties were also calculated from literature and studied. Wall stress distribution and its magnitude were determined using LS-DYNA FEA software. Peak and averaged stresses and stress distributions were compared between patient-specific and both group- and population-averaged material property models.

RESULTS

Patient-specific material properties had minimal influence on either peak or averaged wall stress compared to use of group- or population-averaged material properties. Stress distribution was also nearly superimposed among models with patient-specific vs. group- or population-averaged material properties and provided similar prediction of sites most prone to rupture.

CONCLUSIONS

FEA using population-averaged material properties likely provides reliable stress prediction to indicate sites most prone to rupture. Population-averaged material properties may be reliably used in computational models to assess wall stress and significantly simplify risk prediction of aTAA dissection.