Objectives: In clinical practice, maximum diameter is used as a criterion to estimate aneurysm-rupture risk; however, it is only a general indicator and its value becomes difficult to estimate in the thoracic segment. Improved understanding of aortic aneurysm complexity and biomechanics is needed to achieve advancements in surgical repair techniques. The objective of this study was to determine the maximum wall stress by using imaging-derived data and a specific probabilistic design integrated into finite element (FE) analysis.
Methods: Computed tomography images of thoracic aortic aneurysms from our database were analysed and the main morphological features were identified by means of a specific automatic routine. Morphological data were used to develop an idealized finite element library of thoracic aortic arch models. Sensitivity analyses were performed by using the geometrical parameters as input variables for a statistical wall stress assessment. Numerical results were compared with those obtained from deterministic analysis on patient-specific three-dimensional reconstructions.
Results: The results showed that in small aneurysms, wall stress values similar to those of large aneurysms can be obtained if a significant eccentricity is achieved. In small aneurysms, the peak stress is primarily affected by the eccentricity of the bulge [correlation coefficient (CC) = 0.86], while for diameters in the range of 50-60 mm, the CC is 0.43 for the eccentricity and 0.72 for the maximum diameter.
Conclusions: The stress distribution in small aneurysms may contribute to the pathogenesis of aortic rupture and dissections. Our method can provide a novel and efficient procedure for generating computational models to estimate the wall stress in a comparative multivariate manner.
Keywords: Aneurysm; Biomechanics; Computer-based model; Imaging; Thoracic aorta.