ECCOMAS 2024

Fluid-Structure Interaction Analysis of Ascending Thoracic Aortic Aneurysms: a Comparison of Prestressing Algorithms

  • Mourato, André (NOVA SST, UNIDEMI)
  • Valente, Rodrigo (NOVA SST, UNIDEMI)
  • Brito, Moisés (NOVA SST, UNIDEMI)
  • Xavier, José (NOVA SST, UNIDEMI)
  • Avril, Stéphane (Mines de Saint-Étienne, Sainbiose U1059)
  • Tomás, António (Hospital Santa Marta)
  • Fragata, José (NOVA Medical School)

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Computational frameworks are pivotal in advancing the comprehension of ascending thoracic aortic aneurysms (ATAAs). However, obtaining the stress-free configuration, fundamental for accurately reproducing aortic wall mechanics, is challenging as the aorta is continuously loaded, making this configuration absent from in vivo data. To overcome this issue, two categories of prestressing algorithms have been proposed: Zero Pressure Geometry (ZPG) [1] and Prestress Tensor (PT) [2]. The ZPG uses an iterative approach to estimate the stress-free configuration, describing thoroughly the diastolic stress-strain state; however it is intricate to implement. The PT, a more straightforward approach, only determines the intramural stress state that balances the diastolic hemodynamic, not providing any information about the initial deformation. This study provides a comprehensive comparison of the influence of ZPG and PT algorithms on the numerical simulation of ATAA using a two-way FSI model implemented in SimVascular. A new approach using the PT algorithm with calibrated material properties (PTCalib) is also proposed. The computational domain and inlet boundary condition for FSI models were built using Computed Tomography Angiography (CTA) and Magnetic Resonance Imaging (MRI), respectively. Numerical results revealed comparable pressure fields throughout the cardiac cycle, across all approaches (relative error below 4%). The PTCalib model demonstrated closer agreement (relative error of 10%) with ZPG in the displacement fields. The PT methodology exhibited a stiffer mechanical response, leading to higher discrepancies (relative error of 20%). Both PT and the PTCalib required fewer iterations to achieve cycle-to-cycle convergence (2 and 3 iterations versus 5). The proposed PTCalib method shows improved agreement with ZPG requiring fewer iterations for cycle-to-cycle convergence.