This study aimed to characterize the altered hemodynamics and wall mechanics in ascending thoracic aortic aneurysms (ATAA) by employing fully coupled two-way fluid–structure interaction (FSI) analyses. Our FSI models incorporated hyperelastic wall mechanical properties, prestress, and patient-specific inlet velocity profiles (IVP) extracted from 4D flow magnetic resonance imaging (MRI). By performing FSI analyses on 7 patient-specific ATAA models and 6 healthy aortas, the primary objective of the study was to compare hemodynamic and biomechanical features in ATAA versus healthy controls. A secondary objective was to examine the need for 4D flow MRI-derived IVP in FSI simulations by comparing results with those using two commonly adopted idealized IVPs: Flat-IVP and Para-IVP for selected cases. Our results show that, compared to the healthy aortas, the ATAA models exhibited highly disturbed blood flow in the ascending aorta. Consequently, maximum turbulent kinetic energy (TKE) at peak systole (155.0 ± 188.4 Pa) and maximum time-averaged wall shear stress (TAWSS) (8.6 ± 6.5 Pa) were significantly higher in the ATAA cohort, compared to 0.6 ± 0.5 Pa and 2.8 ± 0.7 Pa in the healthy aortas. Peak wall stress was also nearly doubled in the ATAA group (414 ± 108 kPa vs. 215 ± 31 kPa). Additionally, comparisons of simulation results across models with different IVPs underscore the importance of prescribing 3D-IVP at the inlet, especially for ATAA cases. Using idealized IVPs in two selected ATAA models (P1 and P7) substantially reduced the maximum TKE from 571 Pa to 0.01 Pa (Flat-IVP) and 0.02 Pa (Para-IVP) in P1 and from 73 Pa to 0.01 Pa (Flat-IVP) and 0.08 Pa (Para-IVP) in P7, while the maximum TAWSS in the ascending aorta decreased from 9.6 Pa to 0.7 Pa (Flat-IVP) and 0.9 Pa (Para-IVP) in P1, and from 3.6 Pa to 1.2 Pa and 0.9 Pa, respectively, in P7. Moreover, idealized IVPs also caused the peak wall stress to reduce by up to 11.5% in P1 with severe aortic valve stenosis, and by up to 2% in P7 with mild aortic regurgitation. These results highlight the importance of FSI simulations combined with 4D flow MRI in capturing realistic hemodynamic and biomechanical changes in aneurysmal aortas.

Objective: Computational modelling of ascending thoracic aortic aneurysms (ATAA) typically assumes zero-displacement at the model's inlet. In this study we incorporated different types of aortic root motion into fluid-structure interaction (FSI) models representing an ATAA and a healthy aorta to examine their impacts on wall stress and wall shear stress (WSS) predictions. Methods: Five types of boundary conditions were specified at the inlet of the solid domain: (a) zero-displacement constraints, (b) longitudinal displacement, (c) in-plane displacement, (d) combined longitudinal and in-plane displacement, and (e) rotation. The aortic walls were prestressed and modelled as anisotropic hyperelastic materials. A transitional turbulence model was employed to simulate the non-Newtonian blood flow, together with patient-specific boundary conditions. Results: Combined longitudinal and in-plane displacement at the aortic root increased regions with elevated maximum principal stress (MPS > 250 kPa) by 331% for the healthy aorta, and 57.1% for the ATAA model. Peak wall stress showed modest increases by 11.4% and 14% in the ATAA model and healthy aorta, respectively. Combined longitudinal and in-plane displacement increased the area of extremely high WSS regions (>20 Pa) by 20.5% in the ATAA model, primarily in the ascending aorta. For the healthy aorta, rotation had the most notable impact on WSS, reducing the area of elevated WSS regions (>7 Pa) by 18.8%. Conclusion: Our results highlight the importance of incorporating aortic root motion into FSI models for more accurate prediction of aortic wall stress and WSS. This would enhance patient-specific risk stratification for patients with ATAA.