R30 - Patient-specific Turbulent Kinetic Energy and Vortical Structure Hemodynamics Modeling of Saccular and Fusiform Abdominal Aortic Aneurysm Growth

Introduction: : Cardiovascular disease (CVD) remains a primary global health challenge, with projections estimating up to 23.6 million deaths annually by 2030. Abdominal aortic aneurysm (AAA), an exemplary manifestation of CVD, is characterized by a localized dilation of the abdominal aorta (≥ 3 cm in diameter), typically occurring between the renal arteries and the aorto-iliac bifurcation. AAAs exhibit unpredictable growth and pose a significant risk of rupture, which is associated with mortality rates exceeding 80%. Left untreated, they may continue to expand until rupture. Clinical guidelines recommend surgical or endovascular intervention when the maximum diameter reaches 5.5 cm in men or 5.0–5.4 cm in women, or the growth rate is 1 cm/year. Hemodynamic forces, particularly wall shear stress, play an important role in vascular remodeling and are hypothesized to contribute to AAA pathogenesis. However, their influence in AAA progression is complex, especially due to the presence of intraluminal thrombus (ILT). ILT may disrupt direct blood flow–wall interactions, altering local biomechanical conditions and complicating the relationship between hemodynamics and aneurysm wall adaptation. To investigate this interplay, we developed high-fidelity computational fluid dynamics (CFD) models to quantify turbulent kinetic energy (TKE) and vortex structures in AAAs under surveillance. These models, informed by serial imaging data, aim to serve as predictive tools for characterizing local hemodynamic environments conducive to ILT development. Our findings have the potential to inform risk stratification, improve clinical decision-making, and guide the development of patient-specific intervention strategies in AAA management.

Materials and

Methods: : With Institutional Review Board (IRB) approval from Allegheny General Hospital, Northwestern Memorial Hospital, and Seoul National University Hospital, we retrospectively acquired contrast-enhanced computed tomography (CT) images for 10 AAA patients with serial follow-ups. Lumen segmentation was performed using MIMICS (Materialise NV, Belgium), and surface meshes were imported into SimVascular (https://simvascular.github.io/) for assigning boundary conditions and material properties. Volume meshes were generated using TetGen (http://tetgen.org/), yielding unstructured tetrahedral meshes with an average of 7 ± 1.5 million elements, as guided by prior mesh sensitivity analyses (Updegrove et al., 2017).
A Womersley velocity profile with 10 Fourier modes was prescribed at the suprarenal inlet, while patient-specific outlet conditions were modeled using a 3-element Windkessel (RCR) framework, comprising proximal resistance (Rp), capacitance (C), and distal resistance (Rd). Blood flow was assumed incompressible and Newtonian, with a viscosity of 0.004 Pa·s and density of 1050 kg/m³ (Arzani et al., 2018).
The incompressible Navier–Stokes and continuity equations (Eqs. (1) and (2)) were solved using a stabilized finite-element method in SimVascular:
∇∙v=0 (1)
ρ(∂v/∂t+v.∇v)=∇∙σ+f (2)
Each cardiac cycle was discretized into time steps in the range 0.000769–0.0009 s, with results stored at every step. Simulations were executed for 6–10 cardiac cycles, with the final two cycles used for post-processing. All computations were conducted using ~360 cores on the UTSA ARC cluster and the Texas Advanced Computing Center. We thereby present the results for two exemplary AAA patients (with 5 follow-ups each), representative of a fusiform and a saccular aneurysm.

Results, Conclusions, and Discussions:: TKE was computed using the fluctuating velocity components, defined as the difference between instantaneous velocities and the mean velocity field. Mathematically, this is represented by Eq. (3),
KE= 1/2* ρ*(u ̃^2+v ̃^2+w ̃^2 ) (3)
where ρ is the blood density and (u ̃, v ̃, w ̃) represent fluctuating velocities in the axial, normal, and transverse directions, respectively. Across all follow-ups, mild turbulence was identified, with the fusiform AAA experiencing a maximum TKE of 7,223 g·cm⁻¹·s⁻², while the saccular AAA exhibited high localized TKE exceeding 8,000 g·cm⁻¹·s⁻² at the proximal end of the sac. Notably, a large portion of both aneurysm sacs experienced TKE levels of approximately 4,000 g·cm⁻¹·s⁻², a threshold associated with hemolysis, and localized regions exhibited TKE greater than 6,000 g·cm⁻¹·s⁻², which suggests possible red blood cell damage.

At peak systolic flow, the maximum TKE in the fusiform AAA occurred in the non-diseased vessel segments, whereas in the saccular AAA it was mostly located near the proximal end of the sac. Over five follow-up intervals, a decreasing trend in TKE was observed concomitant with increasing aneurysm diameter and ILT volume. These patterns suggest a transitional or marginally turbulent flow regime within the AAA sac, with the saccular AAA experiencing initially higher turbulence. Moreover, an inverse relationship was found between TKE and aneurysm diameter and ILT volume over time. Despite lower initial turbulence, the fusiform AAA showed a higher overall growth rate in both diameter and ILT volume, supporting the hypothesis that moderate turbulence may attenuate thrombus accumulation.

Our findings further indicate that transient turbulence, generated by downstream-advected vortex rings, can potentially limit ILT growth. In the saccular AAA, elevated proximal TKE and a delayed secondary vortex-2 bursting event appeared to reduce ILT formation, in contrast to the fusiform AAA where the vortex bursts occurred in the middle of the sac and TKE remained below critical thresholds.

We conclude that elevated TKE near the proximal sac and delayed vortex dynamics in saccular AAAs likely contribute to slower ILT growth compared to fusiform AAAs, supporting the concept that mild-to-moderate turbulence may mitigate ILT deposition and influence aneurysm growth rate.

Acknowledgements and/or References (Optional):: This study was supported in part by NIH award R01HL159300.