Hemodynamic predictors of rupture in abdominal aortic aneurysms: a case series using computational fluid dynamics.

BACKGROUND

Abdominal aortic aneurysm (AAA) rupture is a life-threatening event traditionally predicted by aneurysm diameter. However, many clinical observations have revealed that rupture can occur even in small aneurysms, suggesting the influence of additional biomechanical factors such as hemodynamics. The aim of this case series was to perform computational fluid dynamics (CFD) analyses based on CT scans of patients with confirmed abdominal aortic aneurysm rupture and to evaluate correlations between rupture sites and hemodynamic factors derived from simulations.

METHODS

This study analyzed four patients with confirmed ruptured fusiform infrarenal AAAs. Three-dimensional patient-specific models were reconstructed from CT scans and simulated using SimVascular, an open-source CFD platform. Simulations incorporated pulsatile inlet flow and three-element Windkessel outlet boundary conditions to calculate the following key hemodynamic parameters: time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), endothelial cell activation potential (ECAP), and relative residence time (RRT). Rupture sites were compared with spatial distributions of these parameters. Intraluminal thrombus (ILT) regions were estimated by overlaying flow lumen boundaries with the aneurysmal wall.

RESULTS

Rupture consistently occurred in regions of low TAWSS, high OSI, elevated ECAP, and high RRT. These sites also showed flow stagnation during systole and recirculation during diastole. ECAP demonstrated the highest spatial specificity for rupture. Overlay models revealed that ILT-prone zones corresponded with high-RRT regions and often co-localized with rupture sites.

CONCLUSIONS

CFD-derived hemodynamic parameters, particularly ECAP was spatially correlated with AAA rupture sites. These findings support the utility of CFD in identifying rupture-prone regions and suggest its potential as a supplementary tool for risk stratification beyond diameter-based criteria.