Introduction: Aneurysm growth rate has been suggested as an indicator of eventual rupture, and identified as a potential risk factor for rupture. The ability to predict aneurysm growth requires a clear knowledge of the underlying mechanisms, which remain incompletely understood in part due to lack of patient-specific data describing the stages of aneurysm progression. The goal of this study is to take a significant first step to elucidate the mechanisms underpinning cerebral aneurysm (CA) growth.
Methods: Anatomical cerebral aneurysm geometries are segmented and reconstructed from patient-specific computed tomography angiography (CTA) datasets, at three different growth stages (namely the early, mid and late stages). Flow in the resulting aneurysm models are simulated using an in-house developed massively parallel CFD code (HARVEY). Clinically relevant hemodynamic parameters are then examined both qualitatively and quantitatively. The CFD simulations are also validated against in vitro experiments using particle image velocimetry (PIV) measurements. Furthermore, a part-comparison analysis was conducted to quantify morphological displacement between 3D models of CA growth stages. The calculated displacements between early and mid, and mid and late stages quantify variations among the geometries.
Results: Our detailed analysis of local hemodynamic factors including flow pattern, vorticity, wall shear stress (WSS), time average wall shear stress (TAWSS), oscillatory shear index(OSI) suggests that there is a strong correlation between areas of aneurysm growth and hemodynamic features, during the entire cardiac cycle. Growing regions of the aneurysm are characterized by flow-instabilities, flow impingement, and complex 3D vortical structures. Extremely low velocity occurs at the center of vortex where it correlates strongly with growing regions of growing CA. These areas correspond to dramatically lower values (< 0.4 Pa) of time average wall shear stress (TAWSS) and lower values (0.1 Pa) wall shear stress (WSS), significantly higher (> 0.3) oscillatory shear index (OSI), and positive vorticity. The Spearman’s rank correlation of local displacements with WSS, TAWSS, and OSI is found to have a two-tailed p = .0001.
Conclusions: Our study provides a fundamental contribution which details how disruption in hemodynamics is associated with aneurysm progression. This knowledge can be used as potential tool to differentiate stable from growing aneurysms during pre-interventional planning.
Patient Care: Cerebral aneurysm (CA) rupture can lead to subarachnoid hemorrhage, which has a mortality rate of about 50%. CA growth has been established as a key indicator of aneurysm rupture. It is therefore important to differentiate stable from growing aneurysms, especially while discussing prophylactic treatment for small size without any other concerning features.
The purpose of this study is to investigate the hemodynamic changes during the CA progression and elucidate the impact of hemodynamics on CA growth. We evaluated consecutive hemodynamic changes at three consecutive stages of CA growth. We chose patient-specific computed tomography angiography (CTA) datasets that were available for a 40-months period, corresponding to three different growth stages (namely the early, mid and late stages). The current work is the first, to the best of our knowledge, CFD-based investigation to elucidate the link between the local hemodynamics and regions of growth in the growing CA where a case-control study is applied to reconstruct the aneurysm growth models.
Learning Objectives: The significant implication of our findings is for investigations on aneurysm growth. Our results showed strong flow complexity and flow instability, during the entire cardiac cycle, at areas corresponding to aneurysm growth.