Introduction: The growth of a cerebral aneurysm (CA) has been established as a key indicator of aneurysm rupture. It is therefore important to differentiate stable from growing aneurysms during pre-interventional planning. We compare three CA models corresponding to the consecutive stages of growth of an aneurysm in a single patient. The goal is to take a significant first step to elucidate the mechanisms underpinning CA growth and determine accurate criteria for predicting aneurysm growth.
Methods: Patient-specific images of growing cerebral aneurysm at three different growth stages, acquired over the period of 40 months, are segmented and reconstructed. Pulsatile flow in the resulting aneurysm models is simulated using an in-house developed massively parallel CFD code (HARVEY). The CFD simulations are also validated against in vitro experiments using particle image velocimetry (PIV) measurements.
Results: The detailed analysis of intrasaccular hemodynamics shows that growing regions of aneurysms are characterized by flow instabilities and complex vortical structures. These areas correspond to dramatically lower (< 0.5 Pa) time average wall shear stress (TAWSS) along with a significantly higher oscillatory shear index (OSI) (> 0.1). Furthermore, our statistical analysis show that an unstable, recirculating flow structure within the aneurysm sac created in the region adjacent to the aneurysm wall having low TAWSS and high OSI can be introduced as novel and accurate criteria to explain the hemodynamic conditions responsible for aneurysm growth and, more importantly, to predict the risk of growth.
Conclusions: Our results suggest that aneurysm growth is more likely in areas with unstable, recirculating blood flow. In these regions, endothelial cells lining the aneurysmal wall are exposed to minimum values of TAWSS and a maximum value of OSI. Our study provides a fundamental contribution to establish new criteria to predict aneurysm growth which can facilitate the differentiation of stable and growing aneurysms during pre-interventional planning.
Patient Care: In this work, three patient-specific cerebral aneurysm models corresponding to three stages of the aneurysm growth are compared. The models are reconstructed based on the data from a case-control study. Thus, the classification of aneurysm growth and/or stability areas is unique and accurate. Our study provides fundamental knowledge on hemodynamic conditions responsible for aneurysm progression. Our precise analysis establishes novel predictive criteria for aneurysm growth which can be used as potential tool to differentiate stable from growing aneurysms during pre-interventional planning.
Learning Objectives: By the conclusion of this session, participants should be able to: 1) Differentiate stable from growing aneurysms according to discrepancies observed in hemodynamic factors. 2) Discuss to implement our introduced criteria for accurate prediction of cerebral aneurysm growth in early stage of the disease. 3) Identify an effective treatment to prevent the growth of small cerebral aneurysms which are classified as ‘growing’ based on our defined criteria.
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