Computational modeling of platelets and thrombosis in cerebral aneurysm treatment

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Here we seek to improve the accuracy of hemodynamic modeling of cerebral aneurysms. This goal of this project is to predict the outcome of cerebral aneurysm treatment. This is significant due to the prevalence of cerebral aneurysms, their dismal prognosis when ruptured, and treatment failure rates (resulting in aneurysm recurrence and risk of either brain hemorrhage or need for retreatment) of up to 40%. Hemodynamic forces are thought to influence aneurysm treatment outcomes, and can be simulated using computational fluid dynamics (CFD) methods, but such studies have not been widely accepted due to conflicting results. Traditional CFD analysis (termed “Eulerian” metrics) only studies the effect of blood flow on the vascular walls, largely ignoring circulating blood products such as platelets that initiate intra-aneurysmal thrombosis (termed “Lagrangian” metrics), which have a critical role in treatment outcome. Better prediction through a holistic approach combining both types of analyses could identify patients at risk for treatment failure, influencing pre-surgical decision-making. This project builds on our ongoing NIH-funded expertise (via a renewal of R01NS105692) in the CFD modeling of cerebral aneurysms before and after treatment. We have developed an innovative method of incorporating novel Lagrangian metrics, such as residence time and shear history, into CFD simulations in with existing Eulerian hemodynamic metrics, to create a holistic approach to modeling the effects of aneurysm treatment. Feasibility studies have characterized the post-treatment hemodynamic environment with special attention to platelet-representative particles that experience prolonged intra-aneurysmal residence time and low cumulative shear history within treated aneurysms. Previous in vitro studies of platelets in similar conditions demonstrate thrombosis in such environments, which would be advantageous after aneurysm treatment to develop a stable thrombus leading to aneurysm healing. First, we will perform CFD simulations before and after treatment on a cohort of cerebral aneurysms whose treatment outcome (success or failure) is known. We will include both Eulerian and Lagrangian metrics to determine associations with treatment outcome. Second, we will use an established animal model of cerebral aneurysms, treated with commercially-available endovascular devices. We will perform CFD simulations a similar holistic model as the human aneurysm cohort, and investigate the relationship between Lagrangian metrics and treatment-related thrombosis on histological analysis. The final result will be an optimized CFD methodology and set of Eulerian and Lagrangian variables predictive of outcome after cerebral aneurysm embolization.