AuthorsO. M. Khan
TitleNumerical characterization of high-frequency flow fluctuations in intracranial aneurysms
AfilliationScientific Computing
Project(s)Center for Biomedical Computing (SFF)
Publication TypePhD Thesis
Year of Publication2017
Degree awarding institutionUniversity of Toronto
PublisherUniversity of Toronto
Place PublishedUniversity of Toronto

Rupture of intracranial aneurysms (IAs), saccular outpouching of blood vessels, can lead to death or permanent disability in majority of the patients. Hemodynamic forces are thought to play a key role in the process, but, currently, can only be estimated through computational fluid dynamic (CFD) simulations of patients' cerebrovasculature. IA flows have conventionally been considered laminar and stable; however, recent studies highlighted the presence of high-frequency flow fluctuations consistent with clinical evidence Ñ a discrepancy attributed to conventional use of low-order CFD. The goal of this doctoral thesis was to investigate the nature and characteristic of these flow fluctuations, and its prevalence in IAs. Towards that goal, I performed the first mesh, time, and solver refinement study to investigate the isolated impact of each modelling choice. With 320-fold increase in mesh size, 25-fold increase in time-steps, and considering both a low-order solver and a high-order solver, I found that solver choice had a relatively higher impact on hemodynamics compared to other modelling assumptions. Finding of these flow fluctuations also meant rethinking the conventional assumption of Newtonian rheology for blood. As a first step, I performed a controlled numerical experiment on an idealized stenotic vessel for Re=500-1000, which suggested that shear-thinning non-Newtonian rheology caused a delay of 10% in the critical Reynolds number. I later investigated the practical impact of these findings on IA hemodynamics. These findings suggested that assumption of shear-thinning rheology had a negligible impact, particularly when compared to effects of low-order solvers.

Due to limitations of current hemodynamic metrics in quantifying flow fluctuations, I proposed a frequency-based hemodynamic index. Using this tool and aforementioned findings, I performed high-resolution simulations of 19 IAs to characterize and investigate the prevalence of flow fluctuations. Through proper orthogonal decomposition, I showed that, depending on the patient, a wide range of spectra exists, some with high concentration of energy in higher modes. I also found that approximately half of IA flows are "turbulent-like" and 30% can have cycle-to-cycle fluctuations. Further investigation is needed to establish the clinical impact of these flow fluctuations in IA rupture risk assessment.