Clinical decisions regarding preventive treatment of unruptured aneurysms are not straightforward. Often, the question arises if risk of rupture outweighs risk of treatment. In these cases, rupture risk is currently assessed mainly based on size, location, and growth of the aneurysm. Although it has been shown that these parameters influence risk of rupture, they do not envelop all aspects of aneurysm behavior and growth. Local hemodynamics within the aneurysm itself are thought to play an important role in explaining when and why an aneurysm with a certain size, shape, or location will rupture and when it will not.¹ Particular hemodynamic parameters of interest include wall shear stress (WSS), its derivative oscillatory shear index (OSI), and intra-aneurysmal flow patterns — for example, vortex and inflow jet patterns and stability.

Computational fluid dynamics (CFD) is a broadly accepted approach for calculating these hemodynamic parameters. CFD is a computationally demanding method and utilizes numeric solutions to simulate fluid behavior and fluid-surface interaction within a particular geometry. Boundary conditions need to be applied to describe this geometry (fluid input velocity, for instance). The output of these computations includes WSS, pressure, and velocity, which can then be visualized using specialized software. With these visualizations, intra-aneurysmal flow patterns can be qualitatively assessed. Boundary conditions are traditionally based on typical flow rates in a healthy adult. This approach has been shown to be predictive, to an extent, of aneurysm rupture.^2-4 In recent years, a number of studies have been performed using patient-specific boundary conditions as opposed to generalized boundary conditions. It is theorized that incorporating patient-specific boundary conditions will contribute to accuracy of the CFD simulations and result in better predictions for aneurysm rupture. However, use of patient-specific boundary conditions has its own limitations, such as variability between physiologic waveforms.⁵ Up to now, the extent of this contribution to aneurysm rupture risk assessment has not been fully elucidated.

In our study, we focus on the difference in CFD results between the 2 methods.⁶ We performed CFD simulations twice on each aneurysm, once using generalized boundary conditions, and once using spatiotemporal patient-specific inflow boundary conditions. Patient-specific boundary conditions were acquired by 3T phase-contrast MRI (PC-MRI) velocity measurements of the artery proximal to the aneurysm. The resulting hemodynamic parameters were quantitatively and qualitatively assessed, and differences between the 2 methods were evaluated. For the different hemodynamic parameters, large differences could be observed between the 2 methods, particularly in WSS magnitudes. Qualitatively, in 21 of 36 aneurysms, differences were observed for at least 1 hemodynamic parameter. Also, in aneurysms with differences in vortex and inflow jet patterns, these patterns were noted to be more unstable when generalized boundary conditions were applied.

We showed that substantial differences are found between CFD simulations using generalized or patient-specific boundary conditions, and as such, this study emphasizes the need for using patient-specific inflow boundary conditions for CFD simulations in the search for hemodynamic rupture risk factors.

Our study suggests that patient-specific boundary conditions may have an important role to play in further refinement of CFD in cerebral aneurysm rupture risk assessment. Over the past decade an increasing number of studies has been published on this subject, further elucidating the complexity of intra-aneurysmal hemodynamics and the biologic pathways of its related pathophysiology. The increasing complexity of the CFD simulations performed in these studies, of which patient-specific measurements are a prudent example, is apparent. Also, a recent call has been made for efforts to standardize aneurysm modeling in order to combine datasets and increase collaboration of aneurysm researchers worldwide.⁷ This would increase statistical power, add to the validity of rupture risk assessment with CFD across different study populations, and allow for a pooling of knowledge and a faster evaluation and resolution of the inconsistencies in study findings that still exist across the literature. Ultimately, these developments will lead to better aneurysmal flow modeling, further refinement of patient-specific CFD simulations, and more accurate rupture risk assessment to aid clinicians in therapeutic decision making. 

References

1. Meng H, Tutino VM, Xiang J, et al. High WSS or low WSS? Complex interactions of hemodynamics with intracranial aneurysm initiation, growth, and rupture: toward a unifying hypothesis. AJNR Am J Neuroradiol 2014;35:1254–62, 10.3174/ajnr.A3558
2. Byrne G, Mut F, Cebral J. Quantifying the large-scale hemodynamics of intracranial aneurysms. AJNR Am J Neuroradiol 2014;35:333–38, 10.3174/ajnr.A3678
3. Cebral JR, Mut F, Weir J, et al. Association of hemodynamic characteristics and cerebral aneurysm rupture. AJNR Am J Neuroradiol 2011;32:264–70, 10.3174/ajnr.A2274
4. Jou LD, Lee DH, Morsi H, et al. Wall shear stress on ruptured and unruptured intracranial aneurysms at the internal carotid artery. AJNR Am J Neuroradiol 2008;29:1761–67, 10.3174/ajnr.A1180
5. Karmonik C. Toward improving fidelity of computational fluid dynamics simulations: boundary conditions matter. AJNR Am J Neuroradiol 2014;35:1549–50, 10.3174/ajnr.A3984
6. Jansen IG, Schneiders JJ, Potters WV, et al. Generalized versus patient-specific inflow boundary conditions in computational fluid dynamics simulations of cerebral aneurysmal hemodynamics. AJNR Am J Neuroradiol 2014;35:1543–48, 10.3174/ajnr.A3901
7. Xiang J, Tutino VM, Snyder KV, et al. CFD: computational fluid dynamics or confounding factor dissemination? The role of hemodynamics in intracranial aneurysm rupture risk assessment. AJNR Am J Neuroradiol 2014;35:1254–62, 10.3174/ajnr.A3710

 

Read this article at AJNR.org …