Newtonian viscosity model could overestimate wall shear stress in intracranial aneurysm domes and underestimate rupture risk.

OBJECTIVE

Computational fluid dynamics (CFD) simulations of intracranial aneurysm hemodynamics usually adopt the simplification of the Newtonian blood rheology model. A study was undertaken to examine whether such a model affects the predicted hemodynamics in realistic intracranial aneurysm geometries.

METHODS

Pulsatile CFD simulations were carried out using the Newtonian viscosity model and two non-Newtonian models (Casson and Herschel-Bulkley) in three typical internal carotid artery saccular aneurysms (A, sidewall, oblong-shaped with a daughter sac; B, sidewall, quasi-spherical; C, near-spherical bifurcation). For each aneurysm model the surface distributions of shear rate, blood viscosity and wall shear stress (WSS) predicted by the three rheology models were compared.

RESULTS

All three rheology models produced similar intra-aneurysmal flow patterns: aneurysm A had a slowly recirculating secondary vortex near the dome whereas aneurysms B and C contained only a large single vortex. All models predicted similar shear rate, blood viscosity and WSS in parent vessels of all aneurysms and in the sacs of B and C. However, large discrepancies in shear rate, viscosity and WSS among predictions by the various rheology models were found in the dome area of A where the flow was relatively stagnant. Here the Newtonian model predicted higher shear rate and WSS values and lower blood viscosity than the two non-Newtonian models.

CONCLUSIONS

The Newtonian fluid assumption can underestimate viscosity and overestimate shear rate and WSS in regions of stasis or slowly recirculating secondary vortices, typically found at the dome in elongated or complex-shaped saccular aneurysms as well as in aneurysms following endovascular treatment. Because low shear rates and low WSS in such flow conditions indicate a high propensity for thrombus formation and rupture, CFD based on the Newtonian assumption may underestimate the propensity of these events.