Computational modeling of distal protection filters.

PURPOSE: To quantify the relationship between velocity and pressure gradient in a distal protection filter (DPF) and to determine the feasibility of modeling a DPF as a permeable surface using computational fluid dynamics (CFD).
METHODS: Four DPFs (Spider RX, FilterWire EZ, RX Accunet, and Emboshield) were deployed in a single tube representing the internal carotid artery (ICA) in an in vitro flow apparatus. Steady flow of a blood-like solution was circulated with a peristaltic pump and compliance chamber. The flow rate through each DPF was measured at physiological pressure gradients, and permeability was calculated using Darcy's equation. Two computational models representing the RX Accunet were created: an actual representation of the filter geometry and a circular permeable surface. The permeability of RX Accunet was assigned to the surface, and CFD simulations were conducted with both models using experimentally derived boundary conditions.
RESULTS: Spider RX had the largest permeability while RX Accunet was the least permeable filter. CFD modeling of RX Accunet and the permeable surface resulted in excellent agreement with the experimental measurements of velocity and pressure gradient. However, the permeable surface model did not accurately reproduce local flow patterns near the DPF deployment site.
CONCLUSION: CFD can be used to model DPFs, yielding global flow parameters measured with bench-top experiments. CFD models of the detailed DPF geometry could be used for "virtual testing" of device designs under simulated flow conditions, which would have potential benefits in decreasing the number of design iterations leading up to in vivo testing.