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Computer modeling of deployment and mechanical expansion of neurovascular flow diverter in patient-specific intracranial aneurysms
Authors:Ding Ma  Gary F Dargush  Sabareesh K Natarajan  Elad I Levy  Adnan H Siddiqui  Hui Meng
Institution:Toshiba Stroke Research Center, University at Buffalo, State University of New York, Buffalo, NY 14214, USA; Department of Mechanical and Aerospace Engineering, University at Buffalo, State University of New York, Buffalo, NY 14214, USA.
Abstract:Flow diverter (FD) is an emerging neurovascular device based on self-expandable braided stent for treating intracranial aneurysms. Variability in FD outcome has underscored a need for investigating the hemodynamic effect of fully deployed FD in patient-specific aneurysms. Image-based computational fluid dynamics, which can provide important hemodynamic insight, requires accurate representation of FD in deployed states. We developed a finite element analysis (FEA) based workflow for simulating mechanical deployment of FD in patient-specific aneurysms. We constructed FD models of interlaced wires emulating the Pipeline Embolization Device, using 3D finite beam elements to account for interactions between stent strands, and between the stent and other components. The FEA analysis encompasses all steps that affect the final deployed configuration including stent crimping, delivery and expansion. Besides the stent, modeling also includes key components of the FD delivery system such as microcatheter, pusher, and distal coil. Coordinated maneuver of these components allowed the workflow to mimic clinical operation of FD deployment and to explore clinical strategies. The workflow was applied to two patient-specific aneurysms. Parametric study indicated consistency of the deployment result against different friction conditions, but excessive intra-stent friction should be avoided. This study demonstrates for the first time mechanical modeling of braided FD stent deployment in cerebral vasculature to produce realistic deployed configuration, thus paving the way for accurate CFD analysis of flow diverters for reliable prediction and optimization of treatment outcome.
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