Virtual flow diverter deployment and embedding for hemodynamic simulations

Area of Science:

• Biomedical Engineering
• Medical Imaging
• Computational Fluid Dynamics

Background:

• Flow-diverter stents are crucial for treating intracranial aneurysms, but variable success rates necessitate improved in-situ study methods.
• Existing virtual stenting algorithms lack robustness, often relying on uncertain parameters and lacking comprehensive validation.

Purpose of the Study:

• To develop and validate a reliable virtual stenting algorithm for simulating flow-diverter stent deployment.
• To improve the accuracy of computational fluid dynamics (CFD) simulations for intracranial aneurysm treatment.

Main Methods:

• A novel deployment algorithm integrating vessel geometry and previous advancements was developed.
• The algorithm was rigorously validated against literature data, in-vitro experiments, and patient-specific data.
• Techniques for embedding deployed virtual stents into computational meshes using open-source tools were established.

Main Results:

• The developed algorithm achieved a mean angular error below 5° when validated against patient data.
• The method provides a robust simulation of flow-diverter stent deployment and its hemodynamic impact.
• Successful integration of deployed virtual stents into computational meshes was demonstrated.

Conclusions:

• The validated virtual stenting algorithm offers a reliable tool for in-situ hemodynamic studies of flow-diverter stents.
• This advancement supports more accurate research into intracranial aneurysm treatment and device performance.
• The integration with open-source meshing tools facilitates broader application in computational modeling.