Fast virtual stenting with deformable meshes: application to intracranial aneurysms

Area of Science:

• Biomedical Engineering
• Medical Device Technology
• Computational Fluid Dynamics

Background:

• Intracranial stents are increasingly utilized for treating intracranial aneurysms.
• Predicting stent behavior before intervention can optimize treatment selection.
• Current methods may lack speed or adaptability for complex anatomies.

Purpose of the Study:

• To propose a rapid virtual stenting technique for predicting deployed stent configurations.
• To enable virtual stent release in diverse intracranial vessel and aneurysm models.
• To support pre-procedural planning for intracranial aneurysm treatment.

Main Methods:

• Development of a virtual stenting technique employing constrained simplex deformable models.
• Integration of specific stent geometrical properties (cell design, strut dimensions, angles).
• Validation of the method on arbitrarily shaped vessel and aneurysm models.

Main Results:

• The technique successfully predicts stent configuration in virtual intracranial models.
• Favorable execution times, achieving results within approximately one minute.
• The method effectively incorporates detailed stent geometry into the simulation.

Conclusions:

• The proposed virtual stenting technique offers a fast and adaptable solution for pre-procedural planning.
• This computational approach can aid clinicians in choosing the most effective stent for individual patients.
• The method's ability to embed stent properties enhances the accuracy of virtual deployment prediction.