Computational modelling for the embolization of brain arteriovenous malformations

Area of Science:

• Biomedical Engineering
• Medical Imaging
• Computational Fluid Dynamics

Background:

• Arteriovenous malformations (AVMs) of the brain necessitate treatment via liquid embolic material injection to reduce blood flow.
• Pre-operative planning regarding embolic material type and injection site is critical for successful AVM treatment.

Purpose of the Study:

• To introduce a novel computational model for simulating the interaction between liquid embolic materials and blood within brain AVMs.
• To enhance pre-operative planning for AVM treatment by predicting embolic material propagation and solidification.

Main Methods:

• Developed a two-fluid model incorporating scalar transport to simulate embolic material propagation.
• Mimicked embolic material solidification by modeling an increase in viscosity.
• Validated the model using digital phantoms and a patient-derived AVM case.

Main Results:

• The simulation accurately reproduced intuitive two-fluid system behavior.
• Two distinct types of embolic material propagation within the AVM were successfully simulated.
• The model demonstrated the ability to differentiate between fistulous and plexiform compartments of the AVM.

Conclusions:

• The developed model provides a valuable tool for understanding and predicting liquid embolic material behavior in AVMs.
• Simulation results can aid in characterizing embolic material solidification within different AVM compartments.
• This approach has the potential to improve pre-operative planning and treatment outcomes for brain AVMs.