A Computational Framework for Pre-Interventional Planning of Peripheral Arteriovenous Malformations

Area of Science:

• Biomedical Engineering
• Computational Fluid Dynamics
• Vascular Surgery

Background:

• Peripheral arteriovenous malformations (pAVMs) are complex congenital vascular lesions.
• Current embolization treatments for pAVMs have uncertain outcomes.
• Advanced computational tools are needed to improve treatment planning for pAVMs.

Purpose of the Study:

• To develop a computational framework for simulating pAVM hemodynamics.
• To aid clinical decision-making in pAVM treatment using patient-specific data.
• To model the effects of embolization on pAVM nidus hemodynamics.

Main Methods:

• A patient-specific computational model of pAVM hemodynamics was created.
• A porous medium approach simulated embolization by altering nidus permeability.
• Model results were validated against digital subtraction angiography (DSA) and phantom data.

Main Results:

• The model accurately simulated pre-, intra-, and post-embolization hemodynamics.
• Nidus permeability changes effectively represented embolization, reducing nidus flow from 71% to 1%.
• Simulated flow rates showed good agreement with clinical DSA data.

Conclusions:

• Computational simulation using a porous medium can predict embolization effects on pAVMs.
• The framework provides a basis for computational treatment planning in pAVM embolization.
• This approach can enhance clinical decision-making for pAVM interventions.