Real-time endovascular guidewire position simulation using shortest path algorithms.

Area of Science:

• Biomedical Engineering
• Medical Imaging
• Computational Anatomy

Background:

• Endovascular interventions are crucial for treating vascular diseases.
• Accurate guidewire placement is essential for delivering treatment devices effectively.
• Previous research suggests guidewire behavior can be modeled using energy minimization.

Purpose of the Study:

• To develop and validate a computational method for predicting guidewire position in complex vasculature.
• To utilize a k-level graph and shortest path algorithm for simulating guidewire paths.
• To support surgeon decision-making in guidewire selection for endovascular procedures.

Main Methods:

• A k-level graph representation was created using 3D vessel data.
• Guidewire properties were integrated as edge weights based on local bending energy.
• A shortest path algorithm determined the optimal guidewire trajectory.
• Simulations were performed on internal carotid artery phantoms with different guidewires.

Main Results:

• The simulation accurately predicted guidewire positions with an average RMS distance of 0.9 mm to 1.3 mm.
• The computational time for position determination was less than 2 seconds.
• The accuracy varied slightly based on guidewire material properties.

Conclusions:

• The proposed method provides reproducible and accurate guidewire position predictions.
• The technique operates within a clinically relevant timeframe (<2s).
• This approach has the potential to enhance the safety and efficacy of neurovascular interventions.