Improved Accuracy and Lowered Learning Curve of Ventricular Targeting Using Augmented Reality-Phantom and Cadaveric...

Area of Science:

• Neurosurgery
• Medical Technology
• Augmented Reality Applications

Background:

• Augmented reality (AR) shows promise in neurosurgery, but challenges remain in procedures like external ventricular drain (EVD) placement, which has high error rates.
• Current EVD placement techniques have targeting error rates between 10% and 40%.

Purpose of the Study:

• To evaluate the accuracy and efficacy of the Novarad VisAR augmented reality guidance system for external ventricular drain (EVD) placement.
• Assess the system's performance in both phantom and cadaveric models.

Main Methods:

• The VisAR system was registered with CT imaging of synthetic ventricular phantom and cadaver models.
• Measurements of root mean square (RMS) error, angular error (γ), and Euclidean distance were used to quantify accuracy.
• Multiple participants performed EVD placements using the VisAR system in various anatomical locations.

Main Results:

• Phantom models showed low mean errors (Euclidean distance 1.20 ± 0.98 mm, γ 1.25° ± 1.02°).
• In a phantom model, participants using VisAR achieved mean RMS of 3.9 ± 1.8 mm and γ of 3.95° ± 1.78°, with no significant difference based on experience.
• VisAR navigation in a cadaver model demonstrated significantly better accuracy (RMS 7.47 ± 0.94 mm, γ 7.12° ± 0.97°) compared to traditional anatomic landmarks.

Conclusions:

• The Novarad VisAR augmented reality system enables accurate EVD placement with a quick learning curve.
• This technology has the potential to enhance clinical neurosurgical treatment and improve patient outcomes.
• Future applications of VisAR may extend to other neurosurgical interventions.