Augmented reality-guided pedicle screw fixation: an experimental study.

Abstract

Study design: Cadaveric experimental study.

Purpose: To evaluate the feasibility and accuracy of pedicle screw placement using a custom-developed augmented reality-assisted pedicle screw fixation (ARPSF) system in a porcine spine model.

Overview of literature: Conventional pedicle screw placement techniques face limitations including potential inaccuracy, radiation exposure, and workflow disruption. Augmented reality technology can overlay virtual surgical planning directly onto the operative field while maintaining the surgeon's focus on the patient.

Methods: Five porcine cadaveric lumbar spines were used in this study. A custom-developed head-mounted display system with optical tracking projected three-dimensional reconstructed spine models and planned screw trajectories into the surgeon's field of view. A single experienced spine surgeon placed 50 pedicle screws (4.5 mm diameter). Registration was performed using a point-pair matching technique with fifteen anatomical landmarks. Accuracy was assessed via postoperative computed tomography scan, measuring entry point deviation, trajectory deviation, and angular difference, and evaluated using the Gertzbein-Robbins classification.

Results: Of the 50 pedicle screws placed, 47 (94%) achieved grade A accuracy with complete containment within the pedicle. The remaining three screws (6%) were classified as grade B, with minor breaches less than 2 mm. No unsafe placements (grades C-E) occurred. The mean entry point deviation was 0.55 mm (standard deviation [SD]=0.33 mm), and the mean deviation at the screw tip was 0.71 mm (SD=0.32 mm). The mean axial angular deviation was 2.04° (SD=0.58°). The average placement time was 2.2 minutes per screw.

Conclusions: The custom-developed ARPSF system demonstrated high accuracy for pedicle screw placement in a porcine model, achieving submillimeter precision and minimal angular deviation. This experimental study shows the potential of augmented reality technology to enhance spine instrumentation precision.