HoloYolo: A proof-of-concept study for marker-less surgical navigation of spinal rod implants with augmented reality and on-device machine learning.

BACKGROUND Existing surgical navigation approaches of the rod bending procedure in spinal fusion rely on optical tracking systems that determine the location of placed pedicle screws using a hand-held marker. METHODS We propose a novel, marker-less surgical navigation proof-of-concept to bending rod implants. Our method combines augmented reality with on-device machine learning to generate and display a virtual template of the optimal rod shape without touching the instrumented anatomy. Performance was evaluated on lumbosacral spine phantoms against a pointer-based navigation benchmark approach and ground truth data obtained from Computed Tomography. RESULTS Our method achieved a mean error of 1.83±1.10 mm compared to 1.87±1.31 mm measured in the marker-based approach, while only requiring 21.33±8.80 s as opposed to 36.65±7.49 s attained by the pointer-based method. CONCLUSION Our results suggests that the combination of augmented reality and machine learning has the potential to replace conventional pointer-based navigation in the future. This article is protected by copyright. All rights reserved.