An Open-Source Minimal Cost Optical Neurosurgical Navigation System

Introduction: Neurosurgical procedures demand precision and accuracy to achieve optimal outcomes while minimizing patient risk. Optical navigation systems have emerged as essential tools to enhance the precision of these procedures. In the pursuit of affordability and accessibility, we present an innovative approach toward minimal-cost optical navigation for use in care deserts and novel environments for neurosurgical procedures.

Methods: By utilizing widely available hardware components, including a Raspberry Pi, two 12 megapixel IR cameras, retroreflective markers, and 3D printed tools, we have designed a navigation system that costs less than $100 and is adaptable to various neurosurgical environments. We developed a static testing surface to assess the base system accuracy to compare to minimum standards, and performed 100 accuracy measurements. We then constructed an anatomical phantom of the L2 and L3 vertebrae to assess qualitative tracking accuracy within an image-guided tracking environment. We compare the accuracy of our system to an OptiTrack motion capture navigation system that relies on the same tracking principles.

Results: With this basic system, we have achieved a base tool localization accuracy of 0.155 ± 0.36 mm in 3D position using a 1 meter bounding-box workspace. This compares favorably with the OptiTrack system, which has a calibrated accuracy of 0.10 ± 0.23 mm in 3D position.

Conclusion : In conclusion, we show a novel approach for low-cost optical navigation for neurosurgery, aiming to provide an affordable and accessible solution that can significantly enhance surgical precision. Our work not only contributes to the advancement of neurosurgical techniques but also emphasizes the importance of cost-effective solutions in expanding the reach of cutting-edge medical technology. Future steps will involve evaluating the navigation system in a phantom study for optically-navigated minimally invasive pedicle screw placement to assess the effects of registration on system accuracy.