Investigation of a Robotic-Assisted Monocular Optical Tracking System for Navigated Spine Surgery using Modular Patient Reference Trackers

Abstract

On average, 15–18% of spinal implants are malpositioned or breach the cortical bone, leading to complications, revision surgeries, and increased healthcare costs. To improve surgical accuracy and patient outcomes, image-guided navigation systems have been developed to localize surgical instruments and critical anatomy while assisting with implant placement. By providing real-time visualization relative to pre-operative medical images, these systems reduce the need for repeated intra-operative imaging, improving accuracy while decreasing radiation exposure and the likelihood of revision procedures. Despite these advantages, current optical navigation systems remain susceptible to line-of-sight interruptions, which can result in tracking loss and disrupt the surgical workflow. To address these limitations, the objectives of this research were to: (1) compare the tracking performance of stereo and monocular optical tracking systems for spinal navigation, (2) develop and validate a modular patient reference tracker mounting system capable of supporting automatic registration using overhead tracking, and (3) integrate the proposed registration workflow into an augmented reality navigation framework. The first objective was achieved through a comparative evaluation of stereo and monocular tracking systems while tracking an identical rigid body. Both systems demonstrated tracking accuracy within clinically acceptable limits, indicating that the smaller-footprint monocular camera represents a viable alternative to conventional stereo tracking systems. Given the high level of agreement observed between the two cameras, selection may instead be based on operating room constraints and surgeon workflow requirements rather than tracking performance alone. The second objective demonstrated that the modular mounting system provided repeatable positioning of the patient reference tracker with minimal localization error across mounting positions. Although tracking accuracy degraded slightly as the camera offset increased, the observed errors remained within clinically acceptable limits. Furthermore, the mounting system maintained consistent registration when a single point-to-point registration was used across multiple patient reference tracker positions, demonstrating that repositioning did not necessitate repeated manual registration. While the proposed CT-based automatic registration workflow did not achieve clinically acceptable target registration error, it demonstrated sub-millimeter localization accuracy of the patient reference tracker and identified the primary sources of error, suggesting that the methodology could be further improved through secondary registration refinement and improvements to the experimental hardware. The final objective resulted in the development of an open-source augmented reality framework within 3D Slicer that integrates camera calibration, optical tracking, and CT-based registration for real-time anatomical visualization. Using user-defined camera intrinsics, the framework establishes the spatial relationship between the surgical exoscope and the optical tracking system, enabling tracked surgical instruments, patient reference trackers, and pre-operative anatomical information to be projected directly onto the exoscope image. By leveraging the proposed automatic registration workflow, anatomical landmarks identified on the pre-operative CT can be visualized within the surgical field, providing intuitive guidance for tasks such as incision planning, anatomical localization, and spinal implant positioning.