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BACKGROUND AND OBJECTIVES: One of the major challenges in training neurosurgical and orthopedic residents the technique for minimally invasive transforaminal lumbar interbody fusion (MIS-TLIF) is the lack of visualization of surgical landmarks (pedicle, pars, lamina). This is due to the limited access to the bony spine through a tubular retractor, in addition to a smaller working corridor or patient-specific factors such as bony overgrowth, disk space collapse, and listhesis. These factors increase the possibility for surgical error and prolonged surgery time. With augmented reality (AR), relevant surgical anatomy can be projected directly into the user's field of view through the microscope. The purpose of this study was to assess the utility, accuracy, efficiency, and precision of AR-guided MIS-TLIF and to determine its impact in spine surgery training. METHODS: At 2 centers, 12 neurosurgical residents performed a one-level MIS-TLIF on a high-fidelity lumbar spine simulation model with and without AR projection into the microscope. For the MIS-TLIF procedures with AR, surgical landmarks were highlighted in different colors on preoperative image data . These landmarks were visualized in the spinal navigation application on the navigation monitor and in the microscope to confirm the relevant anatomy. Postprocedural surveys (National Aeronautics and Space Administration Task Load Index) were given to the residents. RESULTS: Twelve residents were included in this trial. AR-guided procedures had a consistent impact on resident anatomical orientation and workload experience. Procedures performed without AR had a significantly higher mental demand ( P = .003 ) than with AR. Residents reported to a significantly higher rate that it was harder work for them to accomplish their level of performance without AR ( P = .019 ). CONCLUSION: AR can bring a meaningful value in MIS teaching and training to confirm relevant anatomy in situations where the surgeon will have less direct visual access. AR used in surgical simulation can also speed the learning curve.
Schmidt et al. (Mon,) studied this question.