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Background  The ExcelsiusGPS® (Globus Medical, Inc., Audubon, PA) is a next-generation spine surgery robotic system recently approved for use in the United States. The objective of the current study is to assess pedicle screw accuracy and clinical outcomes among two of the first operative cases utilizing the ExcelsiusGPS® robotic system and describe a novel metric to quantify screw deviation.    Methods  Two patients who underwent lumbar fusion at a single institution with the ExcelsiusGPS® surgical robot were included. Pre-operative trajectory planning was performed from an intra-operative CT scan using the O-arm (Medtronic, Inc., Minneapolis, MN). After robotic-assisted screw implantation, a post-operative CT scan was obtained to confirm ideal screw placement and accuracy with the planned trajectory. A novel pedicle screw accuracy algorithm was devised to measure screw tip/tail deviation distance and angular offset on axial and sagittal planes. Screw accuracy was concurrently determined by a blinded neuroradiologist using the traditional Gertzbein-Robbins method. Clinical variables such as symptomatology, operative data, and post-operative follow-up were also collected.    Results  Eight pedicle screws were placed in two L4-L5 fusion cases. Mean screw tip deviation was 2.1 mm (range 0.8–5.2 mm), mean tail deviation was 3.2 mm (range 0.9–5.4 mm), and mean angular offset was 2.4 degrees (range 0.7–3.8 degrees). All eight screws were accurately placed based on the Gertzbein-Robbins scale (88% Grade A and 12% Grade B). There were no cases of screw revision or new post-operative deficit. Both patients experienced improvement in Frankel grade and Karnofsky Performance Status (KPS) score by 6 weeks post-op.    Conclusion  The ExcelsiusGPS® robot allows for precise execution of an intended pre-planned trajectory and accurate screw placement in the first patients to undergo robotic-assisted fusion with this technology.

Pedicle screw accuracy assessment in ExcelsiusGPS® robotic spine surgery: evaluation of deviation from pre-planned trajectory