Three-dimensional assessment of robot-assisted pedicle screw placement accuracy and instrumentation reliability based on a preplanned trajectory

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  • 1 Department of Neurosurgery, Johns Hopkins School of Medicine;
  • 3 Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland;
  • 2 Aristotle University of Thessaloniki School of Medicine, Thessaloniki, Greece; and
  • 4 Globus Medical, Audubon, Pennsylvania
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OBJECTIVE

Robotic spine surgery systems are increasingly used in the US market. As this technology gains traction, however, it is necessary to identify mechanisms that assess its effectiveness and allow for its continued improvement. One such mechanism is the development of a new 3D grading system that can serve as the foundation for error-based learning in robot systems. Herein the authors attempted 1) to define a system of providing accuracy data along all three pedicle screw placement axes, that is, cephalocaudal, mediolateral, and screw long axes; and 2) to use the grading system to evaluate the mean accuracy of thoracolumbar pedicle screws placed using a single commercially available robotic system.

METHODS

The authors retrospectively reviewed a prospectively maintained, IRB-approved database of patients at a single tertiary care center who had undergone instrumented fusion of the thoracic or lumbosacral spine using robotic assistance. Patients with preoperatively planned screw trajectories and postoperative CT studies were included in the final analysis. Screw accuracy was measured as the net deviation of the planned trajectory from the actual screw trajectory in the mediolateral, cephalocaudal, and screw long axes.

RESULTS

The authors identified 47 patients, 51% male, whose pedicles had been instrumented with a total of 254 screws (63 thoracic, 191 lumbosacral). The patients had a mean age of 61.1 years and a mean BMI of 30.0 kg/m2. The mean screw tip accuracies were 1.3 ± 1.3 mm, 1.2 ± 1.1 mm, and 2.6 ± 2.2 mm in the mediolateral, cephalocaudal, and screw long axes, respectively, for a net linear deviation of 3.6 ± 2.3 mm and net angular deviation of 3.6° ± 2.8°. According to the Gertzbein-Robbins grading system, 184 screws (72%) were classified as grade A and 70 screws (28%) as grade B. Placement of 100% of the screws was clinically acceptable.

CONCLUSIONS

The accuracy of the discussed robotic spine system is similar to that described for other surgical systems. Additionally, the authors outline a new method of grading screw placement accuracy that measures deviation in all three relevant axes. This grading system could provide the error signal necessary for unsupervised machine learning by robotic systems, which would in turn support continued improvement in instrumentation placement accuracy.

Supplementary Materials

    • Supplemental Figure 1 (PDF 1.41 MB)

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Contributor Notes

Correspondence Nicholas Theodore: Johns Hopkins School of Medicine, Baltimore, MD. theodore@jhmi.edu.

INCLUDE WHEN CITING Published online May 29, 2020; DOI: 10.3171/2020.3.SPINE20208.

B.J. and Z.P. contributed equally to this study.

Disclosures Dr. Jiang is a consultant for Longeviti Neuro Solutions and receives grant funding from DePuy Synthes. Dr. Crawford receives royalties from Globus Medical. Dr. Theodore receives royalties from and has ownership interest in Globus Medical and is a consultant for Globus Medical and DePuy Synthes.

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