Feasibility and accuracy of a robotic guidance system for navigated spine surgery in a hybrid operating room: a cadaver study

Abstract

The combination of navigation and robotics in spine surgery has the potential to accurately identify and maintain bone entry position and planned trajectory. The goal of this study was to examine the feasibility, accuracy and efficacy of a new robot-guided system for semi-automated, minimally invasive, pedicle screw placement. A custom robotic arm was integrated into a hybrid operating room (OR) equipped with an augmented reality surgical navigation system (ARSN). The robot was mounted on the OR-table and used to assist in placing Jamshidi needles in 113 pedicles in four cadavers. The ARSN system was used for planning screw paths and directing the robot. The robot arm autonomously aligned with the planned screw trajectory, and the surgeon inserted the Jamshidi needle into the pedicle. Accuracy measurements were performed on verification cone beam computed tomographies with the planned paths superimposed. To provide a clinical grading according to the Gertzbein scale, pedicle screw diameters were simulated on the placed Jamshidi needles. A technical accuracy at bone entry point of 0.48 ± 0.44 mm and 0.68 ± 0.58 mm was achieved in the axial and sagittal views, respectively. The corresponding angular errors were 0.94 ± 0.83° and 0.87 ± 0.82°. The accuracy was statistically superior (p < 0.001) to ARSN without robotic assistance. Simulated pedicle screw grading resulted in a clinical accuracy of 100%. This study demonstrates that the use of a semi-automated surgical robot for pedicle screw placement provides an accuracy well above what is clinically acceptable.

Figure 1

Layout of the robotic arm with a Jamshidi needle (blue) in the instrument adapter is depicted in (a). In (b), the entire surgical setup in the operating room is seen with the robot, C-arm and navigation interface on a monitor.

Figure 2

Depiction of the surgical navigation interface during robot assisted surgery: In (a), top left shows a coronal view along the pedicle trajectory, top right shows an axial view with the navigated Jamshidi in green, bottom left a sagittal view, and bottom right a camera feed with an augmented reality overlay depicting the underlying anatomy. In (b), a post-operative computed tomography scan of a placed Jamshidi needle is depicted. Axial view to the left and sagittal view to the right.

Figure 3

Distribution of distances between placed pedicle devices (n = 113) and planned paths showing: accuracy at bone entry point in the axial (a) and sagittal (b) view, and accuracy at device tip in the axial (c) and sagittal (d) view. Boxplots display the median as a solid line, hinges corresponding to upper and lower quartiles, and whiskers indicating data up to 1.5 interquartile range. Dots represent outliers.

Figure 4

Entry point errors of the Jamshidi needles (n = 113). Planned entry point is the center of the circle and red dots represent the deviation, in mm, of each Jamshidi needle placed.

Figure 5

Distribution of angle errors between placed pedicle devices (n = 113) and planned paths, showing angle deviations in the axial (a) and sagittal (b) view. Boxplots display the median as a solid line, hinges corresponding to upper and lower quartiles, and whiskers indicating data up to 1.5 interquartile range. Dots represent outliers.

Figure 6

The distribution of insertion times per pedicle cannulation (n = 76), including both robotic navigation and pedicle cannulation with Jamshidi needle. Boxplots display the median as a solid line, hinges corresponding to upper and lower quartiles, and whiskers indicating data up to 1.5 interquartile range. Dots represent outliers.