Purpose. A novel form of x-ray-guided robotic positioning of surgical instruments is reported and evaluated in preclinical studies of spine pedicle screw placement with the aim of improving and automating safe, accurate delivery of transpedicle K-wire and screw.
Methods. The known-component registration (KC-Reg) algorithm was used to register the 3D patient CT and CAD model of a pedicle drill guide to intraoperatively acquired 2D radiographs. The resulting transformations, with offline hand-eye calibration, drive a robot-ically-held pedicle drill guide to target trajectories established in the preoperative CT of the patient. The proposed method was as-sessed in comparison to a more conventional tracker-guided approach, and robustness to different clinically realistic errors (e.g., suboptimal fiducial arrangements, gross anatomical deformation) was tested in phantom and cadaver studies.
Results. Analyzing the target registration error (TRE) in terms of the deviation from the target plan, the KC-Reg approach resulted in 1.51 ± 0.51 mm error at the tooltip and 1.01 ± 0.92° in approach angle, showing comparable performance to that of the tracker-guided workflow. In cadaver studies with anatomical deformation, TRE of 2.31 ± 1.05 mm and 0.66 ± 0.62° were observed, with statistically improved performance over a surgical tracker through registration of locally rigid bony anatomy.
Conclusions. Novel x-ray guidance offers an accurate means of driving robotic systems that is naturally compatible with conven-tional workflow in fluoroscopically guided procedures. Moreover, the method was robust against anatomical deformation due to the radiographic scene’s local nature used in 3D-2D registration, presenting a potentially major benefit in surgeries.
Thomas Yi, Vignesh Ramchandran, Jeffrey H. Siewerdsen, and Ali Uneri, "Known-component registration for robotic drill guide positioning in spine pedicle screw placement (Conference Presentation)," Proc. SPIE 10576, Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling, 105760B (Presented at SPIE Medical Imaging: February 13, 2018; Published: 14 March 2018); https://doi.org/10.1117/12.2293886.5751542824001.
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