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Robotic drill guide positioning using known-component 3D-2D image registration.

Thomas Yi1, Vignesh Ramchandran1, Jeffrey H Siewerdsen1

  • 1Johns Hopkins University, Department of Biomedical Engineering, Baltimore, Maryland, United States.

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Summary
This summary is machine-generated.

This study introduces an x-ray image-guided robotic system for precise spinal pedicle screw placement. The novel known-component registration method significantly improves accuracy in cadaver studies compared to traditional approaches.

Keywords:
3D–2D registrationimage-guided surgeryknown-component registrationsurgical robotics

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Area of Science:

  • Medical Robotics
  • Image-Guided Surgery
  • Spinal Surgery

Background:

  • Accurate placement of spinal pedicle screws is crucial for successful spinal fusion and minimizing neurological complications.
  • Conventional methods can be limited by intraoperative inaccuracies and anatomical variations.

Purpose of the Study:

  • To evaluate a novel x-ray image-guided robotic instrument positioning system for transpedicle K-wire and screw delivery.
  • To compare the accuracy and robustness of the known-component (KC) registration algorithm against a conventional tracker-based approach.

Main Methods:

  • Utilized the known-component (KC) registration algorithm to align 3D CT data with intraoperative 2D radiographs.
  • Employed offline hand-eye calibration to guide a robotically held drill guide to preoperative CT-defined trajectories.
  • Assessed accuracy using target registration error (TRE) and approach angle in phantom and cadaver models, including studies with anatomical deformation.

Main Results:

  • In phantom studies, the KC approach demonstrated accuracy comparable to the tracker-based method.
  • In cadaver studies with realistic deformation, the KC approach showed statistically significant improvements in accuracy (TRE and angle) compared to the tracker-based method.
  • The system demonstrated robustness to anatomical deformation, attributed to the local rigidity of anatomy in radiographic views.

Conclusions:

  • X-ray image-guided robotic positioning provides accurate instrument delivery for spinal procedures.
  • The KC registration method offers a robust and accurate alternative to conventional tracker-based systems, particularly in the presence of anatomical deformation.
  • This technology has the potential to integrate seamlessly into existing fluoroscopically guided surgical workflows.