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A Spine Robotic-Assisted Navigation System for Pedicle Screw Placement
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Technical Note: Known-Component Registration for Robotic Drill Guide Positioning.

T Yi1, V Ramchandran1, J H Siewerdsen1

  • 1Department of Biomedical Engineering, Johns Hopkins Univ., Baltimore, MD.

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|September 12, 2022
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Summary
This summary is machine-generated.

This study introduces an x-ray-guided robotic system for precise spine surgery. The known-component registration (KC-Reg) algorithm enhances surgical instrument accuracy, offering a potentially major benefit for patients.

Keywords:
3D-2D registrationKnown-component registrationimage-guided surgerysurgical robotics

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Area of Science:

  • Robotics in Medicine
  • Surgical Navigation Systems
  • Medical Imaging

Background:

  • Spine pedicle screw placement is critical for spinal fusion and stabilization.
  • Current methods for guiding surgical instruments can have limitations in accuracy and intraoperative adaptability.
  • Robotic assistance and advanced imaging techniques offer potential improvements in surgical precision.

Purpose of the Study:

  • To develop and evaluate an x-ray-guided robotic positioning method for surgical instruments.
  • To improve the accuracy of transpedicle drill and screw delivery in spine surgery.
  • To assess the performance and robustness of the system in preclinical settings.

Main Methods:

  • Utilized the known-component registration (KC-Reg) algorithm to align 3D CT scans with intraoperative 2D radiographs.
  • Employed a robotically-held drill guide driven by registration transformations and offline hand-eye calibration.
  • Tested the system's accuracy and robustness using phantom and cadaver models, comparing it to conventional surgical tracker guidance.

Main Results:

  • The KC-Reg approach achieved a tooltip error of 1.51 ± 0.51 mm and an approach angle error of 1.01 ± 0.92°.
  • In cadaver studies with anatomical deformation, target registration error was 2.31 ± 1.05 mm and 0.66 ± 0.62°, outperforming a surgical tracker.
  • The method demonstrated robustness against anatomical deformation, attributed to the local nature of radiographic registration.

Conclusions:

  • X-ray-guided robotic systems, utilizing methods like KC-Reg, provide accurate instrument positioning compatible with standard fluoroscopic workflows.
  • The KC-Reg approach enhances quantitative accuracy and provides valuable guidance and quality assurance during multi-planar fluoroscopic procedures.
  • This technology offers a potentially significant surgical benefit by improving precision and adaptability in complex spine surgeries.