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3D image-guided robotic needle positioning system for small animal interventions.

Jeffrey S Bax1, Christopher S R Waring, Shi Sherebrin

  • 1Biomedical Engineering Graduate Program, The University of Western Ontario, London, Ontario, Canada. jbax@imaging.robarts.ca

Medical Physics
|January 10, 2013
PubMed
Summary

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This study introduces a micro-computed tomography (micro-CT) guided robotic system for precise small animal needle positioning. The system achieves a mean targeting error under 200 μm, enhancing image-guided interventions in preclinical research.

Area of Science:

  • Robotics in Medicine
  • Biomedical Engineering
  • Medical Imaging

Background:

  • Image-guided interventions (IGIs) are crucial for preclinical research.
  • Accurate robotic positioning systems are needed for small animal studies.
  • Existing systems face challenges with targeting accuracy and workflow complexity.

Purpose of the Study:

  • To design and evaluate a micro-CT guided robotic needle positioning system for small animals.
  • To achieve a mean targeting error of less than 200 μm.
  • To enhance user-friendliness and simplify the intervention workflow.

Main Methods:

  • A novel remote center of motion implementation was used for simplified robotic design.
  • The robot operates within a 25 cm micro-CT bore, allowing in-situ imaging and intervention.

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  • Improved needle calibration methods and a calibration fixture were developed.
  • Two registration modes (high-accuracy and fast-low-accuracy) were implemented for coordinate system alignment.

    • Main Results:

    • The primary registration achieved a target registration error (TRE) of 31 ± 12 μm.
    • The combined registration achieved a TRE of 139 ± 63 μm.
    • Overall system targeting errors were 149 ± 41 μm (primary) and 218 ± 38 μm (combined).
    • Pilot in vivo experiments demonstrated successful system performance.

    Conclusions:

    • The robotic system successfully achieved the objective of <200 μm mean targeting error.
    • The system offers improved repeatability compared to existing designs.
    • This technology expands the capabilities for image-guided interventions in preclinical research.