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Path Planning for Semi-automated Simulated Robotic Neurosurgery
Danying Hu1, Yuanzheng Gong2, Blake Hannaford1
1Biorobotics Laboratory, Department of Electrical Engineering, University of Washington, Seattle, WA 98195, USA.
Abstract:
This paper considers the semi-automated robotic surgical procedure for removing the brain tumor margins, where the manual operation is a tedious and time-consuming task for surgeons. We present robust path planning methods for robotic ablation of tumor residues in various shapes, which are represented in point-clouds instead of analytical geometry. Along with the path plans, corresponding metrics are also delivered to the surgeon for selecting the optimal candidate in the automated robotic ablation. The selected path plan is then executed and tested on RAVEN™ II surgical robot platform as part of the semi-automated robotic brain tumor ablation surgery in a simulated tissue phantom.
Insights
This study introduces automated robotic surgery path planning for brain tumor removal, simplifying a complex manual task for surgeons. The developed methods enable precise ablation of tumor residues using point-cloud data for improved surgical outcomes.
Area of Science:
- Neurosurgery
- Robotics
- Medical Engineering
Background:
- Manual resection of brain tumor margins is a complex and time-intensive surgical procedure.
- Current methods for robotic tumor ablation often rely on analytical geometry, limiting flexibility for irregular tumor shapes.
Purpose of the Study:
- To develop robust path planning methods for semi-automated robotic ablation of brain tumor residues.
- To provide surgeons with metrics for selecting optimal ablation paths for improved precision and efficiency.
Main Methods:
- Utilized point-cloud representations for tumor residue geometry, moving beyond analytical descriptions.
- Developed algorithms for generating and evaluating multiple path plans for robotic ablation.
- Integrated path planning with the RAVEN II surgical robot platform for simulated testing.
Main Results:
- Demonstrated robust path planning for irregularly shaped tumor residues using point-cloud data.
- Generated actionable metrics to aid surgeons in selecting the most effective ablation path.
- Successfully executed a semi-automated robotic brain tumor ablation procedure in a simulated environment.
Conclusions:
- Semi-automated robotic surgery with advanced path planning offers a promising approach to brain tumor margin resection.
- The presented methods enhance precision and efficiency in robotic tumor ablation, addressing limitations of manual and traditional robotic techniques.
