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Path planning for minimally-invasive knee surgery using a hybrid optimization procedure.

Adam Ciszkiewicz1, Grzegorz Milewski1

  • 1a Division of Experimental Mechanics and Biomechanics, Institute of Applied Mechanics , Cracow University of Technology , Cracow , Poland.

Computer Methods in Biomechanics and Biomedical Engineering
|January 11, 2018
PubMed
Summary

This study introduces a new method for medical tool path planning in minimally-invasive knee surgery. The procedure ensures collision-free paths, aiding in surgical planning and potentially autonomous procedures.

Keywords:
Genetic algorithmNedler-Mead methodcollision detection

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Area of Science:

  • Medical Robotics
  • Surgical Planning
  • Computational Geometry

Background:

  • Minimally-invasive surgery requires precise instrument navigation.
  • Current tool path planning methods may lack adaptability for complex anatomical variations.

Purpose of the Study:

  • To develop an effective procedure for medical tool path planning in minimally-invasive knee surgery.
  • To create a system capable of generating collision-free tool paths.
  • To incorporate anatomical variability into the planning process.

Main Methods:

  • Utilized surface meshes to represent surgical tools and knee anatomy.
  • Employed a control locations method with a hybrid optimization strategy.
  • Developed a knee model accounting for bone displacement and variable incision parameters.

Main Results:

  • Successfully generated collision-free tool paths for minimally-invasive knee surgery.
  • The developed procedure demonstrated effectiveness in complex surgical scenarios.
  • The knee model accurately represented anatomical variability.

Conclusions:

  • The proposed tool path planning procedure is effective for minimally-invasive knee surgery.
  • This method can significantly aid in surgical planning.
  • The procedure has potential applications in autonomous or semi-autonomous surgical systems.