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Controlling the error on target motion through real-time mesh adaptation: Applications to deep brain stimulation.

Huu Phuoc Bui1, Satyendra Tomar1, Hadrien Courtecuisse2

  • 1Institute of Computational Engineering, University of Luxembourg, Faculty of Sciences Communication and Technology, Luxembourg.

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Summary

This study introduces an error-controlled mesh refinement for needle insertion simulations, improving accuracy for procedures like deep brain stimulation. The adaptive method reduces computational cost, enabling real-time simulations.

Keywords:
a posteriori error estimateadaptive refinementbrain shiftdeep brain stimulationfinite element methodreal-time simulation

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Area of Science:

  • Computational mechanics
  • Biomedical engineering
  • Medical simulation

Background:

  • Needle insertion simulations are crucial for percutaneous procedures and robotic surgery.
  • Accurate simulations require managing computational expense, especially with complex phenomena like brain shift.
  • Existing methods may lack efficiency in balancing accuracy and computational cost.

Purpose of the Study:

  • To present an error-controlled mesh refinement procedure for needle insertion simulations.
  • To demonstrate the procedure's effectiveness in improving accuracy and reducing computational time.
  • To apply the method to deep brain stimulation electrode implantation, considering brain shift.

Main Methods:

  • Developed an adaptive mesh refinement strategy based on error localization around the needle.
  • Applied the procedure to simulations of needle insertion, including deep brain stimulation electrode implantation.
  • Incorporated the brain shift phenomenon into the simulation model.

Main Results:

  • The error in displacement and stress fields is localized around the needle tip and shaft.
  • Adaptive mesh refinement significantly reduces error in these critical regions.
  • The approach enhances accuracy compared to uniform coarse meshes and saves computational time versus uniform finer meshes, facilitating real-time simulations.

Conclusions:

  • The proposed error-controlled mesh refinement procedure effectively enhances simulation accuracy and efficiency.
  • This methodology is applicable to various percutaneous procedures and robotic surgery development.
  • The ability to control computational expense and maintain accuracy has significant implications for medical simulations.