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Diffuse domain approach for flexible needle insertion and relaxation.

Katharina I Jerg1, Lalith Boggaram Naveen1, Guido Kanschat2

  • 1Mannheim Institute for Intelligent Systems in Medicine (MIISM), Heidelberg University, Mannheim, Germany.

International Journal for Numerical Methods in Biomedical Engineering
|October 6, 2023
PubMed
Summary
This summary is machine-generated.

This study enhances needle insertion simulations for flexible needles using a diffuse domain approach, eliminating complex meshing. A new relaxation model improves accuracy for realistic medical interventions.

Keywords:
Euler-Bernoulli beam theorydeformable needle insertiondiffuse domain methoddiffuse penalty methodlinear elastic equationneedle-tissue interactiontissue relaxation

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Area of Science:

  • Computational mechanics
  • Medical simulation
  • Robotics

Background:

  • Needle insertion simulations are crucial for surgical training and planning.
  • Current methods often require complex, boundary-conforming meshes.
  • Existing diffuse domain methods are limited to stiff needles.

Purpose of the Study:

  • To extend the diffuse domain approach for simulating flexible needles with bevel tips.
  • To introduce a novel relaxation model for needle-tissue interaction.
  • To validate the simulation against phantom experiments.

Main Methods:

  • Flexible needles modeled using an Euler-Bernoulli beam.
  • Diffuse domain approach to avoid meshing complexities.
  • Potential energy minimization for system relaxation.
  • Coupled Laplace equations and diffuse penalty method for boundary conditions.

Main Results:

  • Simulated needle deviation averaged 0.29 mm compared to phantom experiments.
  • Tissue deformation error was below 1 mm for 97.5% of markers.
  • Demonstrated feasibility of the relaxation process in additional experiments.

Conclusions:

  • The diffuse domain approach effectively simulates flexible needle insertion without meshing.
  • The novel relaxation model enhances accuracy in needle-tissue positioning.
  • This method is valuable for patient-specific simulations in realistic medical interventions.