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Meshless Method for Simulation of Needle Insertion into Soft Tissues: Preliminary Results

  • Adam WittekEmail author
  • George Bourantas
  • Grand Roman Joldes
  • Anton Khau
  • Konstantinos Mountris
  • Surya P. N. Singh
  • Karol Miller
Conference paper

Abstract

Needle insertion (placement) into human body organs is a frequently performed procedure in clinical practice. Its success largely depends on the accuracy with which the needle tip reaches the anatomical target. As the tissue deforms due to interactions with the needle, the target tends to change its position. One possible way to decrease the risk of missing the target can be to account for tissue deformations when planning the needle insertion. This can be achieved by employing computational biomechanics models to predict the tissue deformations.

In this study, for computing the tissue deformations due to needle insertion, we employed a meshless formulation of computational mechanics that uses a spatial discretisation in a form of a cloud of points. We used the previously verified Meshless Total Lagrangian Explicit Dynamics (MTLED) algorithm that facilitates accurate and robust prediction of soft continua/soft tissues mechanical responses under large deformations. For modelling of interactions between the needle and soft tissues, we propose a kinematic approach that directly links deformation of the tissue adjacent to the needle with the needle motion. This approach does not require any assumptions about the exact mechanisms of such interactions. Its parameters can be determined directly from observation of the tissue sample/body organ deformations during needle insertion.

We evaluated the performance of our kinematic approach for modelling the interactions between the needle and the tissue through application in modelling of needle insertion into a cylindrical sample (diameter of 30 mm and height of 17 mm) of Sylgard 527 (by Dow Corning) silicone gel and comparing the results obtained from the model with the experimentally measured force acting on the needle. The needle insertion depth was up to 10 mm. For modelling of the constitutive responses of Sylgard 527 gel, we used the neo-Hookean hyperelastic material model with the shear modulus experimentally determined from compression of Sylgard 527 gel samples.

The general behaviour of the needle force–insertion depth relationship was correctly predicted by our framework that combines a meshless method of computational mechanics for computing the deformations and kinematic approach for modelling the interactions between the needle and soft tissues. The predicted force magnitude differed by only 25% from the experimentally observed value. These differences require further analysis. One possible explanation can be that the neo-Hookean material model we used here may not be sufficient to correctly represent Sylgard 527 gel constitutive behaviour.

Keywords

Needle insertion simulation Meshless methods Meshless Total Lagrange Explicit Dynamics Hyperelastic material models Computational biomechanics 

Notes

Acknowledgements

This research was supported by the Australian Government through the Australian Research Council's Discovery Projects funding scheme (project DP160100714). Adam Wittek and Anton Khau thank Dr Barry Doyle for use of the VascLab tension–compression rig.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Adam Wittek
    • 1
    Email author
  • George Bourantas
    • 4
  • Grand Roman Joldes
    • 1
  • Anton Khau
    • 4
  • Konstantinos Mountris
    • 2
  • Surya P. N. Singh
    • 3
  • Karol Miller
    • 1
  1. 1.Intelligent Systems for Medicine Laboratory, Department of Mechanical EngineeringThe University of Western AustraliaPerthAustralia
  2. 2.Aragón Institute for Engineering Research, University of Zaragoza, IIS AragónZaragozaSpain
  3. 3.Robotics Design Laboratory, School of Information Technology and Electrical EngineeringThe University of QueenslandBrisbaneAustralia
  4. 4.Intelligent Systems for Medicine LaboratoryThe University of Western AustraliaPerthUK

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