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Related Experiment Video

Updated: May 13, 2026

Transperineal Prostate Biopsy Using a Cone-shaped Double-hole Method with Dual-plane Probe Guidance
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Transperineal Prostate Biopsy Using a Cone-shaped Double-hole Method with Dual-plane Probe Guidance

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Model-based needle control in prostate percutaneous procedures.

Arash Maghsoudi1, Mehran Jahed

  • 1Robotics and Machine Vision Lab, School of Electrical Engineering, Sharif University of Technology, Tehran, Iran. a_maghsoudi@ee.sharif.ir

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of Engineering in Medicine
|March 23, 2013
PubMed
Summary
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This study models needle movement in soft tissue for percutaneous procedures. An adaptive controller shows improved performance over inverse dynamics, especially with uncertain tissue properties.

Area of Science:

  • Robotics and Control Systems
  • Biomedical Engineering
  • Soft Tissue Mechanics

Background:

  • Percutaneous needle insertion into soft tissue is complex and critical for medical procedures.
  • Accurate modeling of needle-tissue interaction is essential for robotic-assisted surgery and interventions.
  • Understanding soft tissue mechanics is key to predicting and controlling needle path.

Purpose of the Study:

  • To develop and evaluate a model-based dynamics approach for controlling needle insertion into prostate soft tissue.
  • To investigate the impact of soft tissue mechanical property uncertainties on needle movement control.
  • To compare the performance of an inverse dynamics control method with an adaptive controller.

Main Methods:

  • A model-based dynamics equation was used to simulate needle movement through prostate soft tissue.

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  • Finite element modeling (FEM) and tissue deformation data were employed to estimate applied forces.
  • An inverse dynamics control method using a sliding mode approach was implemented.
  • An adaptive controller was developed to handle uncertainties in soft tissue mechanical parameters.
  • Sensitivity analysis was conducted to assess the effect of parameter uncertainty on system performance.

    • Main Results:

    • The model successfully estimated applied forces based on tissue deformation and FEM.
    • Sensitivity analysis confirmed that uncertainty in tissue mechanical parameters impacts system performance.
    • The adaptive controller demonstrated slightly better performance compared to the inverse dynamics method.
    • The adaptive controller's improved performance came with the need for fine-tuning an additional gain parameter.

    Conclusions:

    • Model-based dynamics and advanced control strategies are crucial for precise percutaneous needle insertion.
    • Adaptive control offers robustness against uncertainties in soft tissue mechanical properties.
    • Further research into adaptive control tuning can optimize performance for challenging needle insertion tasks.