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Model based stabilization of soft tissue targets in needle insertion procedures.

Jerzy Smolen1, Alexandru Patriciu

  • 1McMaster University, Electrical and Computer Engineering Department, Ontario, Canada. smolenja@univmail.cis.mcmaster.ca

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|December 8, 2009
PubMed
Summary

This study introduces two methods for stabilizing soft tissue targets during needle insertion. A dynamic paddle approach offers greater robustness to modeling errors compared to a static paddle, making it more suitable for real-world applications.

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Area of Science:

  • Medical Robotics
  • Biomechanical Engineering
  • Surgical Navigation

Background:

  • Needle insertion procedures require precise target stabilization, especially in soft tissues.
  • Deformable objects present challenges due to unpredictable motion during manipulation.
  • External tools like paddles can aid in stabilizing targets but require optimal placement and strategy.

Purpose of the Study:

  • To develop and analyze methods for stabilizing soft tissue targets during needle insertion.
  • To compare the effectiveness and robustness of static versus dynamic paddle approaches.
  • To determine optimal paddle placement strategies for improved target stabilization.

Main Methods:

  • Investigated two paddle-based stabilization approaches: static and dynamic.

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  • Analyzed optimal paddle placement for minimizing target motion orthogonal to the needle axis.
  • Conducted numerical simulations on homogeneous and nonhomogeneous deformable objects.

    • Main Results:

    • The static paddle approach showed high sensitivity to object non-homogeneities and modeling errors.
    • The dynamic paddle approach demonstrated reduced sensitivity to modeling errors.
    • Optimal placement strategies were identified for both static and dynamic methods.

    Conclusions:

    • Dynamic paddle stabilization is more robust and desirable for physical applications due to its resilience to modeling uncertainties.
    • Static paddle stabilization is less reliable in the presence of object non-homogeneities.
    • The findings provide insights into improving precision and safety in needle-guided interventions.