Mathematical modeling and computer simulation of needle insertion into soft tissue.

Area of Science:

• Medical Robotics
• Computational Mechanics
• Biomedical Engineering

Background:

• Accurate modeling of needle insertion into soft tissues is crucial for robotic surgery and medical simulations.
• Existing methods often struggle with sensitivity to unknown tissue properties and interaction forces.
• Developing robust and parameter-efficient simulation techniques is an ongoing challenge.

Purpose of the Study:

• To present a novel kinematic approach for modeling needle insertion into soft tissues.
• To demonstrate the robustness of this approach to variations in tissue properties.
• To validate the proposed method through experimental and simulated scenarios.

Main Methods:

• A kinematic modeling approach formulated as a Dirichlet-type problem, driven by boundary motion.
• Utilizing Meshless Total Lagrangian Explicit Dynamics (MTLED) for computing soft tissue deformations.
• Parameter extraction directly from imaging data for straightforward implementation.

Main Results:

• The kinematic approach showed weak sensitivity to unknown tissue mechanical properties and needle-tissue interactions.
• Experimental validation using silicone gel samples confirmed the model's accuracy.
• Simulations of needle insertion into brain tissue further demonstrated robustness to assumed material properties.

Conclusions:

• The proposed kinematic modeling approach offers a robust and image-parameterizable method for simulating needle insertion.
• This technique has potential applications in surgical planning, robotic control, and medical training.
• The method's insensitivity to specific tissue properties simplifies its application in diverse biomedical contexts.