Hyper- and viscoelastic modeling of needle and brain tissue interaction

Area of Science:

• Robotics
• Biomedical Engineering
• Computational Mechanics

Background:

• Accurate deep brain needle insertion is crucial for diagnostics and therapeutics.
• Current methods face challenges in precise targeting within delicate brain tissue.

Purpose of the Study:

• To develop an automated robotic system for flexible needle steering in the brain.
• To create a finite element model for investigating safe needle steering parameters.
• To optimize needle design and control systems for enhanced targeting accuracy.

Main Methods:

• Developed a finite element model simulating brain tissue's hyperelastic and viscoelastic properties.
• Created robotic system for automated flexible needle steering.
• Varied needle parameters (radius, bevel angle, fillet radius, speeds) to analyze tissue response.

Main Results:

• Quantified tissue stress, strain, and strain rate under different needle insertion and rotation parameters.
• Identified key parameters influencing tissue-needle interaction safety.
• Demonstrated the model's capability to simulate complex brain tissue responses.

Conclusions:

• The developed finite element model provides insights into safe parameters for robotic intracerebral needle steering.
• Results will inform the design of improved needle tips and control strategies for neurosurgery.
• This work advances automated robotic interventions in the brain.