Bevel-Tip Needle Deflection Modeling, Simulation, and Validation in Multi-Layer Tissues.

Area of Science:

• Medical Engineering
• Robotics
• Biomedical Simulation

Background:

• Percutaneous needle insertions are crucial for diagnostics and therapeutics but face accuracy challenges due to soft tissue deflection.
• Existing robotic and imaging guidance systems struggle to fully compensate for needle path deviation caused by tissue interaction.

Purpose of the Study:

• To develop a novel mechanics-based 2D needle model for accurate percutaneous insertions.
• To incorporate nonlinear, strain-dependent soft tissue behavior into needle insertion simulations.
• To enable real-time, three-degree-of-freedom (DOF) planar needle motion control.

Main Methods:

• A mechanics-based 2D bevel-tip needle model was developed.
• Real-time finite element simulation was employed to model needle-tissue interactions.
• The model accounts for nonlinear, strain-dependent soft tissue properties under compression.
• Custom multi-layer phantoms and chicken breast tissues were used for validation.

Main Results:

• The proposed model accurately predicts needle deflection in soft tissues.
• Simulations achieved less than 1mm in-plane insertion errors at depths up to 61mm.
• Validation demonstrated the model's effectiveness in both phantom and biological tissues.

Conclusions:

• The novel mechanics-based needle model significantly enhances the accuracy of percutaneous needle insertions.
• This approach offers a generalizable solution for overcoming soft tissue deflection challenges in minimally invasive procedures.
• The real-time simulation capability holds promise for improved robotic-assisted surgery and interventions.