Spatial sensitivity distribution assessment and Monte Carlo simulations for needle-based bioimpedance imaging during...

Area of Science:

• Biomedical Engineering
• Computational Modeling
• Medical Device Technology

Background:

• Needle insertions, common medical procedures, have high error rates.
• Impedance measurements with electrode-equipped needles show potential for improved tissue targeting.
• Current impedance visualization requires extensive pre-measured data and electric field knowledge.

Purpose of the Study:

• To present two finite element simulation approaches for impedance data generation and electric field sensitivity visualization.
• To overcome the reliance on pre-measured impedance datasets for tissue differentiation.
• To enable consistent 3D visualization of electric field sensitivity for electrode-equipped needles.

Main Methods:

• Monte Carlo simulations generated impedance datasets for homogeneous and inhomogeneous tissues.
• Two singularity analysis methods simulated spatial sensitivity distributions for a 12-electrode needle layout.
• Simulations compared impedance generation and sensitivity analysis methods under 12 bipolar excitation states.

Main Results:

• Simulated impedance spread statistically varied significantly with tissue type and inhomogeneity.
• Both singularity analysis methods yielded bounded sensitivity volumes of similar extent and symmetry.
• The study demonstrated the feasibility of simulation-based impedance data and sensitivity visualization.

Conclusions:

• Finite element simulations offer a viable alternative to extensive pre-measured impedance data.
• The developed methods provide insights into tissue properties and electric field interactions during needle insertion.
• Future work should include detailed tissue properties like anisotropy and deformation for enhanced prediction accuracy.