Needle-Based Electrical Impedance Imaging Technology for Needle Navigation

Area of Science:

• Biomedical Engineering
• Medical Imaging
• Electrical Impedance Tomography

Background:

• Needle insertion procedures like biopsies and treatments require accurate guidance.
• Current ultrasound imaging has limitations in spatial resolution and interpretation.
• A new needle-based electrical impedance imaging system is proposed as an alternative.

Purpose of the Study:

• To develop and evaluate a needle-based electrical impedance imaging system for tissue classification.
• To assess the feasibility of this system as an alternative to conventional imaging techniques.
• To visualize tissue types in 3D using impedance measurements.

Main Methods:

• A modified needle with 12 electrodes was used for impedance measurements.
• Finite Element Method (FEM) simulations determined needle sensitivity volumes.
• A k-Nearest Neighbors (k-NN) algorithm classified tissue phantoms.
• A MATLAB Graphical User Interface (GUI) provided control and visualization.

Main Results:

• The system achieved an average tissue classification success rate of 70.56%.
• Fat tissue phantom classification was highly successful (100% accuracy).
• Layered tissue structures presented lower classification success rates.
• Average latency between measurement and 3D visualization was 112.1 ms.

Conclusions:

• Needle-based electrical impedance imaging is a feasible alternative to conventional methods.
• The developed system can classify tissues and provide 3D visualization.
• Further hardware, algorithm, and usability improvements are needed for clinical application.