An accurate analytical modeling method for microwave-based breast tumor detection and phantom manufacturing

Area of Science:

• Biomedical Engineering
• Electrical Engineering
• Medical Physics

Background:

• Early breast cancer detection drastically improves patient survival rates.
• Mathematical modeling aids in the rapid identification of cancerous tissues.
• Current modeling techniques may lack the anatomical accuracy needed for optimal detection.

Purpose of the Study:

• To introduce and evaluate an innovative segmented hemispherical modeling approach for breast tissue.
• To assess the model's performance in discriminating between healthy and cancerous tissues.
• To compare the proposed model against existing state-of-the-art methods.

Main Methods:

• Breast tissues modeled as electrical capacitors with unequal plates.
• Calculation of effective permittivity using dielectric properties.
• Analysis via analytical, simulation-based, and experimental approaches.

Main Results:

• The hemispherical model significantly outperformed cubic models in discrimination levels (0.335 vs. 0.001 for fatty tissue, 0.412 vs. 0.001 for dense tissue).
• The model accurately replicated breast anatomy, showing superior tumor detection efficacy (3 dB and 7-degree difference in S-parameters).
• Potential for developing affordable, accurate breast phantoms for research.

Conclusions:

• The segmented hemispherical model offers superior performance for breast cancer detection.
• The model's anatomical accuracy and improved detection capabilities are significant advancements.
• The proposed method could lead to more practical and reliable breast cancer detection techniques and research tools.