Microwave Antenna Radiometric Temperature Sensing System for Non-Invasive Deep Tissue Thermal Analysis
Year: 2025
Type: article
Abstract: This paper investigates the optimal conditions for temperature modeling in deep human tissue, with a focus on non-invasive tumor detection. A custom rectangular microwave patch antenna and an integrated radiometer system are designed and fabricated. The study emphasizes the determination of the optimal resonance frequency and directivity/radiation patterns, employing characteristic modes theory for analysis. This study integrates the antenna developed with realistic muscle phantoms, engineered to replicate human tissue properties, enabling accurate simulations of microwave interactions. Analysis of S − parameters and impedance characteristics is conducted to evaluate performance. A radiometer, adapted from astrophysical instrumentation principles, is utilized to improve temperature measurement precision, with key performance metrics assessed for subsequent optimization. Integration of an antenna, phantom models, and a radiometer system enhances diagnostic accuracy and sensitivity, presenting a promising tool for advanced clinical applications. The antenna-radiometer system enables modeling of temperature distribution at a 30 mm depth within a phantom, with potential error effects in temperature estimation analyzed to ensure reliability. Validation is achieved using fabricated phantoms engineered to replicate human tissue properties. Experimental results from muscle phantoms substantiate the system’s efficacy and performance. However, discrepancies in measured outcomes suggest errors, which are systematically investigated and discussed. The study concludes by assessing the technology’s potential to advance medical imaging, particularly for early tumor detection and monitoring, and outlines future research directions to optimize this approach for clinical deployment.
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
Funder: Cabildo de Tenerife
OpenAlex ID: W7116706310
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