Microwave imaging has been proposed for breast cancer detection and treatment monitoring. The introduction of new approaches or next-generation prototype systems requires characterization of expected variability when scanning participants over clinically relevant timeframes.Objective: The objective of this study is to quantify the reliability and variability in scans of a group of 35 volunteers collected at multiple time points with a next-generation microwave imaging system. Methods: Multiple scans of the same volunteer are collected both during one visit and over multiple visits. Test-retest reliability and variability in measurements are investigated for the average permittivity of breast tissues. Results: The average permittivity for each volunteer exhibited similarity during and between sessions, with some variation noted for smaller breast sizes. The average properties of right and left breasts were also similar. Reliability was demonstrated with the intra-class correlation coefficient (ICC) values statistically greater than 0.9 both within and between sessions. Variability of the measurement was typically less than one unit and coefficient of variation less than 5% (within sessions) or 6% (between sessions).Conclusion: The microwave imaging system exhibits excellent reliability when scanning volunteers multiple times during one session and between sessions. This study represents the largest group of participants scanned at multiple time points reported to date. Significance: The excellent reliability demonstrated in this study suggests that microwave breast imaging has strong potential for capturing changes over time, such as treatment or therapy related effects, along with detecting changes in breast tissues.

Hydration is an important aspect of human health, as water is a critical nutrient used in many physiological processes. However, there is currently no clinical gold standard for non-invasively assessing hydration status. Recent work has suggested that permittivity in the microwave frequency range provides a physiologically meaningful metric for hydration monitoring. Using a simple time of flight technique for estimating permittivity, this study investigates microwave-based hydration assessment using a population of volunteers fasting during Ramadan. Volunteers are measured throughout the day while fasting during Ramadan and while not fasting after Ramadan. Comparing the estimated changes in permittivity to changes in weight and the time s fails to establish a clear relationship between permittivity and hydration. Assessing the subtle changes in hydration found in a population of sedentary, healthy adults proves difficult and more work is required to determine approaches suitable for tracking subtle changes in hydration over time with microwave-based hydration assessment techniques.

The incorporation of a priori information is required to regularize the ill-posed microwave scattering problem associated with microwave tomography. A new physics-informed regularization technique using electromagnetic power balance is introduced. The method does not require the ad hoc specification of the regularization parameter. The technique is demonstrated on in silico synthetic data, as well as previously reported measurements for simple lossless dielectrics in free space, and in vivo measurements of human forearms in a lossy matching medium. In the lossless imaging scenario, the power balance regularization technique produces similar results to the well-known truncated conjugate gradient and total variation multiplicative regularizers. However, for the biomedical measurements, the results are markedly different with the reconstructed images demonstrating significantly higher contrast, more accurate property estimation for high contrast inclusions, and successful resolution of inclusions in the imaginary permittivity. The power balance regularization technique can be easily added to conventional microwave imaging algorithms and suggests other physics-informed regularization schemes could be used in future work.

Readily available animal tissue, such as ground beef, is a convenient material to represent the dielectric properties of biological tissue when validating microwave imaging and sensing hardware and techniques. The reliable use of these materials depends on the accurate characterization of their properties. In this work, the effect of physiologically relevant levels of dehydration on ex vivo tissue samples is quantified while controlling for variation within and between samples. Seven commercial ground beef samples (90% lean muscle, 10% fat) are dehydrated from 0.0% to 7.0% in 1.0% increments by weight. Dielectric measurements are collected using a conventional dielectric probe technique from 0.2 to 6 GHz. A linear mixed‐effects model is used to control for within‐ and between‐sample variation while modeling the effect of dehydration and dispersion across frequency. Significant () changes are noted in both permittivity and conductivity due to sample dehydration. For a 1% change in weight due to dehydration, changes in permittivity (5.1%–5.6%) and conductivity (3.2%–5.7%) are reported. These changes are important for the use of large muscle‐based phantoms in microwave sensing and imaging validation, as well as the feasibility of microwave hydration assessment. The statistical model used here can be applied to similar research questions and can augment existing frameworks for reporting dielectric measurements.