The knowledge of frequency and temperature dependent dielectric properties of tissue is essential to develop ultra-wideband diagnostic technologies, such as a non-invasive temperature monitoring system during hyperthermia treatment. To this end, we characterized the dielectric properties of animal liver, muscle, fat and blood in the microwave frequency range from 0.5 GHz to 7 GHz and in the temperature range between 30 °C and 50 °C. The measured data were modeled to a two-pole Cole-Cole model and a second-order polynomial was introduced to fit the Cole-Cole parameters as a function of temperature. The parametric model provides access to the dielectric properties of tissue at any frequency and temperature in the specified range.

Wideband microwave imaging is of interest wherever optical opaque scenarios need to be analyzed, as these waves can penetrate biological tissues, many building materials, or industrial materials. One of the challenges of microwave imaging is the computation of the image from the measurement data because of the need to solve extensive inverse scattering problems due to the sometimes complicated wave propagation. The inversion problem simplifies if only spatially limited objects—point objects, in the simplest case—with temporally variable scattering properties are of interest. Differential imaging uses this time variance by observing the scenario under test over a certain time interval. Such problems exist in medical diagnostics, in the search for surviving earthquake victims, monitoring of the vitality of persons, detection of wood pests, control of industrial processes, and much more. This paper gives an overview of imaging methods for point-like targets and discusses the impact of target variations onto the radar data. Because the target variations are very weak in many applications, a major issue of differential imaging concerns the suppression of random effects by appropriate data processing and concepts of radar hardware. The paper introduces related methods and approaches, and some applications illustrate their performance.

Magnetic nanoparticle-aided microwave imaging is recently gaining an increasing interest as potential tool for breast cancer diagnostics. This is due to the peculiar features of magnetic nanoparticles, which are biocompatible, can be selectively targeted to the tumor and may change their microwave magnetic response when modulated by a polarizing magnetic field. This latter aspect is particularly appealing, as it enables the physical separation of the microwave signal due the malignancy, targeted by the nanoparticles, from that due to healthy tissue. This increases the specificity of the diagnostic tool, in principle allowing a diagnosis based solely on the detection of the signal due to the nanoparticles response. In this respect, a proper choice of the polarizing field modulation can remarkably increase the detection performances. This paper deals with this issue, by providing the mathematical framework for such an optimization and a procedure for estimating the required quantities from a set of proper measurements. The procedure is then experimentally demonstrated by applying it to a recently developed ultra-wide band radar system for the magnetic nanoparticle-aided detection of breast cancer. For such a system, the optimal magnetic field modulation is determined.