Quantitative Interpretation of UWB Radar Images for Non-Invasive Tissue Temperature Estimation during Hyperthermia

An Effective Framework for Deep-Learning-Enhanced Quantitative Microwave Imaging and Its Potential for Medical Applications

Microwave imaging is emerging as an alternative modality to conventional medical diagnostics technologies. However, its adoption is hindered by the intrinsic difficulties faced in the solution of the underlying inverse scattering problem, namely non-linearity and ill-posedness. In this paper, an innovative approach for a reliable and automated solution of the inverse scattering problem is presented, which combines a qualitative imaging technique and deep learning in a two-step framework. In the first step, the orthogonality sampling method is employed to process measurements of the scattered field into an image, which explicitly provides an estimate of the targets shapes and implicitly encodes information in their contrast values. In the second step, the images obtained in the previous step are fed into a neural network (U-Net), whose duty is retrieving the exact shape of the target and its contrast value. This task is cast as an image segmentation one, where each pixel is classified into a discrete set of permittivity values within a given range. The use of a reduced number of possible permittivities facilitates the training stage by limiting its scope. The approach was tested with synthetic data and validated with experimental data taken from the Fresnel database to allow a fair comparison with the literature. Finally, its potential for biomedical imaging is demonstrated with a numerical example related to microwave brain stroke diagnosis.

Numerical Estimation of SAR and Temperature Distributions inside Differently Shaped Female Breast Tumors during Radio-Frequency Ablation

Radio-frequency (RF) ablation is a reliable technique for the treatment of deep-seated malignant tumors, including breast carcinoma, using high ablative temperatures. The paper aims at a comparative analysis of the specific absorption rate and temperature distribution during RF ablation with regard to different female breast tumors. In the study, four tumor models equivalent to an irregular tumor were considered, i.e., an equivalent sphere and ellipsoid with the same surfaces and volumes as the irregular tumor and an equivalent sphere and ellipsoid inscribed in the irregular tumor. An RF applicator with a specific voltage, operating at 100 kHz inserted into the anatomically correct female breast, was applied as a source of electromagnetically induced heat. A conjugated Laplace equation with the modified Pennes equation was used to obtain the appropriate temperature gradient in the treated area. The levels of power dissipation in terms of the specific absorption rate (SAR) inside the naturalistically shaped tumor, together with the temperature profiles of the four simplified tumor models equivalent to the irregular one, were determined. It was suggested that the equivalent tumor models might successfully replace a real, irregularly shaped tumor, and the presented numeric methodology may play an important role in the complex therapeutic RF ablation process of irregularly shaped female breast tumors.

MNP-Enhanced Microwave Medical Imaging by Means of Pseudo-Noise Sensing

Magnetic nanoparticles have been investigated for microwave imaging over the last decade. The use of functionalized magnetic nanoparticles, which are able to accumulate selectively within tumorous tissue, can increase the diagnostic reliability. This paper deals with the detecting and imaging of magnetic nanoparticles by means of ultra-wideband microwave sensing via pseudo-noise technology. The investigations were based on phantom measurements. In the first experiment, we analyzed the detectability of magnetic nanoparticles depending on the magnetic field intensity of the polarizing magnetic field, as well as the viscosity of the target and the surrounding medium in which the particles were embedded, respectively. The results show a nonlinear behavior of the magnetic nanoparticle response depending on the magnetic field intensity for magnetic nanoparticles diluted in distilled water and for magnetic nanoparticles embedded in a solid medium. Furthermore, the maximum amplitude of the magnetic nanoparticles responses varies for the different surrounding materials of the magnetic nanoparticles. In the second experiment, we investigated the influence of the target position on the three-dimensional imaging of the magnetic nanoparticles in a realistic measurement setup for breast cancer imaging. The results show that the magnetic nanoparticles can be detected successfully. However, the intensity of the particles in the image depends on its position due to the path-dependent attenuation, the inhomogeneous microwave illumination of the breast, and the inhomogeneity of the magnetic field. Regarding the last point, we present an approach to compensate for the inhomogeneity of the magnetic field by computing a position-dependent correction factor based on the measured magnetic field intensity and the magnetic susceptibility of the magnetic particles. Moreover, the results indicate an influence of the polarizing magnetic field on the measured ultra-wideband signals even without magnetic nanoparticles. Such a disturbing influence of the polarizing magnetic field on the measurements should be reduced for a robust magnetic nanoparticles detection. Therefore, we analyzed the two-state (ON/OFF) and the sinusoidal modulation of the external magnetic field concerning the detectability of the magnetic nanoparticles with respect to these spurious effects, as well as their practical application.