is work presents the design and manufacturing of an anatomically and dielectrically realistic layered phantom of the human head that allows the insertion of ischemic and hemorrhagic stroke phantom models. A 2.5D physical phantom was designed using a representative anatomical image of the human head, which was simplified into 5 different layers that mimic the scalp, skull, cerebrospinal fluid, brain, and stroke regions in terms of anatomy and dielectric properties. Apart from the brain phantom, all other layers consist of a mixture of polyurethane rubber, graphite powder, and carbon black powder. e brain phantom is in the liquid form to facilitate the insertion of different stroke models (ischemic or hemorrhagic) with different positions and shapes. Phantoms were designed with dielectric properties valid within the frequency range 0.5-3.0 GHz, which is relevant for microwave stroke detection and classification. Molds for casting individual parts of the phantom were printed in 3D. e presented phantom is suitable for the development and testing of microwave systems and algorithms used in the detection and classification of vascular events relevant to stroke diagnosis.

Due to the clinically proven benefit of hyperthermia treatments if added to standard cancer therapies for various tumor sites and the recent development of non-invasive temperature measurements using magnetic resonance systems, the hyperthermia community is convinced that it is a time when even patients with brain tumors could benefit from regional microwave hyperthermia, even if they are the subject of a treatment to a vital organ. The purpose of this study was to numerically analyze the ability to achieve a therapeutically relevant constructive superposition of electromagnetic (EM) waves in the treatment of hyperthermia targets within the brain. We evaluated the effect of the target size and position, operating frequency, and the number of antenna elements forming the phased array applicator on the treatment quality. In total, 10 anatomically realistic 2D human head models were considered, in which 10 circular hyperthermia targets with diameters of 20, 25, and 30 mm were examined. Additionally, applicators with 8, 12, 16, and 24 antenna elements and operating frequencies of 434, 650, 915, and 1150 MHz, respectively, were analyzed. For all scenarios considered (4800 combinations), the EM field distributions of individual antenna elements were calculated and treatment planning was performed. Their quality was evaluated using parameters applied in clinical practice, i.e., target coverage (TC) and the target to hot-spot quotient (THQ). The 12-antenna phased array system operating at 434 MHz was the best candidate among all tested systems for HT treatments of glioblastoma tumors. The 12 antenna elements met all the requirements to cover the entire target area; an additional increase in the number of antenna elements did not have a significant effect on the treatment quality.

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The aim of this work was to test microwave brain stroke detection and classification using support vector machines (SVMs). We tested how the nature and variability of training data and system parameters impact the achieved classification accuracy. Using experimentally verified numerical models, a large database of synthetic training and test data was created. The models consist of an antenna array surrounding reconfigurable geometrically and dielectrically realistic human head phantoms with virtually inserted strokes of arbitrary size, and different dielectric parameters in different positions. The generated synthetic data sets were used to test four different hypotheses, regarding the appropriate parameters of the training dataset, the appropriate frequency range and the number of frequency points, as well as the level of subject variability to reach the highest SVM classification accuracy. The results indicate that the SVM algorithm is able to detect the presence of the stroke and classify it (i.e., ischemic or hemorrhagic) even when trained with single-frequency data. Moreover, it is shown that data of subjects with smaller strokes appear to be the most suitable for training accurate SVM predictors with high generalization capabilities. Finally, the datasets created for this study are made available to the community for testing and developing their own algorithms.

The design of proper antenna element (AE) for microwave-based head imaging or brain stroke detection is a crucial challenge in the development process of microwave imaging (MWI) systems. The main purpose of this paper was to design, fabricate, and experimentally verify the compact and dimensions-reduced H-slot antenna suitable for the new generation of multichannel MWI system for brain stroke detection. The slot antenna type was chosen based on the numerical study of three AEs available in the literature, i.e. bow tie, slot, and waveguide-based. The study was focused on the sensitivity of the antennae (change of magnitude and phase of S21) due to dielectric parameters change or type and diameter of inclusion in a head phantom representing a hemorrhagic (HEM) or ischemic (ISCH) stroke phantom, respectively. Further, the analysis of antenna radiation to lossy medium/air and its immunity against plane wave exposure was carried out. The H-slot antenna was fabricated and experimentally verified (measurements of reflection as well as transmission coefficients) using a liquid head phantom with inserted HEM stroke phantom (both prepared as a mixture of propylene glycol, water, and salt). The phantoms were filled inside the designed two-port test system. Numerical models were validated by comparing calculated and measured S-parameters. The sensitivity of the H-slot antenna to the presence of the HEM stroke phenomenon within the phantom of the head was also demonstrated. The main advantage of the proposed H-slot antenna is its small dimensions, easy, inexpensive, and repeatable fabrication as well as mechanical stability.