Synthetic Microwave Focusing Techniques for Medical Imaging: Fundamentals, Limitations, and Challenges

Synthetic microwave focusing methods have been widely adopted in qualitative medical imaging to detect and localize anomalies based on their electromagnetic scattering signatures. This paper discusses the principles, challenges, and limitations of synthetic microwave-focusing techniques in medical applications. It is shown that the various focusing techniques, including time reversal, confocal imaging, and delay-and-sum, are all based on the scalar solution of the electromagnetic scattering problem, assuming the imaged object, i.e., the tissue or object, is linear, reciprocal, and time-invariant. They all aim to generate a qualitative image, revealing any strong scatterer within the imaged domain. The differences among these techniques lie only in the assumptions made to derive the solution and create an image of the relevant tissue or object. To get a fast solution using limited computational resources, those methods assume the tissue is homogeneous and non-dispersive, and thus, a simplified far-field Green's function is used. Some focusing methods compensate for dispersive effects and attenuation in lossy tissues. Other approaches replace the simplified Green's function with more representative functions. While these focusing techniques offer benefits like speed and low computational requirements, they face significant ongoing challenges in real-life applications due to their oversimplified linear solutions to the complex problem of non-linear medical microwave imaging. This paper discusses these challenges and potential solutions.

Microwave Remote Sensing with Hybrid Quantum Receiver

Detecting a microwave signal that is emitted or reflected by distant targets is a powerful tool in fundamental science and industrial technology. Solid-state spins provide an opportunity to realize quantum-enhanced remote sensing under ambient conditions. However, the weak interaction between the free-space signal and atomic size sensor limits the sensitivity. This hinders the realization of practical quantum remote sensing. Here, we demonstrate active microwave remote sensing with a diamond-based hybrid quantum receiver by combining electromagnetic field localization at nanoscale with quantum spin manipulation. A method of differential spin refocusing (DSR) is developed to overcome the challenge of reducing the impact of inhomogeneities in spin-signal interaction, while the strength of interaction is enhanced by more than 3 orders with nanostructure. It improves the coherent interaction time of quantum receiver by 30-fold, substantially enhancing the sensitivity and stability. By detecting the reflected microwave with picotesla sensitivity, diamond remote sensing monitors the real-time status of a centimeter-sized target at 2 m distance. Our method is general to various solid-state spins. The results will expand the applications of solid-state spin quantum sensors in areas ranging from medical imaging to resource survey.

Microwave Technique for Linear Skull Fracture Detection-Simulation and Experimental Study Using Realistic Human Head Models

Microwave (MW) sensing is regarded as a promising technique for various medical monitoring and diagnostic applications due to its numerous advantages and the potential to be developed into a portable device for use outside hospital settings. The detection of skull fractures and the monitoring of their healing process would greatly benefit from a rapidly and frequently usable application that can be employed outside the hospital. This paper presents a simulation- and experiment-based study on skull fracture detection with the MW technique using realistic models for the first time. It also presents assessments on the most promising frequency ranges for skull fracture detection within the Industrial, Scientific and Medical (ISM) and ultrawideband (UWB) ranges. Evaluations are carried out with electromagnetic simulations using different head tissue layer models corresponding to different locations in the human head, as well as an anatomically realistic human head simulation model. The measurements are conducted with a real human skull combined with tissue phantoms developed in our laboratory. The comprehensive evaluations show that fractures cause clear differences in antenna and channel parameters (S11 and S21). The difference in S11 is 0.1-20 dB and in S21 is 0.1-30 dB, depending on the fracture width and location. Skull fractures with a less than 1 mm width can be detected with microwaves at different fracture locations. The detectability is frequency dependent. Power flow representations illustrate how fractures impact on the signal propagation at different frequencies. MW-based detection of skull fractures provides the possibility to (1) detect fractures using a safe and low-cost portable device, (2) monitor the healing-process of fractures, and (3) bring essential information for emerging portable MW-based diagnostic applications that can detect, e.g., strokes.

A novel textile-based UWB patch antenna for breast cancer imaging

Breast cancer is the second leading cause of death for women worldwide, and detecting cancer at an early stage increases the survival rate by 97%. In this study, a novel textile-based ultrawideband (UWB) microstrip patch antenna was designed and modeled to work in the 2-11.6 GHz frequency range and a simulation was used to test its performance in early breast cancer detection. The antenna was designed with an overall size of 31*31 mm2 using a denim substrate and 100% metal polyamide-based fabric with copper, silver, and nickel to provide comfort for the wearer. The designed antenna was tested in four numerical breast models. The models ranged from simple tumor-free to complex models with small tumors. The size, structure, and position of the tumor were modified to test the suggested ability of the antenna to detect cancers with different shapes, sizes, and positions. The specific absorption rate (SAR), return loss (S11), and voltage standing wave ratio (VSWR) were calculated for each model to measure the antenna performance. The simulation results showed that SAR values were between 1.6 and 2 W/g (10 g SAR) and were within the allowed range for medical applications. Additionally, the VSWR remained in an acceptable range from 1.15 to 2. Depending on the size and location of the tumor, the antenna return losses of the four models ranged from - 36 to - 18.5 dB. The effect of bending was tested to determine the flexibility. The antenna proved to be highly effective and capable of detecting small tumors with diameters of up to 2 mm.

Realistic 3D Phantoms for Validation of Microwave Sensing in Health Monitoring Applications

The development of new medical-monitoring applications requires precise modeling of effects on the human body as well as the simulation and the emulation of realistic scenarios and conditions. The first aim of this paper is to develop realistic and adjustable 3D human-body emulation platforms that could be used for evaluating emerging microwave-based medical monitoring/sensing applications such as the detection of brain tumors, strokes, and breast cancers, as well as for capsule endoscopy studies. New phantom recipes are developed for microwave ranges for phantom molds with realistic shapes. The second aim is to validate the feasibility and reliability of using the phantoms for practical scenarios with electromagnetic simulations using tissue-layer models and biomedical antennas. The third aim is to investigate the impact of the water temperature in the phantom-cooking phase on the dielectric properties of the stabilized phantom. The evaluations show that the dielectric properties of the developed phantoms correspond closely to those of real human tissue. The error in dielectric properties varies between 0.5-8%. In the practical-scenario simulations, the differences obtained with phantoms-based simulations in S21 parameters are 0.1-13 dB. However, the differences are smaller in the frequency ranges used for medical applications.

Clinical electromagnetic brain scanner

Stroke is a leading cause of death and disability worldwide, and early diagnosis and prompt medical intervention are thus crucial. Frequent monitoring of stroke patients is also essential to assess treatment efficacy and detect complications earlier. While computed tomography (CT) and magnetic resonance imaging (MRI) are commonly used for stroke diagnosis, they cannot be easily used onsite, nor for frequent monitoring purposes. To meet those requirements, an electromagnetic imaging (EMI) device, which is portable, non-invasive, and non-ionizing, has been developed. It uses a headset with an antenna array that irradiates the head with a safe low-frequency EM field and captures scattered fields to map the brain using a complementary set of physics-based and data-driven algorithms, enabling quasi-real-time detection, two-dimensional localization, and classification of strokes. This study reports clinical findings from the first time the device was used on stroke patients. The clinical results on 50 patients indicate achieving an overall accuracy of 98% in classification and 80% in two-dimensional quadrant localization. With its lightweight design and potential for use by a single para-medical staff at the point of care, the device can be used in intensive care units, emergency departments, and by paramedics for onsite diagnosis.

Glioblastoma Therapy: Past, Present and Future

Glioblastoma (GB) stands out as the most prevalent and lethal form of brain cancer. Although great efforts have been made by clinicians and researchers, no significant improvement in survival has been achieved since the Stupp protocol became the standard of care (SOC) in 2005. Despite multimodality treatments, recurrence is almost universal with survival rates under 2 years after diagnosis. Here, we discuss the recent progress in our understanding of GB pathophysiology, in particular, the importance of glioma stem cells (GSCs), the tumor microenvironment conditions, and epigenetic mechanisms involved in GB growth, aggressiveness and recurrence. The discussion on therapeutic strategies first covers the SOC treatment and targeted therapies that have been shown to interfere with different signaling pathways (pRB/CDK4/RB1/P16ink4, TP53/MDM2/P14arf, PI3k/Akt-PTEN, RAS/RAF/MEK, PARP) involved in GB tumorigenesis, pathophysiology, and treatment resistance acquisition. Below, we analyze several immunotherapeutic approaches (i.e., checkpoint inhibitors, vaccines, CAR-modified NK or T cells, oncolytic virotherapy) that have been used in an attempt to enhance the immune response against GB, and thereby avoid recidivism or increase survival of GB patients. Finally, we present treatment attempts made using nanotherapies (nanometric structures having active anti-GB agents such as antibodies, chemotherapeutic/anti-angiogenic drugs or sensitizers, radionuclides, and molecules that target GB cellular receptors or open the blood-brain barrier) and non-ionizing energies (laser interstitial thermal therapy, high/low intensity focused ultrasounds, photodynamic/sonodynamic therapies and electroporation). The aim of this review is to discuss the advances and limitations of the current therapies and to present novel approaches that are under development or following clinical trials.

Microwave and Antenna Systems in Medical Applications

The non-ionizing nature of microwave radiation and the low cost of microwave electronics offer innovative solutions for medical diagnosis, treatment, and health monitoring [...].

Dual-Planar Monopole Antenna-Based Remote Sensing System for Microwave Medical Applications

Neurodegenerative diseases (NDs) can be life threatening and have chronic impacts on patients and society. Timely diagnosis and treatment are imperative to prevent deterioration. Conventional imaging modalities, such as Computed Tomography (CT), Magnetic Resonance Imaging (MRI), and Positron Emission Tomography (PET), are expensive and not readily accessible to patients. Microwave sensing and imaging (MSI) systems are promising tools for monitoring pathological changes, namely the lateral ventricle enlargement associated with ND, in a non-invasive and convenient way. This paper presents a dual-planar monopole antenna-based remote sensing system for ND monitoring. First, planar monopole antennas were designed using the simulation software CST Studio Suite. The antenna analysis was carried out regarding the reflection coefficient, gain, radiation pattern, time domain characterization, E-field distribution, and Specific Absorption Rate (SAR). The designed antennas were then integrated with a controlling circuit as a remote sensing system. The system was experimentally validated on brain phantoms using a vector network analyzer and a laptop. The collected reflection coefficient data were processed using a radar-based imaging algorithm to reconstruct images indicating brain abnormality in ND. The results suggest that the system could serve as a low-cost and efficient tool for long-term monitoring of ND, particularly in clinics and care home scenarios.

Applied machine learning for stroke differentiation by electrical impedance tomography with realistic numerical models

Electrical impedance tomography (EIT) may have potential to overcome existing limitations in stroke differentiation, enabling low-cost, rapid, and mobile data collection. Combining bioimpedance measurement technologies such as EIT with machine learning classifiers to support decision-making can avoid commonly faced reconstruction challenges due to the nonlinear and ill-posed nature of EIT imaging. Therefore, in this work, we advance this field through a study integrating realistic head models with clinically relevant test scenarios, and a robust architecture consisting of nested cross-validation and principal component analysis. Specifically, realistic head models are designed which incorporate the highly conductive layers of cerebrospinal fluid in the subarachnoid space and ventricles. In total, 135 unique models are created to represent a large patient population, with normal, haemorrhagic, and ischemic brains. Simulated EIT voltage data generated from these models are used to assess the classification performance of support vector machines. Parameters explored include driving frequency, signal-to-noise ratio, kernel function, and composition of binary classes. Classifier accuracy at 60 dB signal-to-noise ratio, reported as mean and standard deviation, are (79.92% ± 10.82%) for lesion differentiation, (74.78% ± 3.79%) for lesion detection, (77.49% ± 15.90%) for bleed detection, and (60.31% ± 3.98%) for ischemia detection (after ruling out bleed). The results for each method were obtained with statistics from 3 independent runs with 17,280 observations, polynomial kernel functions, and feature reduction of 76% by PCA (from 208 to 50 features). While results of this study show promise for stroke differentiation using EIT data, our findings indicate that the achievable accuracy is highly dependent on the classification scenario and application-specific classifiers may be necessary to achieve acceptable accuracy.

Microwave bone fracture diagnosis using deep neural network

This paper studies the feasibility of a deep neural network (DNN) approach for bone fracture diagnosis based on the non-invasive propagation of radio frequency waves. In contrast to previous "semi-automated" techniques, where X-ray images were used as the network input, in this work, we use S-parameters profiles for DNN training to avoid labeling and data collection problems. Our designed network can simultaneously classify different complex fracture types (normal, transverse, oblique, and comminuted) and estimate the length of the cracks. The proposed system can be used as a portable device in ambulances, retirement houses, and low-income settings for fast preliminary diagnosis in emergency locations when expert radiologists are not available. Using accurate modeling of the human body as well as changing tissue diameters to emulate various anatomical regions, we have created our datasets. Our numerical results show that our design DNN is successfully trained without overfitting. Finally, for the validation of the numerical results, different sets of experiments have been done on the sheep femur bones covered by the liquid phantom. Experimental results demonstrate that fracture types can be correctly classified without using potentially harmful and ionizing X-rays.

Microwave Breast Sensing via Deep Learning for Tumor Spatial Localization by Probability Maps

BACKGROUND

microwave imaging (MWI) has emerged as a promising modality for breast cancer screening, offering cost-effective, rapid, safe and comfortable exams. However, the practical application of MWI for tumor detection and localization is hampered by its inherent low resolution and low detection capability.

METHODS

this study aims to generate an accurate tumor probability map directly from the scattering matrix. This direct conversion makes the probability map independent of specific image formation techniques and thus potentially complementary to any image formation technique. An approach based on a convolutional neural network (CNN) is used to convert the scattering matrix into a tumor probability map. The proposed deep learning model is trained using a large realistic numerical dataset of two-dimensional (2D) breast slices. The performance of the model is assessed through visual inspection and quantitative measures to assess the predictive quality at various levels of detail.

RESULTS

the results demonstrate a remarkably high accuracy (0.9995) in classifying profiles as healthy or diseased, and exhibit the model's ability to accurately locate the core of a single tumor (within 0.9 cm for most cases).

CONCLUSION

overall, this research demonstrates that an approach based on neural networks (NN) for direct conversion from scattering matrices to tumor probability maps holds promise in advancing state-of-the-art tumor detection algorithms in the MWI domain.

Evaluation of the Resolution in Inverse Scattering of Dielectric Cylinders for Medical Applications

The inverse scattering problem has numerous significant applications, including in geophysical explorations, medical imaging, and radar imaging. To achieve better performance of the imaging system, theoretical knowledge of the resolution of the algorithm is required for most of these applications. However, analytical investigations about the resolution presently feel inadequate. In order to estimate the achievable resolution, we address the point spread function (PSF) evaluation of the scattered field for a single frequency and the multi-view case both for the near and the far fields and the scalar case when the angular domain of the incident field and observation ranges is a round angle. Instead of the common free space condition, an inhomogeneous background medium, consisting of a homogeneous dielectric cylinder with a circular cross-section in free space, is assumed. In addition, since the exact evaluation of the PSF can only be accomplished numerically, an analytical approximation of the resolution is also considered. For the sake of its comparison, the truncated singular value decomposition (TSVD) algorithm can be used to implement the exact PSF. We show how the behavior of the singular values and the resolution change by varying the permittivity of the background medium. The usefulness of the theoretical discussion is demonstrated in localizing point-like scatterers within a dielectric cylinder, so mimicking a scenario that may occur in breast cancer imaging. Numerical results are provided to validate the analytical investigations.

Reducing Non-Through Body Energy Transfer in Microwave Imaging Systems

On-body antennas for use in microwave imaging (MI) systems can direct energy around the body instead of through the body, thus degrading the overall signal-to-noise ratio (SNR) of the system. This work introduces and quantifies the usage of modern metal-backed RF absorbing foam in conjunction with on-body antennas to dampen energy flowing around the body, using both simulations and experiments. A head imaging system is demonstrated herein but the principle can be applied to any part of the body including the torso or extremities. A computational model was simulated numerically using Ansys HFSS. A physical prototype in the form of a helmet with embedded antennas was built to compare simulations with measured data. Simulations and measurements demonstrate that usage of such metal-backed RF-absorbing foams can significantly reduce around-body coupling from Transmit (Tx) and Receive (Rx) antennas by approximately 10dB. Thus, the overall SNR of the MI system can be substantially improved using this low-cost and affordable method.

Miniaturized Dual Antiphase Patch Antenna Radiating into the Human Body at 2.4 GHz

An on-body antenna, comprised of two closely-spaced antiphase patch elements, for microwave imaging may provide enhanced signal penetration into the tissue. By further integrating a 180-degree on-chip power combiner with the dual antiphase patch antenna element, a low-profile miniaturized antenna, integrated into a single 18.5 mm x 10 mm x 1.6 mm circuit board assembly, is designed and evaluated both numerically and experimentally. This is the smallest on-body antenna known to the authors for the given frequency band. This linearly polarized antenna may potentially serve as a building block of a dense antenna array for prospective high-resolution microwave imaging. A 2.4 GHz band was chosen as the design target. The final antenna size was a compromise between the miniaturization, the SNR (Signal-to-Noise Ratio), and the targeted antenna bandwidth (2.3-2.5 GHz). The effect of surface waves (the secondary radiating components) was also factored in the design consideration, while maximizing the detected signals' SNR.

Review and Analysis of Tumour Detection and Image Quality Analysis in Experimental Breast Microwave Sensing

This review evaluates the methods used for image quality analysis and tumour detection in experimental breast microwave sensing (BMS), a developing technology being investigated for breast cancer detection. This article examines the methods used for image quality analysis and the estimated diagnostic performance of BMS for image-based and machine-learning tumour detection approaches. The majority of image analysis performed in BMS has been qualitative and existing quantitative image quality metrics aim to describe image contrast-other aspects of image quality have not been addressed. Image-based diagnostic sensitivities between 63 and 100% have been achieved in eleven trials, but only four articles have estimated the specificity of BMS. The estimates range from 20 to 65%, and do not demonstrate the clinical utility of the modality. Despite over two decades of research in BMS, significant challenges remain that limit the development of this modality as a clinical tool. The BMS community should utilize consistent image quality metric definitions and include image resolution, noise, and artifacts in their analyses. Future work should include more robust metrics, estimates of the diagnostic specificity of the modality, and machine-learning applications should be used with more diverse datasets and with robust methodologies to further enhance BMS as a viable clinical technique.

Diagnosis of a brain stroke using wideband microwave scattering

This paper presents a new computer-aided microwave monitoring system as a promising, portable and inexpensive tool to detect and localize brain stroke using a bank of a new wavelet-matched filters. The head is exposed to microwave radiation over the band from 1.1 to 3 GHz, and the backscattered signals at a hemi-elliptical array of 16 antenna elements surrounding the head are filtered to analyse the perturbation in the microwave signals from the brain. A novel technique is applied to remove the strong reflection from the air-skull interface as a way to estimate the target response and is compared with different techniques from literature to portray their role in the performance. The study results approve that the intensity and the distribution of wavelet energy and Shannon wavelet entropy in the filtered microwave signal, and the novel tool based on the distance between the wavelet energies at symmetric opposite antennas are promising candidate signatures for computer-aided detection and localization of a stroke.

Dielectric Characterization of Healthy Human Teeth from 0.5 to 18 GHz with an Open-Ended Coaxial Probe

Dental caries is a major oral health issue which compromises oral health, as it is the main cause of oral pain and tooth loss. Early caries detection is essential for effective clinical intervention. However, methods commonly employed for its diagnosis often fail to detect early caries lesions, which motivates the research for more effective diagnostic solutions. In this work, the relative permittivity of healthy permanent teeth, in caries-prone areas, was studied between 0.5 and 18 GHz. The reliability of such measurements is an important first step to, ultimately, evaluate the feasibility of a microwave device for caries detection. The open-ended coaxial probe technique was employed. Its performance showed to be compromised by the poor probe-tooth contact. We proposed a method based on applying coupling media to reduce this limitation. A decrease in the measured relative permittivity variability was observed when the space between the probe tip and tooth surface was filled by coupling media instead of air. The influence of the experimental conditions in the measurement result was found to be less than 5%. Measurements conducted in ex vivo teeth showed that the relative permittivity of the dental crown and root ranges between 10.0-11.0 and 8.0-9.5, respectively.

Application of the Model of Spots for Inverse Problems

This article proposes the application of a new mathematical model of spots for solving inverse problems using a learning method, which is similar to using deep learning. In general, the spots represent vague figures in abstract "information spaces" or crisp figures with a lack of information about their shapes. However, crisp figures are regarded as a special and limiting case of spots. A basic mathematical apparatus, based on L4 numbers, has been developed for the representation and processing of qualitative information of elementary spatial relations between spots. Moreover, we defined L4 vectors, L4 matrices, and mathematical operations on them. The developed apparatus can be used in Artificial Intelligence, in particular, for knowledge representation and for modeling qualitative reasoning and learning. Another application area is the solution of inverse problems by learning. For example, this can be applied to image reconstruction using ultrasound, X-ray, magnetic resonance, or radar scan data. The introduced apparatus was verified by solving problems of reconstruction of images, utilizing only qualitative data of its elementary relations with some scanning figures. This article also demonstrates the application of a spot-based inverse Radon algorithm for binary image reconstruction. In both cases, the spot-based algorithms have demonstrated an effective denoising property.

ROS production in response to high-power microwave pulses induces p53 activation and DNA damage in brain cells: Radiosensitivity and biological dosimetry evaluation

Background: Pulsed high-power microwave (HPM) has many applications and is constantly being researched to expand its uses in the future. As the number of applications grows, the biological effects and safety level of pulsed HPM become a serious issue, requiring further research. Objective: The brain is regarded as the most vulnerable organ to radiation, raising concerns about determining an acceptable level of exposure. The effect of nanosecond pulses and the mechanisms underlying HPM on the brain has not been studied. For the first time, we observed the effect of pulsed 3.5 GHz HPM on brain normal astrocytes and cancer U87 MG cells, as well as the likely mechanisms involved. Methods: To generate 3.5 GHz HPM, an axial virtual cathode oscillator was constructed on pulsed power generator "Chundoong". The cells were directly exposed to HPM (10, 25, 40, and 60) pulses (1 mJ/pulse), with each pulse delivered after 1 min of charging time to evaluate the dose dependent effects. Results: A strong electric field (∼23 kV/cm) of HPM irradiation primarily causes the production of reactive oxygen species (ROS), altering cell viability, mitochondrial activity, and cell death rates in U87 and astrocytes at certain dosages. The ROS generation in response to HPM exposure was primarily responsible for DNA damage and p53 activation. The hazardous dosage of 60 pulses is acknowledged as having damaging effects on brain normal cells. Interestingly, the particular 25 pulses exhibited therapeutic effects on U87 cells via p53, Bax, and Caspase-3 activation. Conclusion: HPM pulses induced apoptosis-related events such as ROS burst and increased oxidative DNA damage at higher dosages in normal cells and specific 25 pulses in cancer U87. These findings are useful to understand the physiological mechanisms driving HPM-induced cell death, as well as the safety threshold range for HPM exposure on normal cells and therapeutic effects on cancer U87. As HPM technology advances, we believe this study is timely and will benefit humanity and future research.

Monitoring of intracerebral hemorrhage with a linear microwave imaging algorithm

Intracerebral hemorrhage is a life-threatening condition where conventional imaging modalities such as CT and MRI are indispensable in diagnosing. Nevertheless, monitoring the evolution of intracerebral hemorrhage still poses a technological challenge. We consider continuous monitoring of intracerebral hemorrhage in this context and present a differential microwave imaging scheme based on a linearized inverse scattering. Our aim is to reconstruct non-anatomical maps that reveal the volumetric evolution of hemorrhage by using the differences between consecutive electric field measurements. This approach can potentially allow the monitoring of intracerebral hemorrhage in a real-time and cost-effective manner. Here, we devise an indicator function, which reveals the position, volumetric growth, and shrinkage of hemorrhage. Later, the method is numerically tested via a 3D anthropomorphic dielectric head model. Through several simulations performed for different locations of intracerebral hemorrhage, the indicator function-based technique is demonstrated to be capable of detecting the changes accurately. Finally, the robustness under noisy conditions is analyzed to assess the feasibility of the method. This analysis suggests that the method can be used to monitor the evolution of intracerebral hemorrhage in real-world scenarios.

An End-to-End Deep Learning Approach for Quantitative Microwave Breast Imaging in Real-Time Applications

(1) Background: In this paper, an artificial neural network approach for effective and real-time quantitative microwave breast imaging is proposed. It proposes some numerical analyses for the optimization of the network architecture and the improvement of recovery performance and processing time in the microwave breast imaging framework, which represents a fundamental preliminary step for future diagnostic applications. (2) Methods: The methodological analysis of the proposed approach is based on two main aspects: firstly, the definition and generation of a proper database adopted for the training of the neural networks and, secondly, the design and analysis of different neural network architectures. (3) Results: The methodology was tested in noisy numerical scenarios with different values of SNR showing good robustness against noise. The results seem very promising in comparison with conventional nonlinear inverse scattering approaches from a qualitative as well as a quantitative point of view. (4) Conclusion: The use of quantitative microwave imaging and neural networks can represent a valid alternative to (or completion of) modern conventional medical imaging techniques since it is cheaper, safer, fast, and quantitative, thus suitable to assist medical decisions.

Influence of Power Supply Ripple on Injection Locking of Magnetron with Frequency Pushing Effect

The influence of anode voltage ripple on injection locking of a magnetron with frequency pushing effect has been studied systematically. Theoretical analysis shows that, when power supply ripple and injection ratio are constant, frequency pushing effect will increase the magnetron’s locking bandwidth. Meanwhile, the locking bandwidth decreases with the increase of power supply ripple. Thus, to achieve injection locking, both power supply ripple and frequency pushing effect must be considered. The experiment results show that at injection ratio μ of 0.003, frequency pushing effect at 0.5, and power supply ripple increases from 0% to 1% and 2.5%, the locking bandwidth of magnetron decreases by 0.32 MHz, 2.12 MHz. With the amplitude of ripple increasing, the spectrum after injection locking deteriorates, and output amplitude reduces, which verifies the theoretical analysis. Considering anode voltage ripple and frequency pushing effect, the research results contribute to the realization of high-quality output of injection locked magnetrons.

Enhanced Machine Learning Approach for Accurate and Fast Resolution of Inverse Scattering Problem in Breast Cancer Detection

An improved machine learning approach is presented in this paper to guarantee the fast convergence of the Born Iterative Method, even in the presence of strong scatterers, by assuming a single operating frequency and a reduced number of antennas in the scattering setup. The initial estimation of the dielectric profile, provided by the Born Iterative Method, was processed by a specific convolutional neural network to improve the reconstruction using a fast machine learning approach. To ensure rapid convergence, a proper choice of the initial guess in terms of the minimum permittivity value over the entire domain was also made. Numerical validations on realistic breast phantoms were illustrated, demonstrating an average error of 2.4% and an accuracy greater than 96% for all considered tests, even when considering a single operating frequency and a reduced amount of training data.

A portable non-invasive microwave based head imaging system using compact metamaterial loaded 3D unidirectional antenna for stroke detection

A metamaterial (MTM) loaded compact three-dimensional antenna is presented for the portable, low-cost, non-invasive microwave head imaging system. The antenna has two slotted dipole elements with finite arrays of MTM unit cell and a folded parasitic patch that attains directional radiation patterns with 80% of fractional bandwidth. The operating frequency of the antenna is 1.95–4.5 GHz. The optimization of MTM unit cell is performed to increase the operational bandwidth, realized gain, and efficiency of the antenna within the frequency regime. It is also explored to improve radiation efficiency and gain when placed to head proximity. One-dimensional mathematical modelling is analyzed to precisely estimate the power distribution that validates the performance of the proposed antenna. To verify the imaging capability of the proposed system, an array of 9 antennas and a realistic three-dimensional tissue-emulating experimental semi-solid head phantom are fabricated and measured. The backscattered signal is collected from different antenna positions and processed by the updated Iterative Correction of Coherence Factor Delay-Multiply-and-Sum beamforming algorithm to reconstruct the hemorrhage images. The reconstructed images in simulation and experimental environment demonstrate the feasibility of the proposed system as a portable platform to successfully detect and locate the hemorrhages inside the brain.

Validation of an RF Image System for Real-Time Tracking Neurosurgical Tools

A radio frequency (RF)-based system for surgical navigation is presented. Surgical navigation technologies are widely used nowadays for aiding the surgical team with many interventions. However, the currently available options still pose considerable limitations, such as line-of-sight occlusion prevention or restricted materials and equipment allowance. In this work, we suggest a different approach based on a microwave broadband antenna system. We combine techniques from microwave medical imaging, which can overcome the current limitations in surgical navigation technologies, and we propose methods to develop RF-based systems for real-time tracking neurosurgical tools. The design of the RF system to perform the measurements is shown and discussed, and two methods (Multiply and Sum and Delay Multiply and Sum) for building the medical images are analyzed. From these measurements, a surgical tool's position tracking system is developed and experimentally assessed in an emulated surgical scenario. The reported results are coherent with other approaches found in the literature, while overcoming their main practical limitations. The discussion of the results discloses some hints on the validity of the system, the optimal configurations depending on the requirements, and the possibilities for future enhancements.

Microwaves as Diagnostic Tool for Pituitary Tumors: Preliminary Investigations

To date, tumors, the second cause of death worldwide, are a modern medicine plight. The development of rapid, cost-effective and reliable prevention and diagnostics tools is mandatory to support clinicians and ensure patients’ adequate intervention. Pituitary tumors are a class of neoplasm, which calls for suitable and ad hoc diagnostic tools. Recently, microwaves have gained interest as a non-ionizing, non-invasive valuable diagnostic approach for identifying pathologic tissues according to their dielectric properties. This work deals with the preliminary investigation of the feasibility of using microwaves to diagnose pituitary tumors. In particular, it focuses on benign tumors of the adenohypophysis, e.g., the pituitary adenomas. It is assumed to access the region of interest of the pituitary region by following a trans-sphenoidal approach. The problem was modeled by developing an equivalent transmission line model of the multi-layered, lossy tissues (front bone of sphenoid sinuses, air in the sinuses, posterior bone of sphenoid sinuses, the pituitary gland and the tumor). The forward problem was developed to investigate the transmission coefficient for identifying the most favorable propagation conditions. Then, it was analyzed if, by the solution of an inverse problem, it is possible to reconstruct the permittivity and electrical conductivity profiles and identify the tumor presence. The results are promising since a maximum reconstruction error of 8% is found, in the worst case, thus paving the way for the use of microwaves for the diagnosis of pituitary tumors.

Calibrated Frequency-Division Distorted Born Iterative Tomography for Real-Life Head Imaging

The clinical use of microwave tomography (MT) requires addressing the significant mismatch between simulated environment, which is used in the forward solver, and real-life system. To alleviate this mismatch, a calibrated tomography, which uses two homogeneous calibration phantoms and a modified distorted Born iterative method (DBIM), is presented. The two phantoms are used to derive a linear model that matches the forward solver to real-life measurements. Moreover, experimental observations indicate that signal quality at different frequencies varies between different antennas due to inevitably inconsistent manufacturing tolerance and variances in radio-frequency chains. An optimum frequency, at which the simulated and measured signals of the antenna present maximum similarity when irradiating the calibrated phantoms, is thus calculated for each antenna. A frequency-division DBIM (FD-DBIM), in which different antennas in the array transmit their corresponding optimum frequencies, is subsequently developed. A clinical brain scanner is then used to assess performance of the algorithm in lab and healthy volunteers' tests. The linear calibration model is first used to calibrate the measured data. After that FD-DBIM is used to solve the problem and map the dielectric properties of the imaged domain. The simulated and experimental results confirm validity of the presented approach and its superiority to other tomographic method.

Microwave Imaging for Early Breast Cancer Detection: Current State, Challenges, and Future Directions

Breast cancer is the most commonly diagnosed cancer type and is the leading cause of cancer-related death among females worldwide. Breast screening and early detection are currently the most successful approaches for the management and treatment of this disease. Several imaging modalities are currently utilized for detecting breast cancer, of which microwave imaging (MWI) is gaining quite a lot of attention as a promising diagnostic tool for early breast cancer detection. MWI is a noninvasive, relatively inexpensive, fast, convenient, and safe screening tool. The purpose of this paper is to provide an up-to-date survey of the principles, developments, and current research status of MWI for breast cancer detection. This paper is structured into two sections; the first is an overview of current MWI techniques used for detecting breast cancer, followed by an explanation of the working principle behind MWI and its various types, namely, microwave tomography and radar-based imaging. In the second section, a review of the initial experiments along with more recent studies on the use of MWI for breast cancer detection is presented. Furthermore, the paper summarizes the challenges facing MWI as a breast cancer detection tool and provides future research directions. On the whole, MWI has proven its potential as a screening tool for breast cancer detection, both as a standalone or complementary technique. However, there are a few challenges that need to be addressed to unlock the full potential of this imaging modality and translate it to clinical settings.

A Versatile and Shelf-Stable Dielectric Coupling Medium for Microwave Imaging

OBJECTIVE

To develop a new class of emulsions using a protein-based emulsifier as the coupling fluid for microwave imaging systems.

METHODS

In this paper, we provide a theoretical basis for engineering shelf-stable dielectric fluids, a step-by-step formulation method, and measurements of complex dielectric properties in the frequency range of 0.5-3 GHz, which can be applicable for many of the recent microwave imaging systems.

RESULTS

This medium was primarily designed for long-term stability while providing a controllable range of complex dielectric permittivities given different fractions of its constituents. Consequently, this emulsion shows dielectric stability in open air throughout a 7-day experiment and temperature insensitivity over the range of 0 to 60 Celsius degree.

CONCLUSIONS

This control over dielectric permittivity enables formulations that tune the background-to-target contrast to the linearizable regime of iterative inverse scattering algorithms. Accordingly, the emulsion conductivity can also be controlled and reduced to maintain the required signal-to-noise ratio within the dynamic range of the imaging system. The new formulation overcomes the practical challenges of engineering coupling fluids for microwave imaging systems, e.g., temporal stability, non-toxic, low sensitivity to temperature variation, and easy formulation from readily available and inexpensive materials.

SIGNIFICANCE

The achieved properties associated with this new fluid are of particular benefit to microwave imaging systems used in thermal therapy monitoring.

An Optimization-Based Approach to Radar Image Reconstruction in Breast Microwave Sensing

Breast microwave sensing (BMS) has been studied as a potential technique for cancer detection due to the observed microwave properties of malignant and healthy breast tissues. This work presents a novel radar-based image reconstruction algorithm for use in BMS that reframes the radar image reconstruction process as an optimization problem. A gradient descent optimizer was used to create an optimization-based radar reconstruction (ORR) algorithm. Two hundred scans of MRI-derived breast phantoms were performed with a preclinical BMS system. These scans were reconstructed using the ORR, delay-and-sum (DAS), and delay-multiply-and-sum (DMAS) beamformers. The ORR was observed to improve both sensitivity and specificity compared to DAS and DMAS. The estimated sensitivity and specificity of the DAS beamformer were 19% and 44%, respectively, while for ORR, they were 27% and 56%, representing a relative increase of 42% and 27%. The DAS reconstructions also exhibited a hot-spot image artifact, where a localized region of high intensity that did not correspond to any physical phantom feature would be present in an image. This artifact appeared like a tumour response within the image and contributed to the lower specificity of the DAS beamformer. This artifact was not observed in the ORR reconstructions. This work demonstrates the potential of an optimization-based conceptualization of the radar image reconstruction problem in BMS. The ORR algorithm implemented in this work showed improved diagnostic performance and fewer image artifacts compared to the widely employed DAS algorithm.

Controlled Measurement Setup for Ultra-Wideband Dielectric Modeling of Muscle Tissue in 20-45 °C Temperature Range

In order to design electromagnetic applicators for diagnostic and therapeutic applications, an adequate dielectric tissue model is required. In addition, tissue temperature will heavily influence the dielectric properties and the dielectric model should, thus, be extended to incorporate this temperature dependence. Thus, this work has a dual purpose. Given the influence of temperature, dehydration, and probe-to-tissue contact pressure on dielectric measurements, this work will initially present the first setup to actively control and monitor the temperature of the sample, the dehydration rate of the investigated sample, and the applied probe-to-tissue contact pressure. Secondly, this work measured the dielectric properties of porcine muscle in the 0.5-40 GHz frequency range for temperatures from 20 °C to 45 °C. Following measurements, a single-pole Cole-Cole model is presented, in which the five Cole-Cole parameters (ϵ∞, σs, Δϵ, τ, and α) are given by a first order polynomial as function of tissue temperature. The dielectric model closely agrees with the limited dielectric models known in literature for muscle tissue at 37 °C, which makes it suited for the design of in vivo applicators. Furthermore, the dielectric data at 41-45 °C is of great importance for the design of hyperthermia applicators.

Microwave power penetration enhancement inside an inhomogeneous human head

The penetration of microwave power inside a human head model is improved by employing a dielectric loaded rectangular waveguide as the transmission source. A multi-layer reflection model is investigated to evaluate the combined material characteristics of different lossy human head tissues at 2.45 GHz. A waveguide loaded with a calculated permittivity of 3.62 is shown to maximise the microwave power penetration at the desired frequency. A Quartz (SiO₂) loaded rectangular waveguide fed by a microstrip antenna is designed to validate the power penetration improvement inside an inhomogeneous human head phantom. A measured 1.33 dB power penetration increment is observed for the dielectric loaded waveguide over a standard rectangular waveguide at 50 mm inside the head, with an 81.9% reduction in the size of the transmission source.

Application of a Neural Network Classifier to Radiofrequency-Based Osteopenia/Osteoporosis Screening

This preliminary study reports application of a neural network classifier to the processing of previously collected data on low power radiofrequency propagation through the wrist with the goal to detect osteoporotic/osteopenic conditions. The data set used includes 67 subjects (23-94 years old, 50 females, 17 males, 27 osteoporotic/osteopenic, 40 healthy). We process the entire spectrum of the propagation coefficient through the wrist from 30 kHz to 2 GHz, with 201 sampling points in total. We found that the dichotomic diagnostic test of raw non-normalized radiofrequency data performed with the trained neural network approaches 90% specificity and ~70% sensitivity. These results are obtained without inclusion of any additional clinical risk factors. They justify that the radio transmission data are usable on their own as a predictor of bone density. With the inclusion of additional clinical risk factors, both specificity and sensitivity improve to 95% and 76% respectively. Our approach correlates well with the available DXA measurements and has the potential for screening patients at risk for fragility fractures, given the ease of implementation and low costs associated with both the technique and the equipment.Clinical Relevance- Dichotomic diagnostic test of raw non-normalized radiofrequency data performed with the trained neural network approaches 90% specificity and ~70% sensitivity. With the inclusion of other clinical risk factors, specificity and sensitivity increase to 95% and 76% respectively.

Application of a Neural Network Classifier to Radiofrequency-Based Osteopenia/Osteoporosis Screening

Objective: There is an unmet need for quick, physically small, and cost-effective office-based techniques that can measure bone properties without the use of ionizing radiation. Methods: The present study reports the application of a neural network classifier to the processing of previously collected data on very-low-power radiofrequency propagation through the wrist to detect osteoporotic/osteopenic conditions. Our approach categorizes the data obtained for two dichotomic groups. Group 1 included 27 osteoporotic/osteopenic subjects with low Bone Mineral Density (BMD), characterized by a Dual X-Ray Absorptiometry (DXA) T-score below – 1, measured within one year. Group 2 included 40 healthy and mostly young subjects without major clinical risk factors such as a (family) history of bone fracture. We process the complex radiofrequency spectrum from 30 kHz to 2 GHz. Instead of averaging data for both wrists, we process them independently along with the wrist circumference and then combine the results, which greatly increases the sensitivity. Measurements along with data processing require less than 1 min. Results: For the two dichotomic groups identified above, the neural network classifier of the radiofrequency spectrum reports a sensitivity of 83% and a specificity of 94%. Significance: These results are obtained without including any additional clinical risk factors. They justify that the radio transmission data are usable on their own as a predictor of bone density. This approach has the potential for screening patients at risk for fragility fractures in the office, given the ease of implementation, small device size, and low costs associated with both the technique and the equipment.

Evaluation of non-thermal effect of microwave radiation and its mode of action in bacterial cell inactivation

A growing body of literature has recognized the non-thermal effect of pulsed microwave radiation (PMR) on bacterial systems. However, its mode of action in deactivating bacteria has not yet been extensively investigated. Nevertheless, it is highly important to advance the applications of PMR from simple to complex biological systems. In this study, we first optimized the conditions of the PMR device and we assessed the results by simulations, using ANSYS HFSS (High Frequency Structure Simulator) and a 3D particle-in-cell code for the electron behavior, to provide a better overview of the bacterial cell exposure to microwave radiation. To determine the sensitivity of PMR, Escherichia coli and Staphylococcus aureus cultures were exposed to PMR (pulse duration: 60 ns, peak frequency: 3.5 GHz) with power density of 17 kW/cm² at the free space of sample position, which would induce electric field of 8.0 kV/cm inside the PBS solution of falcon tube in this experiment at 25 °C. At various discharges (D) of microwaves, the colony forming unit curves were analyzed. The highest ratios of viable count reductions were observed when the doses were increased from 20D to 80D, which resulted in an approximate 6 log reduction in E. coli and 4 log reduction in S. aureus. Moreover, scanning electron microscopy also revealed surface damage in both bacterial strains after PMR exposure. The bacterial inactivation was attributed to the deactivation of oxidation-regulating genes and DNA damage.

Nanomaterials responding to microwaves: an emerging field for imaging and therapy

In recent years, new microwave-based imaging, sensing and hyperthermia applications have emerged in the field of diagnostics and therapy. For diagnosis, this technology involves the application of low power microwaves, utilising contrast between the relative permittivity of tissues to identify pathologies. This contrast can be further enhanced through the implementation of nanomaterials. For therapy, this technology can be applied in tissues either through hyperthermia, which can help anti-cancer drug tumour penetration or as ablation to destroy malignant tissues. Nanomaterials can absorb electromagnetic radiation and can enhance the microwave hyperthermic effect. In this review we aim to introduce this area of renewed interest and provide insights into current developments in its technologies and companion nanoparticles, as well as presenting an overview of applications for diagnosis and therapy.

Flexible Electromagnetic Cap for Three-Dimensional Electromagnetic Head Imaging

The timely treatment is the crucial element for the survival of patients with brain stroke. Thus, a fast, cost-effective, and portable device is needed for the early and on-the-spot diagnosis of stroke patients. A 3D electromagnetic head imaging system for rapid brain stroke diagnosis with a wearable and lightweight platform is presented. The platform comprises a custom-built flexible cap with a 24-element planar antenna array, and a flexible matching medium layer. The custom-built cap is made out of an engineered polymer-ceramic composite substrate of RTV silicone rubber and aluminum oxide (Al₂O₃) for enhanced dielectric properties and mechanical flexibility and robustness. The array is arranged into two elliptical rings that are entirely incorporated into the flexible cap. The employed antenna elements within the system are compact with low SAR values over the utilized frequency range of 0.9-2.5 GHz. Moreover, a flexible matching medium layer is introduced on the front of the apertures of the antenna array to enhance the impedance matching with the skin. The detection capability of the system is experimentally verified on 3D realistic head phantoms at multiple imaging scenarios and different types of strokes. The reconstructed 3D and 2D multi-slice images using the beamforming and polar sensitivity encoding (PSE) image processing algorithms indicate the applicability and potential of the system for onsite brain imaging.

Pulsed 3.5 GHz high power microwaves irradiation on physiological solution and their biological evaluation on human cell lines

Microwave (MW) radiation is increasingly being used for several biological applications. Many investigations have focused on understanding the potential influences of pulsed MW irradiation on biological solutions. The current study aimed to investigate the effects of 3.5 GHz pulsed MW radiation-irradiated liquid solutions on the survival of human cancer and normal cells. Different physiological solutions such as phosphate buffer saline, deionized water, and Dulbecco's modified Eagle medium (DMEM) for cell culture growth were irradiated with pulsed MW radiation (45 shots with the energy of 1 mJ/shot). We then evaluated physiological effects such as cell viability, metabolic activity, mitochondrial membrane potential, cell cycle, and cell death in cells treated with MW-irradiated biological solutions. As MW irradiation with power density ~ 12 kW/cm2 mainly induces reactive nitrogen oxygen species in deionized water, it altered the cell cycle, membrane potential, and cell death rates in U373MG cells due to its high electric field ~ 11 kV/cm in water. Interestingly, MW-irradiated cell culture medium and phosphate-buffered saline did not alter the cellular viability and metabolic energy of cancer and normal cells without affecting the expression of genes responsible for cell death. Taken together, MW-irradiated water can alter cellular physiology noticeably, whereas irradiated media and buffered saline solutions induce negligible or irrelevant changes that do not affect cellular health.

Development of a Solid and Flexible Matching Medium for Microwave Medical Diagnostic Systems

This paper reports the development of a new composite material as a matching medium for medical microwave diagnostic systems, where maximizing the microwave energy that penetrates the interrogated tissue is critical for improving the quality of the diagnostic images. The proposed material has several advantages over what is commonly used in microwave diagnostic systems: it is semi-flexible and rigid, and it can maximize microwave energy coupling by matching the tissue’s dielectric constant without introducing high loss. The developed matching medium is a mirocomposite of barium titanate filler in polydimethylsiloxane (PDMS) in different weight-based mixing ratios. Dielectric properties of the material are measured using a Keysight open-ended coaxial slim probe from 0.5 to 10 GHz. To avoid systematic errors, a full dielectric properties calibration is performed before measurements of sample materials. Furthermore, the repeatability of the measurements and the homogeneity of the sample of interest are considered. Finally, to evaluate the proposed matching medium, its impact on a printed monopole antenna is studied. We demonstrate that the permittivity of the investigated mixtures can be increased in a controlled manner to reach values that have been previously shown to be optimal for medical microwave imaging (MWI) such as stroke and breast cancer diagnostic applications. As a result, the material is a good candidate for supporting antenna arrays designed for portable MWI scanners in applications such as stroke detection.

A Simulation-Based Methodology of Developing 3D Printed Anthropomorphic Phantoms for Microwave Imaging Systems

This work is devoted to the development and manufacturing of realistic benchmark phantoms to evaluate the performance of microwave imaging devices. The 3D (3 dimensional) printed phantoms contain several cavities, designed to be filled with liquid solutions that mimic biological tissues in terms of complex permittivity over a wide frequency range. Numerical versions (stereolithography (STL) format files) of these phantoms were used to perform simulations to investigate experimental parameters. The purpose of this paper is two-fold. First, a general methodology for the development of a biological phantom is presented. Second, this approach is applied to the particular case of the experimental device developed by the Department of Electronics and Telecommunications at Politecnico di Torino (POLITO) that currently uses a homogeneous version of the head phantom considered in this paper. Numerical versions of the introduced inhomogeneous head phantoms were used to evaluate the effect of various parameters related to their development, such as the permittivity of the equivalent biological tissue, coupling medium, thickness and nature of the phantom walls, and number of compartments. To shed light on the effects of blood circulation on the recognition of a randomly shaped stroke, a numerical brain model including blood vessels was considered.

Flexible Electromagnetic Cap for Head Imaging

A wideband wearable electromagnetic (EM) head imaging system for brain stroke detection is presented. The proposed system aims at overcoming the challenges of size, rigidity, and complex structures of existing systems. The proposed system is built into a light-weight and compact imaging platform, which integrates a 16-element antenna array into a highly flexible custom-made wearable cap made of a cost-effective and robust room-temperature-vulcanizing (RTV) silicone. The system mitigates the mismatch between the skin and antenna array by introducing a flexible high-permittivity matching layer. The utilized compact antenna demonstrates wideband operational frequency over 0.6-2.5 GHz with a low signal distortion, safe values of SAR, and unidirectional radiations. The system is experimentally validated on realistic head phantoms. The polar sensitivity encoding (PSE) image processing algorithm is utilized to generate 2D images of different testing scenarios. The obtained images of a stroke-like target inside the head phantoms demonstrate the merits and feasibility of the system for preclinical trials.

Localization of Small Anomalies via the Orthogonality Sampling Method from Scattering Parameters

We investigate the application of the orthogonality sampling method (OSM) in microwave imaging for a fast localization of small anomalies from measured scattering parameters. For this purpose, we design an indicator function of OSM defined on a Lebesgue space to test the orthogonality relation between the Hankel function and the scattering parameters. This is based on an application of the Born approximation and the integral equation formula for scattering parameters in the presence of a small anomaly. We then prove that the indicator function consists of a combination of an infinite series of Bessel functions of integer order, an antenna configuration, and material properties. Simulation results with synthetic data are presented to show the feasibility and limitations of designed OSM.

Numerical Sensitivity Analysis for Dielectric Characterization of Biological Samples by Open-Ended Probe Technique

Dielectric characterization of biological tissues has become a fundamental aspect of the design of medical treatments based on electromagnetic energy delivery and their pre-treatment planning. Among several measuring techniques proposed in the literature, broadband and minimally-invasive open-ended probe measurements are best-suited for biological tissues. However, several challenges related to measurement accuracy arise when dealing with biological tissues in both ex vivo and in vivo scenarios such as very constrained set-ups in terms of limited sample size and probe positioning. By means of the Finite Integration Technique in the CST Studio Suite^® software, the numerical accuracy of the reconstruction of the complex permittivity of a high water-content tissue such as liver and a low water-content tissue such as fat is evaluated for different sample dimensions, different location of the probe, and considering the influence of the background environment. It is found that for high water-content tissues, the insertion depth of the probe into the sample is the most critical parameter on the accuracy of the reconstruction. Whereas when low water-content tissues are measured, the probe could be simply placed in contact with the surface of the sample but a deeper and wider sample is required to mitigate biasing effects from the background environment. The numerical analysis proves to be a valid tool to assess the suitability of a measurement set-up for a target accuracy threshold.

PySpark-Based Optimization of Microwave Image Reconstruction Algorithm for Head Imaging Big Data on High-Performance Computing and Google Cloud Platform

For processing large-scale medical imaging data, adopting high-performance computing and cloud-based resources are getting attention rapidly. Due to its low–cost and non-invasive nature, microwave technology is being investigated for breast and brain imaging. Microwave imaging via space-time algorithm and its extended versions are commonly used, as it provides high-quality images. However, due to intensive computation and sequential execution, these algorithms are not capable of producing images in an acceptable time. In this paper, a parallel microwave image reconstruction algorithm based on Apache Spark on high-performance computing and Google Cloud Platform is proposed. The input data is first converted to a resilient distributed data set and then distributed to multiple nodes on a cluster. The subset of pixel data is calculated in parallel on these nodes, and the results are retrieved to a master node for image reconstruction. Using Apache Spark, the performance of the parallel microwave image reconstruction algorithm is evaluated on high-performance computing and Google Cloud Platform, which shows an average speed increase of 28.56 times on four homogeneous computing nodes. Experimental results revealed that the proposed parallel microwave image reconstruction algorithm fully inherits the parallelism, resulting in fast reconstruction of images from radio frequency sensor’s data. This paper also illustrates that the proposed algorithm is generalized and can be deployed on any master-slave architecture.

Concept of a Radiofrequency Device for Osteopenia/Osteoporosis Screening

Osteoporosis represents a major health problem, resulting in substantial increases in health care costs. There is an unmet need for a cost-effective technique that can measure bone properties without the use of ionizing radiation. The present study reports design, construction, and testing of a safe, and easy to use radiofrequency device to detect osteoporotic bone conditions. The device uses novel on-body antennas contacting the human wrist under an applied, operator-controlled pressure. For the dichotomous diagnostic test, we selected 60 study participants (23-94 years old, 48 female, 12 male) who could be positively differentiated between healthy and osteopenic/osteoporotic states. The band-limited integral of the transmission coefficient averaged for both wrists, multiplied by age, and divided by BMI has been used as an index. For a 100 MHz frequency band centered about 890-920 MHz, the maximum Youden's J index is 81.5%. Both the sensitivity and specificity simultaneously reach 87% given the calibration device threshold tolerance of ±3%. Our approach correlates well with the available DXA measurements and has the potential for screening patients at risk for fragility fractures, given the ease of implementation and low costs associated with both the technique and the equipment. The inclusion of radiofrequency transmission data does add supplementary useful information to the available clinical risk factors.

Experimental Validation of Microwave Tomographywith the DBIM-TwIST Algorithm for Brain StrokeDetection and Classification

We present an initial experimental validation of a microwave tomography (MWT) prototypefor brain stroke detection and classification using the distorted Born iterative method, two-stepiterative shrinkage thresholding (DBIM-TwIST) algorithm. The validation study consists of firstpreparing and characterizing gel phantoms which mimic the structure and the dielectric propertiesof a simplified brain model with a haemorrhagic or ischemic stroke target. Then, we measure theS-parameters of the phantoms in our experimental prototype and process the scattered signals from 0.5to 2.5 GHz using the DBIM-TwIST algorithm to estimate the dielectric properties of the reconstructiondomain. Our results demonstrate that we are able to detect the stroke target in scenarios where theinitial guess of the inverse problem is only an approximation of the true experimental phantom.Moreover, the prototype can differentiate between haemorrhagic and ischemic strokes based on theestimation of their dielectric properties.

Dielectric Properties of Normal and Metastatic Lymph Nodes Ex Vivo From Lung Cancer Surgeries

The dielectric properties of normal and tumor human tissues have been widely reported in recent years. However, the dielectric properties of intrathoracic lymph nodes (LNs) have not been reported. In this communication, we measured the dielectric properties (i.e., permittivity and conductivity) of ex vivo intrathoracic LNs obtained from lung cancer surgeries. Results show that the permittivity and conductivity of metastatic LNs are higher than those of normal LNs over the frequency range of 1 MHz-4 GHz. Statistically significant differences are observed at single specific frequencies (64, 128, 298, 433, and 915 MHz and 2.45 GHz). Our study provides the basic data to support future-related research and fills the research gap on the dielectric properties of LNs in the lungs. Bioelectromagnetics. 2020;41:148-155. © 2020 Bioelectromagnetics Society.