A Wearable Microwave Antenna Array for Time-Domain Breast Tumor Screening

Reducing soft tissue artefacts through projection of markers and microwave imaging: An exploratory study

Soft tissue artefacts (STA) are widely considered the most critical source of error in skin-mounted marker-based biomechanics, negatively impacting the clinical usability of skin-mounted marker-based data. Amongst the numerous solutions proposed to ameliorate STA, incorporating true bone movement-acquired using adaptive constraints, projection of markers, or various imaging modalities-has been reported to improve kinematic accuracy. However, efficacy of these proposed solutions reduces for different investigated motions and participants. In this study, we propose two novel marker projection schemes, wherein a cluster of markers are projected onto the bone surface during motion. Additionally, we investigate the feasibility of applying a novel, safe and cost-effective imaging modality-microwave imaging-to detect the location of the bone from the skin surface. Our results indicate that the novel marker projection schemes reduce kinematic errors significantly (by 50%) and improve the quality of computed kinematics (95% correlation to true bone movement). In addition, our results show that microwave imaging was able to detect the bone from the skin surface in both male and female anatomical models of varying body mass index scores and poses. We believe our findings underscore the generalisability and applicability of our proposed solution to reduce STA.

Metamaterial-based Artificial magnetic conductor for efficient breast cancer diagnosis using a low-cost antenna array

Breast cancer is the most common malignancy in women globally, stemming from gene mutations that prompt irregular cellular growth and subsequent tumor development. Early-stage detection of cancer cells results in a remarkable 99% survival rate. This research presents a microwave imaging technique for the non-invasive identification of tumors in the initial stages within the women's breast. A low-cost antenna array with an Artificial Magnetic Conductor (AMC) is proposed, featuring a compact structure size of 37.2 × 37.2 mm2 . The AMC, a metamaterial, acts as a reflective surface to enhance frequency selectivity, specifically at 8.48 GHz. The maximum gains reached 9.35 dBi in simulated results and 10.51 dBi in measured results. The fabricated antenna validates the simulated findings, and its operational efficiency has undergone experimental validation. Moreover, fidelity factors in face-to-face (FtF) and side-by-side (SbS) scenarios are delineated. The antenna, operating as a transceiver, is applied to a modeled breast phantom across five distinct cases for numerical simulations pertaining to cancer cell detection applications. The outcomes of this research bear considerable implications for advancing early-stage breast cancer detection methodologies.

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.

Design and experimental validation of a metamaterial-based sensor for microwave imaging in breast, lung, and brain cancer detection

This study proposes an innovative geometry of a microstrip sensor for high-resolution microwave imaging (MWI). The main intended application of the sensor is early detection of breast, lung, and brain cancer. The proposed design consists of a microstrip patch antenna fed by a coplanar waveguide with a metamaterial (MTM) layer-based lens implemented on the back side, and an artificial magnetic conductor (AMC) realized on as a separate layer. The analysis of the AMC's permeability and permittivity demonstrate that the structure exhibits negative epsilon (ENG) qualities near the antenna resonance point. In addition, reflectivity, transmittance, and absorption are also studied. The sensor prototype has been manufactures using the FR4 laminate. Excellent electrical and field characteristics of the structure are confirmed through experimental validation. At the resonance frequency of 4.56 GHz, the realized gain reaches 8.5 dBi, with 3.8 dBi gain enhancement contributed by the AMC. The suitability of the presented sensor for detecting brain tumors, lung cancer, and breast cancer has been corroborated through extensive simulation-based experiments performed using the MWI system model, which employs four copies of the proposed sensor, as well as the breast, lung, and brain phantoms. As demonstrated, the directional radiation pattern and enhanced gain of the sensor enable precise tumor size discrimination. The proposed sensor offers competitive performance in comparison the state-of-the-art sensors described in the recent literature, especially with respect to as gain, pattern directivity, and impedance matching, all being critical for MWI.

Review of Microwave Near-Field Sensing and Imaging Devices in Medical Applications

Microwaves can safely and non-destructively illuminate and penetrate dielectric materials, making them an attractive solution for various medical tasks, including detection, diagnosis, classification, and monitoring. Their inherent electromagnetic properties, portability, cost-effectiveness, and the growth in computing capabilities have encouraged the development of numerous microwave sensing and imaging systems in the medical field, with the potential to complement or even replace current gold-standard methods. This review aims to provide a comprehensive update on the latest advances in medical applications of microwaves, particularly focusing on the near-field ones working within the 1-15 GHz frequency range. It specifically examines significant strides in the development of clinical devices for brain stroke diagnosis and classification, breast cancer screening, and continuous blood glucose monitoring. The technical implementation and algorithmic aspects of prototypes and devices are discussed in detail, including the transceiver systems, radiating elements (such as antennas and sensors), and the imaging algorithms. Additionally, it provides an overview of other promising cutting-edge microwave medical applications, such as knee injuries and colon polyps detection, torso scanning and image-based monitoring of thermal therapy intervention. Finally, the review discusses the challenges of achieving clinical engagement with microwave-based technologies and explores future perspectives.

Dielectric Characterization of Ex-Vivo Breast Tissues: Differentiation of Tumor Types through Permittivity Measurements

Early analysis and diagnosis of breast tumors is essential for either quickly launching a treatment or for seeing the evolution of patients who, for instance, have already undergone chemotherapy treatment. Once tissues are excised, histological analysis is the most frequent tool used to characterize benign or malignant tumors. Dielectric microwave spectroscopy makes use of an open-ended coaxial probe in the 1-8 GHz frequency range to quickly identify the type of tumor (ductal carcinoma, lobular carcinoma, mucinous carcinoma and fibroadenoma). The experiment was undertaken with data from 70 patients who had already undergone chemotherapy treatment, which helped to electrically map the histological tissues with their electric permittivity. Thus, the variations in the permittivity of different types of tumors reveal distinctive patterns: benign tumors have permittivity values lower than 35, while malignant ones range between 40 and 60. For example, at a frequency of 2 GHz, the measured permittivity was 45.6 for ductal carcinoma, 33.1 for lobular carcinoma, 59.5 for mucinous carcinoma, and 27.6 for benign tumors. This differentiation remains consistent in a frequency range of 1 to 4.5 GHz. These results highlight the effectiveness of these measurements in the classification of breast tumors, providing a valuable tool for quick and accurate diagnosis and effective treatment.

Interconnect for Dense Electronically Scanned Antenna Array Using High-Speed Vertical Connector

We present the design and the performance evaluation of a new interconnect for large-scale densely packed electronically scanned antenna arrays that utilize a high-speed digital board-to-board vertical connector. The application targets microwave tissue, imaging in the frequency range from 3 GHz to 8 GHz. The tissue-imaging arrays consist of hundreds of active antenna elements, which require low-reflection, low-loss, and low-crosstalk connections to their respective receiving and transmitting circuits. The small antenna size and the high array density preclude the use of coaxial connectors, which are also expensive and mechanically unreliable. Modern board-to-board high-speed connectors promise bandwidths as high as 12 GHz, along with high pin density, mechanical robustness, and low cost. However, their compatibility with the various transmission lines leading to/from the miniature printed antenna elements and microwave circuitry is not well studied. Here, we focus on the design of the transitions from coplanar waveguide transmission lines to/from a high-speed vertical connector. The performance of the interconnect is examined through electromagnetic simulations and measurements. Comparison is carried out with the expensive sub-miniature push-on sub-micro coaxial connectors commonly used in miniature radio-frequency electronics. The results demonstrate that high-speed vertical connectors can provide comparable performance in the UWB frequency range.

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.

Compact Flexible Planar Antennas for Biomedical Applications: Insight into Materials and Systems Design

Planar antennas have become an integral component in modern biomedical instruments owing to their compact structure, cost effectiveness, and light weight. These antennas are crucial in realizing medical systems such as body area networks, remote health monitoring, and microwave imaging systems. Antennas intended for the above applications should be conformal and fabricated using lightweight materials that are suitable for wear on the human body. Wearable antennas are intended to be placed on the human body to examine its health conditions. Hence, the performance of the antenna, such as its radiation characteristics across the operating frequency bands, should not be affected by human body proximity. This is achieved by selecting appropriate conformal materials whose characteristics remain stable under all environmental conditions. This paper aims to highlight the effects of human body proximity on wearable antenna performance. Additionally, this paper reviews the various types of flexible antennas proposed for biomedical applications. It describes the challenges in designing wearable antennas, the selection of a flexible material that is suitable for fabricating wearable antennas, and the relevant methods of fabrication. This paper also highlights the future directions in this rapidly growing field. Flexible antennas are the keystone for implementing next-generation wireless communication devices for health monitoring and health safety applications.

Microwave Imaging and Sensing Techniques for Breast Cancer Detection

Medical imaging techniques, including X-ray mammography, ultrasound, and magnetic resonance imaging, play a crucial role in the timely identification and monitoring of breast cancer. However, these conventional imaging modalities have their limitations, and there is a need for a more accurate and sensitive alternative. Microwave imaging has emerged as a promising technique for breast cancer detection due to its non-ionizing, non-invasive, and cost-effective nature. Recent advancements in microwave imaging and sensing techniques have opened up new possibilities for the early diagnosis and treatment of breast cancer. By combining microwave sensing with machine learning techniques, microwave imaging approaches can rapidly and affordably identify and classify breast tumors. This manuscript provides a comprehensive overview of the latest developments in microwave imaging and sensing techniques for the early detection of breast cancer. It discusses the principles and applications of microwave imaging and highlights its advantages over conventional imaging modalities. The manuscript also delves into integrating machine learning algorithms to enhance the accuracy and efficiency of microwave imaging in breast cancer detection.

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.

Circularly Polarized Textile Sensors for Microwave-Based Smart Bra Monitoring System

This paper presents a conformal and biodegradable circularly polarized microwave sensor (CPMS) that can be utilized in several medical applications. The proposed textile sensor can be implemented in a Smart Bra system for breast cancer detection (BCD) and a wireless body area network (WBAN). The proposed sensor is composed of a wideband circularly polarized (CP) textile-based monopole antenna with an overall size of 33.5 × 33.5 mm² (0.2 λ_o × 0.2 λ_o) and CPW feed line. The radiating element and ground are fabricated using silver conductive fabric and stitched to a cotton substrate of thickness 2 mm. In the proposed design, a slot is etched in the radiating element to extend bandwidth from 1.8 to 8 GHz at |S₁₁| ≤ -10 dB. It realizes a circularly polarized output with AR ≤ 3 dB operation band from 1.8 to 4 GHz and an average gain of 6 dBi. The proposed CPMS's performance is studied both off-body (air) and on-body in proximity to breast models with and without tumors using near-field microwave imaging. Moreover, the axial ratio is recorded as a feature for a circularly polarized antenna and adds another degree of freedom for cancer detection and data analysis. It assists in detecting tumors in the breast by analyzing the magnitude of the electric field components in vertical and horizontal directions. Finally, the radiation properties are recorded, as well as the specific absorption rate (SAR), to ensure safe operation. The proposed CPMS covers a bandwidth of 1.8-8 GHz with SAR values following the 1 g and 10 g standards. The proposed work demonstrates the feasibility of using textile antennas in wearables, microwave sensing systems, and wireless body area networks (WBANs).

Complete Breast Cancer Detection and Monitoring System by Using Microwave Textile Based Antenna Sensors

This paper presents the development of a new complete wearable system for detecting breast tumors based on fully textile antenna-based sensors. The proposed sensor is compact and fully made of textiles so that it fits conformably and comfortably on the breasts with dimensions of 24 × 45 × 0.17 mm³ on a cotton substrate. The proposed antenna sensor is fed with a coplanar waveguide feed for easy integration with other systems. It realizes impedance bandwidth from 1.6 GHz up to 10 GHz at |S₁₁| ≤ -6 dB (VSWR ≤ 3) and from 1.8 to 2.4 GHz and from 4 up to 10 GHz at |S₁₁| ≤ -10 dB (VSWR ≤ 2). The proposed sensor acquires a low specific absorption rate (SAR) of 0.55 W/kg and 0.25 W/kg at 1g and 10 g, respectively, at 25 dBm power level over the operating band. Furthermore, the proposed system utilizes machine-learning algorithms (MLA) to differentiate between malignant tumor and benign breast tissues. Simulation examples have been recorded to verify and validate machine-learning algorithms in detecting tumors at different sizes of 10 mm and 20 mm, respectively. The classification accuracy reached 100% on the tested dataset when considering |S21| parameter features. The proposed system is vision as a "Smart Bra" that is capable of providing an easy interface for women who require continuous breast monitoring in the comfort of their homes.

Multi-Element UWB Probe Optimization for Medical Microwave Imaging

The need for non-ionizing techniques for medical imaging applications has led to the use of microwave signals. Several systems have been introduced in recent years based on increasing the number of antennas and frequency bandwidth to obtain high resolution and good accuracy in locating objects. A novel microwave imaging system that reduces the number of required antennas for precise target location appropriate for medical applications is presented. The proposed system consists of four UWB extended gap ridge horn (EGRH) antennas covering the frequency band from 0.5 GHz to 1.5 GHz mounted on a cylindrical phantom that mimics the brain in an orthogonal set of two EGRH probes. This configuration has the ability to control both the longitudinal and transversal dimensions of the reconstructed target's image, rather than controlling the spatial resolution, by increasing the frequency band that can be easily affected by medium losses. The system is tested numerically and experimentally by the detection of a cylindrical target within a human brain model.

Early-Stage Lung Tumor Detection Based on Super-Wideband Microwave Reflectometry

This paper aims to detect early-stage lung tumors in deep-seated and superficial locations, and to precisely measure the size of the detected tumor using non-invasive microwave reflectometry over a super-wideband (SWB) frequency range. Human lung phantom and lung tumors are modeled using a multi-layer concentric cylinder structure and spherical-shaped inclusions, respectively. Firstly, a study on the dielectric properties of human torso tissues is carried out over an SWB frequency range of 1–25 GHz based on the Cole–Cole dispersion model. Intensive full-wave simulations of the modeled phantom under irradiation by a custom-designed SWB antenna array are then performed. Results show that small tumor sizes from 5 mm radius in both deep-seated and superficial locations of the lung tissue can be detected based on the contrast of reflection coefficients and reconstructed images produced from backscattered signals between normal and anomalous tissues. The potential of using SWB microwave reflectometry to successfully detect the lung tumors in their early stages and at different depths of the lung tissue has been demonstrated.

Near-Field Microwave Scattering Formulation by A Deep Learning Method

A deep learning method is applied to modelling electromagnetic (EM) scattering for microwave breast imaging (MBI). The neural network (NN) accepts 2D dielectric breast maps at 3 GHz and produces scattered-field data on an antenna array composed of 24 transmitters and 24 receivers. The NN was trained by 18,000 synthetic digital breast phantoms generated by generative adversarial network (GAN), and the scattered-field data pre-calculated by method of moments (MOM). Validation was performed by comparing the 2,000 NN-produced datasets isolated from the training data with the data computed by MOM. Finally, data generated by NN and MOM were used for image reconstruction. The reconstruction demonstrated that errors caused by NN would not significantly affect the image result. But the computational speed of NN was nearly 104 times faster than the MOM, indicating that deep learning has the potential to be considered as a fast tool for EM scattering computation.

Non-Invasive Microwave-Based Imaging System for Early Detection of Breast Tumours

This work introduces a microwave-based system able to detect tumours in breast phantoms in a non-invasive way. The data acquisition system is composed of a hardware system which involves high-frequency components (antennas, switches and cables), a microcontroller, a vector network analyser used as measurement instrument and a computer devoted to the control and automation of the operation of the system. Concerning the software system, the computer runs a Python script which is in charge of mastering and automatising all the required stages for the data acquisition, from initialisation of the hardware system to performing and saving the measurements. We also report on the design of the high-performance broadband antenna used to carry out the measurements, as well as on the algorithm employed to build the final medical images, based on an adapted version of the so-called Improved Delay-and-Sum (IDAS) algorithm improved by a Hamming window filter and averaging preprocessing. The calibration and start-up of the system are also described. The experimental validation includes the use of different tumour models with different dielectric properties inside the breast phantom. The results show promising tumour detection capabilities, even when there is low dielectric contrast between the tumoural and healthy tissues, as is the usual case for dense breasts in young women.

Dynamic Microwave Imaging of the Cardiovascular System Using Ultra-Wideband Radar-on-Chip Devices

OBJECTIVE

Microwave imaging has been investigated for medical applications such as stroke and breast imaging. Current systems typically rely on bench-top equipment to scan at a variety of antenna positions. For dynamic imaging of moving structures, such as the cardiovascular system, much higher imaging speeds are required than what has thus far been reported. Recent innovations in radar-on-chip technology allow for simultaneous high speed data collection at multiple antenna positions at a fraction of the cost of conventional microwave equipment, in a small and potentially portable system. The objective of the current work is to provide proof of concept of dynamic microwave imaging in the body, using radar-on-chip technology.

METHODS

Arrays of body-coupled antennas were used with nine simultaneously operated coherent ultra-wideband radar chips. Data were collected from the chest and thigh of a volunteer, with the objective of imaging the femoral artery and beating heart. In addition, data were collected from a phantom to validate system performance. Video data were constructed using beamforming.

RESULTS

The location of the femoral artery could successfully be resolved, and a distinct arterial pulse wave was discernable. Cardiac activity was imaged at locations corresponding to the heart, but image quality was insufficient to identify individual anatomical structures. Static and differential imaging of the femur bone proved unsuccessful.

CONCLUSION

Using radar chip technology and an imaging approach, cardiovascular activity was detected in the body, demonstrating first steps towards biomedical dynamic microwave imaging. The current portable and modular system design was found unsuitable for static in-body imaging.

SIGNIFICANCE

This first proof of concept demonstrates that radar-on-chip could enable cardiovascular imaging in a low-cost, small and portable system. Such a system could make medical imaging more accessible, particularly in ambulatory or long-term monitoring settings.

Single slice microwave imaging of breast cancer by reverse time migration

PURPOSE

Microwave imaging of breast cancer is considered and a new microwave imaging prototype including the imaging algorithm, the antenna array, and the measurement configuration is presented. The prototype aims to project the geometrical features of the anomalies inside the breast to a single-slice image at the coronal plane depending on the complex dielectric permittivity variation among the tissues to aid the diagnosis.

METHODS

The imaging prototype uses a solid cylindrical dielectric platform, where a total of 24 optimized Vivaldi antennas are embedded inside to form a uniform circular antenna array. The center of the platform is carved to create a hollow part for placement of the breast and the multi-static, microwave scattering parameters are collected with the antenna array around the hollow center. The dielectric platform further enhances the microwave impedance matching against the breast fat tissue and preserves the vertical polarization during the measurements. In the imaging phase, a computationally efficient inverse electromagnetic scattering method - reverse time migration - is considered and adapted in terms of scattering parameters to comply with the actual measurements.

RESULTS

The prototype system is experimentally tested against tissue-mimicking breast phantoms with realistic dielectric permittivity profiles. The reconstructed single-slice images accurately determined the locations and the geometrical extents of the tumor phantoms. These experiments not only verified the microwave imaging prototype but also provided the first experimental results of the imaging algorithm.

CONCLUSIONS

The presented prototype system implementing the reverse time migration method is capable of reconstructing single-slice, non-anatomical images, where the hotspots correspond to the geometrical projections of the anomalies inside the breast. This article is protected by copyright. All rights reserved.

Stretchable printed device for the simultaneous sensing of temperature and strain validated in a mouse wound healing model

Temperature and strain are two vital parameters that play a significant role in wound diagnosis and healing. As periodic temperature measurements with a custom thermometer or strain measurements with conventional metallic gauges became less feasible for the modern competent health monitoring, individual temperature and strain measurement modalities incorporated into wearables and patches were developed. The proposed research in the article shows the development of a single sensor solution which can simultaneously measure both the above mentioned parameters. This work integrates a thermoelectric principle based temperature measurement approach into wearables, ensuring flexibility and bendability properties without affecting its thermo-generated voltage. The modified thermoelectric material helped to achieve stretchability of the sensor, thanks to its superior mechano-transduction properties. Moreover, the stretch-induced resistance changes become an additional marker for strain measurements so that both the parameters can be measured with the same sensor. Due to the independent measurement parameters (open circuit voltage and sensor resistance), the sensing model is greatly attractive for measurements without cross-sensitivity. The highly resilient temperature and strain sensor show excellent linearity, repeatability and good sensitivity. Besides, due to the compatibility of the fabrication scheme to low-temperature processing of the flexible materials and to mass volume production, printed fabrication methodologies were adopted to realize the sensor. This promises low-cost production and a disposable nature (single use) of the sensor patch. For the first time, this innovative temperature-strain dual parameter sensor concept has been tested on mice wounds in vivo. The preliminary experiments on mice wounds offer prospects for developing smart, i.e. sensorized, wound dressings for clinical applications.

Feasibility Study of Glucose Concentration Measurement of Aqueous Solution Using Time Domain Reflected Signals

Recently, wideband microwave spectroscopy (WBMS) has been applied for material characterization. Blood glucose sensing through microwave spectroscopy is usually done with resonant frequency-domain methods. Time-domain (TD) WBMS is a low-cost and convenient technique that can be used for glucose sensing of the aqueous solution. In this paper, early research for the implementation of a TD dielectric spectroscopy setup for glucose concentration measurement is presented. TD reflected signals from water with different glucose content are calculated using inverse Laplace transform. The proposed setup is a quasi-monostatic setup in which measurements are done with two different devices in the frequency range of 0.1 to 6 GHz to make a comparison between frequency domain (FD) and TD methods. Frequency domain (FD) measurement is performed with VNA and two Vivaldi antennas. Then, TD data is obtained using the transforming option of VNA. Direct TD measurement is operated with a maximum length sequence (m-sequence) transceiver. Measurement and numerical results follow the same trend and show good agreement with each other. A monotonic relation between peaks of TD signals and the corresponding glucose concentration is achieved. The variation of the height of the reflected signal's peak is 0.00002 and 0.0005 for each 50 mg/dL glucose concentration with FD measurements and direct TD measurements, respectively. The glucose concentration range of 25 mg/dL to 400 mg/dL is investigated, and the worst repeatability of this method is 3.65% for 300 mg/dL.

Using prior information to enhance microwave tomography images in bone health assessment

BACKGROUND

Osteoporosis is the major cause of bone weakness and fragility in more than 10 million people in the United States. This disease causes bone fractures in the hip or spine, which result in increasing the risk of disabilities or even death. The current gold standard in osteoporosis diagnostics, X-ray, although reliable, it uses ionizing radiations that makes it unfeasible for early and continuous monitoring applications. Recently, microwave tomography (MWT) has been emerging as a biomedical imaging modality that utilizes non-ionizing electromagnetic signals to screen bones' electrical properties. These properties are highly correlated to bones' density, which makes MWT to be an effective and safe alternative for frequent testing in osteoporosis diagnostics.

RESULTS

Both the conventional and wearable simulated systems were successful in localizing the tibia and fibula bones in the enhanced MWT images. Furthermore, structure extraction of the leg's model from the blind MWT images had a minimal error compared to the original one (L2-norm: 15.60%). Under five sequentially incremental bone volume fraction (BVF) scenarios simulating bones' treatment procedure, bones were detected successfully and their densities were found to be inversely proportional to the real part of the relative permittivity values.

CONCLUSIONS

This study paves the way towards implementing a safe and user-friendly MWT system that can be wearable to monitor bone degradation or treatment for osteoporosis cases.

METHODS

An anatomically realistic finite-element (FE) model representing the human leg was initially generated and filled with corresponding tissues' (skin, fat, muscles, and bones) dielectric properties. Then, numerically, the forward and inverse MWT problems were solved within the framework of the finite-element method-contrast source inversion algorithm (FEM-CSI). Furthermore, image reconstruction enhancements were investigated by utilizing prior information about different tissues as an inhomogeneous background as well as by adjusting the imaging domain and antennas locations based on the prior structural information. In addition, the utilization of a medically approved matching medium that can be used in wearable applications, namely an ultrasound gel, was suggested. Additionally, an approach based on k-means clustering was developed to extract the prior structural information from blind reconstructions. Finally, the enhanced images were used to monitor variations in BVF.

Early Stage Breast Cancer Detection Using Wearable Health Diagnosis System

The most prevalent cancer that threatens women’s life is Breast cancer. According to WHO Statistics in 2020, 2.3 Million Women were diagnosed with Breast cancer and 685000 death rate were disclosed globally. In this paper, Wearable Health Diagnosis System (WHDS) based antenna for the identification of the early breast cancer is discussed. Conventional methods are limited by their uncomfortable testing setups, panic environment and failure in results. Recently, textile based antenna for microwave imaging stared to work on the detection of the cancer cells at the earlier stage in breast. WHDS antenna has the requirements of wider bandwidth, high resolution, low Specific Absorption Rate (SAR), bio compatibility, and flexibility. The proposed work is based on the textile antenna using Denim substrate (permittivity = 1.67, thickness = 2 mm) to diagnosis the Early Breast Cancer Tissues (EBCT). Using the following antenna parameters (return loss, E-filed, H-field and SAR values), the position and malignancy of the EBCT is identified. Since the dielectric properties of the cancer cells are high, the influence of the effective permittivity is higher on the E-field and SAR. Along with the above parameters, comparison of various substrate materials (Denim, FR4, and RT duroid) were also tested and Denim is selected for our application as it introduces greater reflection co-efficient and wider bandwidth. The proposed antenna is designed to operate at a frequency of 2–4 GHz. This miniaturised antenna has a volume of 30 × 28 × 2 mm3.

Microwave breast tumor localization using wavelet feature extraction and genetic algorithm-neural network

PURPOSE

Ultra-Wide Band (UWB) microwave breast cancer detection is a promising new technology for routine physical examination and home monitoring. The existing microwave imaging algorithms for breast tumor detection are complex and the effect is still not ideal, due to the heterogeneity of breast tissue, skin reflection, and fibroglandular tissue reflection in backscatter signals. This study aims to develop a machine learning method to accurately locate breast tumor.

METHODS

A microwave-based breast tumor localization method is proposed by time-frequency feature extraction and neural network technology. First, the received microwave array signals are converted into representative and compact features by 4-level Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA). Then, the Genetic Algorithm-Neural Network (GA-NN) is developed to tune hyper-parameters of the neural network adaptively. The neural network embedded in the GA-NN algorithm is a four-layer architecture and 10-fold cross-validation is performed. Through the trained neural network, the tumor localization performance is evaluated on four datasets that are created by FDTD simulation method from 2-D MRI-derived breast models with varying tissue density, shape, and size. Each dataset consists of 1000 backscatter signals with different tumor positions, in which the ratio of training set to test set is 9:1. In order to verify the generalizability and scalability of the proposed method, the tumor localization performance is also tested on a 3-D breast model.

RESULTS

For these 2-D breast models with unknown tumor locations, the evaluation results show that the proposed method has small location errors, which are 0.6076 mm, 3.0813 mm, 2.0798 mm, and 3.2988 mm, respectively, and high accuracy, which is 99%, 80%, 94%, and 85%, respectively. Furthermore, the location error and the prediction accuracy of the 3-D breast model are 3.3896 mm and 81%.

CONCLUSIONS

These evaluation results demonstrate that the proposed machine learning method is effective and accurate for microwave breast tumor localization. The traditional microwave-based breast cancer detection method is to reconstruct the entire breast image to highlight the tumor. Compared with the traditional method, our proposed method can directly get the breast tumor location by applying neural network to the received microwave array signals, and circumvent any complicated image reconstruction processing.

An amplitude-based characteristic parameter extraction algorithm for cerebral edema detection based on electromagnetic induction

Background

Cerebral edema is a common condition secondary to any type of neurological injury. The early diagnosis and monitoring of cerebral edema is of great importance to improve the prognosis. In this article, a flexible conformal electromagnetic two-coil sensor was employed as the electromagnetic induction sensor, associated with a vector network analyzer (VNA) for signal generation and receiving. Measurement of amplitude data over the frequency range of 1–100 MHz is conducted to evaluate the changes in cerebral edema. We proposed an Amplitude-based Characteristic Parameter Extraction (Ab-CPE) algorithm for multi-frequency characteristic analysis over the frequency range of 1–100 MHz and investigated its performance in electromagnetic induction-based cerebral edema detection and distinction of its acute/chronic phase. Fourteen rabbits were enrolled to establish cerebral edema model and the 24 h real-time monitoring experiments were carried out for algorithm verification.

Results

The proposed Ab-CPE algorithm was able to detect cerebral edema with a sensitivity of 94.1% and specificity of 95.4%. Also, in the early stage, it can detect cerebral edema with a sensitivity of 85.0% and specificity of 87.5%. Moreover, the Ab-CPE algorithm was able to distinguish between acute and chronic phase of cerebral edema with a sensitivity of 85.0% and specificity of 91.0%.

Conclusion

The proposed Ab-CPE algorithm is suitable for multi-frequency characteristic analysis. Combined with this algorithm, the electromagnetic induction method has an excellent performance on the detection and monitoring of cerebral edema.

A Computational Method for the Estimation of the Geometrical and Thermophysical Properties of Tumor Using Contact Thermometry

Contact thermometry is the measurement of surface temperature using sensors in contact with the medium. These surface temperatures can be potential indicators of any abnormality possibly a tumor. This research work aims to present a computation method that makes use of contact thermometry to estimate the geometric center, size, and thermophysical properties of breast tumor. Wearable thermal sensors captured real-time surface temperature readings from discrete point locations. The continuous heat distribution over the domain was formulated using forward heat transfer analysis. The optimization method estimated tumor parameters of the breast, and a three-dimensional thermal model was developed from the estimated parameters. Laboratory experiments on breast phantoms were done to validate the estimation method. Furthermore, real-time temperature readings of human subjects were recorded, and the estimated location and size were then compared with the mammogram results. It was found that the estimated two-dimensional geometric center and the size in diameter of the tumor closely match with the mammogram results. Further, the thermophysical properties estimated using the proposed method had a higher order in subjects having a tumor making it a tool for breast cancer screening.

[Connected bras for breast cancer detection in 2021: Analysis and perspectives]

OBJECTIVES

Breast cancer is the leading cancer in women worldwide with about 2 million new cases and 685,000 deaths each year. Mammography is the most widely used screening and diagnostic method. Currently, digital technologies advances facilitate the development of connected and portable devices. To overcome some of the disadvantages of mammography (breast compression, difficulty in analyzing dense breasts, radiation, limited accessibility in some countries, etc.), portable devices, conventionally known as connected bras (CB), have been created to offer an alternative method to mammography. The objective of our review was to list all the published CBs in order to know their main characteristics, their potential indications and their possible limitations.

METHOD

A bibliographical search in the PUBMED database selecting only articles written in French or English, between 2011 and 2020, found 7 CBs under development.

RESULTS

These CBs use thermal, ultrasonic and impedance sensors. Their advantages are an absence of irradiation, an absence of breast compression and a flexibility of use (outside an X-ray cabinet). Mammary gland analysis times vary, depending on the device, between 30min and 24h. They are all connected to data transmission systems and models that analyze the results.

DISCUSSION AND CONCLUSION

These CBs are mostly still undergoing clinical validation (only [iTBra] has been evaluated in a clinical trial) and require evaluation steps that will eventually allow their future use for breast cancer detection in high-risk women, particularly in women with dense breasts and in women between screening waves.

Textile Electromagnetic Brace for Knee Imaging

A wearable textile brace is introduced as an electromagnetic imaging system that breaks hospital boundaries to real-time onsite scanning for knee injuries. The proposed brace consists of a 12-element textile slot loop antenna array, which is designed to match the human knee for enhanced electromagnetic wave penetration. Wool felt and conductive fabric are used to fabricate the antenna array thanks to their flexibility and proper dielectric properties. Each antenna element has a compact footprint of 42 ×24 ×3.22 mm³ and achieves unidirectional radiation, high front-to-back ratio of 14 dB, wide bandwidth of 81% at 0.7-1.7 GHz, and safe SAR levels. A modified double-stage delay, multiply, and sum (DS-DMAS) algorithm is used to process the collected signals from the antenna array based on differential left/right knee imaging. The reconstructed images numerically and experimentally on realistic phantoms demonstrate the potential of the brace system for onsite detection of different types of ligaments/tendon tears.

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.

Full Ground Ultra-Wideband Wearable Textile Antenna for Breast Cancer and Wireless Body Area Network Applications

Wireless body area network (WBAN) applications have broad utility in monitoring patient health and transmitting the data wirelessly. WBAN can greatly benefit from wearable antennas. Wearable antennas provide comfort and continuity of the monitoring of the patient. Therefore, they must be comfortable, flexible, and operate without excessive degradation near the body. Most wearable antennas use a truncated ground, which increases specific absorption rate (SAR) undesirably. A full ground ultra-wideband (UWB) antenna is proposed and utilized here to attain a broad bandwidth while keeping SAR in the acceptable range based on both 1 g and 10 g standards. It is designed on a denim substrate with a dielectric constant of 1.4 and thickness of 0.7 mm alongside the ShieldIt conductive textile. The antenna is fed using a ground coplanar waveguide (GCPW) through a substrate-integrated waveguide (SIW) transition. This transition creates a perfect match while reducing SAR. In addition, the proposed antenna has a bandwidth (BW) of 7-28 GHz, maximum directive gain of 10.5 dBi and maximum radiation efficiency of 96%, with small dimensions of 60 × 50 × 0.7 mm3. The good antenna's performance while it is placed on the breast shows that it is a good candidate for both breast cancer imaging and WBAN.

An Active and Low-Cost Microwave Imaging System design for Detection of Breast Cancer Using Back Scattered Signal

A defected ground antenna with dielectric reflector is designed and investigated for breast tumour diagnosis. Ultra-wide band resonance (3.1 to 10.6 GHz) is achieved by etching two slots and adding a narrow vertical strip in a patch antenna. A high dielectric constant substrate is added below the antenna, which shows remarkable effect on performance. Antenna performance is verified experimentally on an artificially fabricated breast tissue and tumour. Malignant tissue has different dielectric properties than the normal tissue, that causes deviation in the scattered antenna power. Average value of backscattered signal variation and ground penetrating radar (GPR) algorithm is used to localize the tumour of radius 4mm in breast tissue.

Breast tumor parameter estimation and interactive 3D thermal tomography using discrete thermal sensor data

This work uses a simple low-cost wearable device embedded with discrete thermal sensors to map the breast skin surface temperature. A methodology has been developed to estimate diameter, blood perfusion, metabolic heat generation and location in X, Y, Z coordinate of tumor from this discrete set of data. An interactive 3D thermal tomography was developed which provides a detailed 3D thermal view of the breast anatomy. Using this system, the user can interactively rotate and slice the 3D thermal image of the breast for a detailed study of the tumor. Finite element method (FEM) and an evolution-based inverse method were used for the parameter estimation. The method was first validated using phantom experiments and the results obtained were within an error of 10% (0.005 W cm^-3) for heat generation and 15% (0.3 cm) for heater location. Further validation was carried out through clinical trials on 60 human subjects. Estimated blood perfusion rate and metabolic heat generation rate exhibit distinguishable difference between cancerous and non-cancerous breast. Estimated diameter and location of tumor in cancerous breast shows good agreement with the actual clinical reports. We have obtained a sensitivity of 82.78% and specificity of 87.09%. Proposed breast tumor parameter estimation methodology with interactive 3D thermal tomography is a good screening tool for breast cancer detection and also useful for clinicians to find out location including depth.

CMOS Gaussian Monocycle Pulse Transceiver for Radar-Based Microwave Imaging

A single-chip Gaussian monocycle pulse (GMP) transceiver was developed for radar-based microwave imaging by the use of 65-nm complementary metal oxide semiconductor (CMOS) technology. A transmitter (TX) generates GMP signals, whose pulse widths and -3 dB bandwidths are 192 ps and 5.9 GHz, respectively. A 102.4 GS/s equivalent time sampling receiver (RX) performs the minimum jitter, input referred noise, signal-to-nose-ratio (SNR), signal-to-noise and distortion ratio (SNDR) effective number of bits (ENOB) of 0.58 ps, 0.24 mVrms, 28.4 dB, 26.6 dB and 4.1 bits, respectively. The SNR for the bandwidth of 3.6 GHz is 36.3 dB. The power dissipations of transmitter and receiver circuits are 19.79 mW and 48.87 mW, respectively. The GMP transceiver module can differentiate two phantom targets with the size of 1 cm and the spacing of 1 cm by confocal imaging.

Non-Invasive RF Technique for Detecting Different Stages of Alzheimer's Disease and Imaging Beta-Amyloid Plaques and Tau Tangles in the Brain

This paper describes a novel approach of detecting different stages of Alzheimer's disease (AD) and imaging beta-amyloid plaques and tau tangles in the brain using RF sensors. Dielectric measurements were obtained from grey matter and white matter regions of brain tissues with severe AD pathology at a frequency range of 200 MHz to 3 GHz using a vector network analyzer and dielectric probe. Computational models were created on CST Microwave Suite using a realistic head model and the measured dielectric properties to represent affected brain regions at different stages of AD. Simulations were carried out to test the performance of the RF sensors. Experiments were performed using textile-based RF sensors on fabricated phantoms, representing a human brain with different volumes of AD-affected brain tissues. Experimental data was collected from the sensors and processed in an imaging algorithm to reconstruct images of the affected areas in the brain. Measured dielectric properties in brain tissues with AD pathology were found to be different from healthy human brain tissues. Simulation and experimental results indicated a correlated shift in the captured reflection coefficient data from RF sensors as the amount of affected brain regions increased. Finally, images reconstructed from the imaging algorithm successfully highlighted areas of the brain affected by plaques and tangles as a result of AD. The results from this study show that RF sensing can be used to identify areas of the brain affected by AD pathology. This provides a promising new non-invasive technique for monitoring the progression of AD.

A Planar Ultrawideband Patch Antenna Array for Microwave Breast Tumor Detection

In this paper, a compact planar ultrawideband (UWB) antenna and an antenna array setup for microwave breast imaging are presented. The proposed antenna is constructed with a slotted semicircular-shaped patch and partial trapezoidal ground. It is compact in dimension: 0.30λ × 0.31λ × 0.011λ, where λ is the wavelength of the lowest operating frequency. For design purposes, several parameters are assumed and optimized to achieve better performance. The prototype is applied in the breast imaging scheme over the UWB frequency range 3.10–10.60 GHz. However, the antenna achieves an operating bandwidth of 8.70 GHz (2.30–11.00 GHz) for the reflection coefficient under–10 dB with decent impedance matching, 5.80 dBi of maximum gain with steady radiation pattern. The antenna provides a fidelity factor (FF) of 82% and 81% for face-to-face and side-by-side setups, respectively, which specifies the directionality and minor variation of the received pulses. The antenna is fabricated and measured to evaluate the antenna characteristics. A 16-antenna array-based configuration is considered to measure the backscattering signal of the breast phantom where one antenna acts as transmitter, and 15 of them receive the scattered signals. The data is taken in both the configuration of the phantom with and without the tumor inside. Later, the Iteratively Corrected Delay and Sum (IC–DAS) image reconstructed algorithm was used to identify the tumor in the breast phantom. Finally, the reconstructed images from the analysis and processing of the backscattering signal by the algorithm are illustrated to verify the imaging performance.

Microwave Breast Imaging Using Rotational Bistatic Impulse Radar for the Detection of Breast Cancer: Protocol for a Prospective Diagnostic Study

Background

Mammography is the standard examination for breast cancer screening; however, it is associated with pain and exposure to ionizing radiation. Microwave breast imaging is a less invasive method for breast cancer surveillance. A bistatic impulse radar–based breast cancer detector has recently been developed.

Objective

This study aims to present a protocol for evaluating the diagnostic accuracy of the novel microwave breast imaging device.

Methods

This is a prospective diagnostic study. A total of 120 participants were recruited before treatment administration and divided into 2 cohorts: 100 patients diagnosed with breast cancer and 20 participants with benign breast tumors. The detector will be directly placed on each breast, while the participant is in supine position, without a coupling medium. Confocal images will be created based on the analyzed data, and the presence of breast tumors will be assessed. The primary endpoint will be the diagnostic accuracy, sensitivity, and specificity of the detector for breast cancer and benign tumors. The secondary endpoint will be the safety and detectability of each molecular subtype of breast cancer. For an exploratory endpoint, the influence of breast density and tumor size on tumor detection will be investigated.

Results

Recruitment began in November 2018 and was completed by March 2020. We anticipate the preliminary results to be available by summer 2021.

Conclusions

This study will provide insights on the diagnostic accuracy of microwave breast imaging using a rotational bistatic impulse radar. The collected data will improve the diagnostic algorithm of microwave imaging and lead to enhanced device performance.

Trial Registration

Japan Registry of Clinical Trials jRCTs062180005; https://jrct.niph.go.jp/en-latest-detail/jRCTs062180005

International Registered Report Identifier (IRRID)

DERR1-10.2196/17524

The Application of an Iterative Structure to the Delay-and-Sum and the Delay-Multiply-and-Sum Beamformers in Breast Microwave Imaging

Breast microwave imaging (BMI) is a potential breast cancer screening method. This manuscript presents a novel iterative delay-and-sum (DAS) based reconstruction algorithm for BMI. This iterative-DAS (itDAS) algorithm uses a forward radar model to iteratively update an image estimate. A variation of the itDAS reconstruction algorithm that uses the delay-multiply-and-sum (DMAS) beamformer was also implemented (the itDMAS algorithm). Both algorithms were used to reconstruct images from experimental scans of an array of 3D-printed MRI-based breast phantoms performed with a clinical BMI system. The signal-to-clutter ratio (SCR) and signal-to-mean ratio (SMR) were used to compare the performance of the itDAS and itDMAS methods to the DAS and DMAS beamformers. While no significant difference between the itDAS and itDMAS methods was observed in most images, the itDAS algorithm produced reconstructions that had significantly higher SMR than the non-iterative methods, increasing contrast by as much as 19 dB over DAS and 13 dB over DMAS. The itDAS algorithm also increased the SCR of reconstructions by up to 5 dB over DAS and 4 dB over DMAS, indicating that both high-intensity and background clutter are reduced in images reconstructed by the itDAS algorithm.

Nanostrip flexible microwave enzymatic biosensor for noninvasive epidermal glucose sensing

Microwave sensors based on microstrip antennas are promising as wearable devices because of their flexibility and wireless communication compatibility. However, their sensitivity is limited due to the reduced sensor size and the potential of biochemical monitoring needs to be explored. In this work, we present a new concept to enhance the microwave signals using nanostrip-based metamaterials. The introduction of the nanostrip structures was achieved by theory and simulations. Experiments prove their enhancement of the electric field and sensing response in the characteristic gigahertz (GHz) wave band. Ordered nanostrips were fabricated on a plastic substrate through a simple nanoscale printing approach. Glucose oxidase is directly doped into the nanostrips, which enables a flexible wearable enzymatic biosensor for glucose sensing. Sensing experiments demonstrated that the nanostrip biosensor gives excellent performance for glucose detection, including high sensitivity, fast response, low detection limit, high affinity, and low power consumption. The applicability of the nanostrip-based sensor as a wearable epidermal device for real-time noninvasive monitoring of glucose in sweat is verified as well.

Advances in Microwave Near-Field Imaging: Prototypes, Systems, and Applications

Microwave imaging employs detection techniques to evaluate hidden or embedded objects in a structure or media using electro-magnetic (EM) waves in the microwave range, 300 MHz-300 GHz. Microwave imaging is often associated with radar detection such as target location and tracking, weather-pattern recognition, and underground surveillance, which are far-field applications. In recent years, due to microwaves' ability to penetrate optically opaque media, short-range applications, including medical imaging, nondestructive testing (NDT) and quality evaluation, through-the-wall imaging, and security screening, have been developed. Microwave near-field imaging most often occurs when detecting the profile of an object within the short range (when the distance from the sensor to the object is less than one wavelength to several wave-lengths) and depends on the electrical size of the antenna(s) and target.

Review of Microwaves Techniques for Breast Cancer Detection

Conventional breast cancer detection techniques including X-ray mammography, magnetic resonance imaging, and ultrasound scanning suffer from shortcomings such as excessive cost, harmful radiation, and inconveniences to the patients. These challenges motivated researchers to investigate alternative methods including the use of microwaves. This article focuses on reviewing the background of microwave techniques for breast tumour detection. In particular, this study reviews the recent advancements in active microwave imaging, namely microwave tomography and radar-based techniques. The main objective of this paper is to provide researchers and physicians with an overview of the principles, techniques, and fundamental challenges associated with microwave imaging for breast cancer detection. Furthermore, this study aims to shed light on the fact that until today, there are very few commercially available and cost-effective microwave-based systems for breast cancer imaging or detection. This conclusion is not intended to imply the inefficacy of microwaves for breast cancer detection, but rather to encourage a healthy debate on why a commercially available system has yet to be made available despite almost 30 years of intensive research.

Metasurface Loaded High Gain Antenna based Microwave Imaging using Iteratively Corrected Delay Multiply and Sum Algorithm

In this paper, the design consideration is investigated for a cylindrical system with low-cost and low-loss dielectric materials for the detection of breast tumor using iteratively corrected delay multiply and sum (IC- DMAS) algorithm. Anomaly in breast tissue is one of the most crucial health issues for women all over the world today. Emergency medical imaging diagnosis can be harmlessly managed by microwave-based analysis technology. Microwave Imaging (MI) has been proved to be a reliable health monitoring approach that can play a fundamental role in diagnosing anomaly in breast tissue. An array of 16 high gain microstrip antennas loaded by Index Near-Zero (INZ) metasurfaces (MS), having the impedance bandwidth of 8.5 GHz (2.70-11.20 GHz) are used as transceivers for the system. The MS is used to increase the electrical length of the signal that results in the gain enhancements. The antennas are mounted in a cylindrical arrangement on a mechanical rotating table along with a phantom mounting podium. A non-reflective positive control switching matrix is used for transmitting and receiving microwave signals. A set of lab-made realistic heterogeneous breast phantoms containing skin, fat, glandular, and tumor tissue dielectric properties in individual layers are used to verify the performance of the proposed technique. The control of the mechanical unit, data collection, and post-processing is conducted via MATLAB. The system can detect multiple tumor objects. The imaging results and numerical Signal to Mean Ratio (SMR) values of the experiment validate the system efficiency and performance that can be a viable solution for tumor detections.

Comparing Radar-Based Breast Imaging Algorithm Performance with Realistic Patient-Specific Permittivity Estimation

Radar-based breast imaging has shown promise as an imaging modality for early-stage cancer detection, and clinical investigations of two commercial imaging systems are ongoing. Many imaging algorithms have been proposed, which seek to improve the quality of the reconstructed microwave image to enhance the potential clinical decision. However, in many cases, the radar-based imaging algorithms have only been tested in limited numerical or experimental test cases or with simplifying assumptions such as using one estimate of permittivity for all patient test cases. In this work, the potential impact of patient-specific permittivity estimation on algorithm comparison is highlighted using representative experimental breast phantoms. In particular, the case studies presented help show that the permittivity estimate can impact the conclusions of the algorithm comparison. Overall, this work suggests that it is important that imaging algorithm comparisons use realistic test cases with and without breast abnormalities and with reconstruction permittivity estimation.

A Low Cost and Portable Microwave Imaging System for Breast Tumor Detection Using UWB Directional Antenna array

Globally, breast cancer is a major reason for female mortality. Due to the limitations of current clinical imaging, the researchers are encouraged to explore alternative and complementary tools to available techniques to detect the breast tumor in an earlier stage. This article outlines a new, portable, and low-cost microwave imaging (MWI) system using an iterative enhancing technique for breast imaging. A compact side slotted tapered slot antenna is designed for microwave imaging. The radiating fins of tapered slot antenna are modified by etching nine rectangular side slots. The irregular slots on the radiating fins enhance the electrical length as well as produce strong directive radiation due to the suppression of induced surface currents that radiate vertically at the outer edges of the radiating arms with end-fire direction. It has remarkable effects on efficiency and gain. With the addition of slots, the side-lobe levels are reduced, the gain of the main-lobe is increased and corrects the squint effects simultaneously, thus improving the characteristics of the radiation. For experimental validation, a heterogeneous breast phantom was developed that contains dielectric properties identical to real breast tissues with the inclusion of tumors. An alternative PC controlled and microcontroller-based mechanical MWI system is designed and developed to collect the antenna scattering signal. The radiated backscattered signals from the targeted area of the human body are analyzed to reveal the changes in dielectric properties in tissues. The dielectric constants of tumorous cells are higher than that of normal tissues due to their higher water content. The remarkable deviation of the scattered field is processed by using newly proposed Iteratively Corrected Delay and Sum (IC-DAS) algorithm and the reconstruction of the image of the phantom interior is done. The developed UWB (Ultra-Wideband) antenna based MWI has been able to perform the detection of tumorous cells in breast phantom that can pave the way to saving lives.

Patient-Specific Debye Parameters for Human Blood

This paper develops a patient-specific model for the Debye parameters of human blood based on hemoglobin content. Blood samples were collected from 176 patients visiting the University Hospital, with both permittivity measurements and standard hematological analysis performed on each blood draw. The complete blood count of each sample provided information on the hemoglobin concentration of each sample; in total there were 73 distinct hemoglobin concentrations reported. An iterative process was used to find patient-specific, based on hemoglobin content, Debye parameters. First, a two-stage genetic algorithm was used to solve for the parameters of a two-pole Debye model based on the mean-blood properties. Then, a modified two-pole Debye model incorporating hemoglobin information was developed, and those parameters were solved for using the same two-stage genetic algorithm. This paper presents the parameters for both the mean-blood model and the patient-specific model. The patient-specific model has a mean-fractional error across all 73 samples of 3.41% compared to 7.64% when using the mean-blood model to represent the entire population. This work demonstrates the range in the dielectric properties of human blood samples and highlights the need for incorporating patient-specific information when using the Debye parameters to model the dielectric properties of human blood.

Wearable Triband E-Shaped Dipole Antenna with Low SAR for IoT Applications

This paper presents a novel design of a flexible and wearable E-shaped, multiband dipole antenna. The antenna has a low profile and is printed on a common 2 mm thick denim fabric ( ε r = 1.7 ). By installing a passively coupled rectangular patch with L-shaped cuts, the lower frequency band is supported and the bandwidth at higher frequencies is also enhanced. The antenna’s performance was observed under different deformations in free space as well as when it was placed on different parts of the human body. No significant changes in the characteristics of the frequency bands of interest were observed for the flexible antenna compared with the initial nondeformable antenna. Simulations for 10 g average specific absorption rate (SAR) at different input powers up to 250 mW were carried out considering that the antenna adheres well to the human body and there is no spacing or shielding. The obtained results show that the amount of energy absorbed by the body tissue increases by increasing the incident power.

Detectability of Breast Tumors in Excised Breast Tissues of Total Mastectomy by IR-UWB-Radar-Based Breast Cancer Detector

The objective of this paper is to investigate the detectability of breast tumors having various histological types in excised breast tissues of total mastectomy. The tumor images measured by a portable impulse-radio-ultra-wideband (IR-UWB)-radar-based breast cancer detector are compared with both pathological images and images of dedicated breast positron emission tomography. It is found that the detector can detect invasive-ductal-carcinomas and extensive intraductal component in the dense breast. The density of the breast has a correlation to the effective permittivity derived from the reconstructed confocal images. The results show that the IR-UWB-radar-based breast cancer detector has a potential as a portable modality for early-stage breast cancer screening.