Breast cancer cells exhibits specific dielectric signature in vitro using the open-ended coaxial probe technique from 200 MHz to 13.6 GHz

Open-Ended Coaxial Probe for Effective Reconstruction of Biopsy-Excised Tissues' Dielectric Properties

Dielectric characterization is extremely promising in medical contexts because it offers insights into the electromagnetic properties of biological tissues for the diagnosis of tumor diseases. This study introduces a promising approach to improve accuracy in the dielectric characterization of millimeter-sized biopsies based on the use of a customized electromagnetic characterization system by adopting a coated open-ended coaxial probe. Our approach aims to accelerate biopsy analysis without sample manipulation. Through comprehensive numerical simulations and experiments, we evaluated the effectiveness of a metal-coating system in comparison to a dielectric coating with the aim for replicating a real scenario: the use of a needle biopsy core with the tissue inside. The numerical analyses highlighted a substantial improvement in the reconstruction of the dielectric properties, particularly in managing the electric field distribution and mitigating fringing field effects. Experimental validation using bovine liver samples revealed highly accurate measurements, particularly in the real part of the permittivity, showing errors lower than 1% compared to the existing literature data. These results represent a significant advancement for the dielectric characterization of biopsy specimens in a rapid, precise, and non-invasive manner. This study underscores the robustness and reliability of our innovative approach, demonstrating the convergence of numerical analyses and empirical validation.

A Novel Liver Cancer POC Diagnostic Detection Technique by a Gate-engineered Source-extended TFET Device

This work reports a novel POC diagnostic technique to identify the cancerous liver cell lines by designing a Source-Extended (SE) Tunnel Field Effect Transistor (TFET) having a Single-Gate (SG) with Single-Metal (SM) and Dual-Metal (DM) structure. The proposed structures have been equipped with nanocavities by trenching the gate oxide layer where the needle biopsy obtained liver sample has been immobilized. The detection is based on the difference in drain current and the ratio of the proposed device's ON and OFF state currents, which has been evaluated by obtaining the sensitivities. The cancerous and non-cancerous liver cell lines possess different dielectric properties in high frequencies ranging from 100 MHz to 5 GHz, affecting the cavity region's effective capacitances. The change in the dielectric constant of the specimen at 900 MHz has been considered which results in the change in device drain current and device performance. Various parameters of the device, like the adhesive layer in the cavity region, the material of the gate, the length of the cavities, and the orientation of the cavities, have been modified to observe the performance. The total work has been done in the simulation environment, which includes the study considering the different proportions of cancerous and non-cancerous cells in a particular specimen. A comparative analysis has been made between the performance of the proposed SM and DM gate structure. The proposed detection method has been compared with the existing methods reported in the literature. The proposed method can be considered a novel technique and can be implemented as a point of care (POC) diagnostic to detect whether the specimen liver cell line is cancerous.

Continuous-flow electrorotation (cROT): improved throughput characterization for dielectric properties of cancer cells

This paper presents the concept of a newly developed high-throughput measurement device for determining the dielectric properties of cancer cells. The proposed continuous-flow electrorotation (cROT) device can induce electrorotation (ROT) with vertical rotation using two sets of interdigitated electrodes on the top and bottom substrates to torque the cells. In the developed device, multiple rotating cells flowing in a microchannel are aligned between electrodes using dielectrophoresis. This allows for the measurement of the rotational behavior of the cells with continuous flow, resulting in a significant improvement in throughput compared to the conventional ROT devices reported previously. The dielectric properties, permittivity of the cell membrane and conductivity of the cell cytoplasm, of HeLa cells obtained by simultaneous measurements using the developed cROT device were 9.13 ± 1.02 and 0.93 ± 0.10 S m-1, respectively. Moreover, the measurement throughput was successfully increased to 2700 cells per h using the cROT technique.

Ultra Sensitive Breast Cancer Cell Lines Detection Using Dual Nanocavities Engraved Junctionless FET

This article reports breast cancer cell lines (Hs578T, MDA-MB-231, MCF-7, and T47D) and healthy breast cells (MCF-10A) detection based on the modulation of its electrical properties by deploying dual nanocavity engraved junctionless FET. The device has a dual gate to enhance gate control and has two nanocavities etched under both gates for breast cancer cell lines immobilization. As the cancer cells are immobilized in the engraved nanocavities, which were earlier filled with air, the dielectric constant of the nanocavities changes. This results in the modulation of the device's electrical parameters. This electrical parameters modulation is then calibrated to detect the breast cancer cell lines. The reported device demonstrates a higher sensitivity toward the detection of breast cancer cells. The JLFET device optimization is done for improving the performance by optimizing the nanocavity thickness and the SiO2 oxide length. The variation in the dielectric property of cell lines plays a key role in the detection technique of the reported biosensor. The sensitivity of the JLFET biosensor is analyzed in terms of ∆VTH, ∆ION, ∆gm , and ∆SS . The reported biosensor shows the maximum sensitivity for T47D ( κ = 32 ) breast cancer cell line with ∆VTH = 0.800 V, ∆ION = 0.165 mA/μm, ∆gm = 0.296 mA/V-μm , and ∆SS = 5.41 mV/decade. Moreover, the effect of variation in the occupancy of the cavity by the immobilized cell lines has also been studied and analyzed. With increased cavity occupancy the variation in the device performance parameter enhances Further, the sensitivity of the proposed biosensor is compared with the existing biosensors and it is reported to be highly sensitive as compared to the existing biosensors. Hence, the device can be utilized for array based screening of cell lines of breast cancer and diagnosis with the benefit of easier fabrication and cost effectiveness of the device.

Dielectric Characterization of Breast Biopsied Tissues as Pre-Pathological Aid in Early Cancer Detection: A Blinded Feasibility Study

Dielectric characterization has significant potential in several medical applications, providing valuable insights into the electromagnetic properties of biological tissues for disease diagnosis, treatment planning, and monitoring of therapeutic interventions. This work presents the use of a custom-designed electromagnetic characterization system, based on an open-ended coaxial probe, for discriminating between benign and malignant breast tissues in a clinical setting. The probe's development involved a well-balanced compromise between physical feasibility and its combined use with a reconstruction algorithm known as the virtual transmission line model (VTLM). Immediately following the biopsy procedure, the dielectric properties of the breast tissues were reconstructed, enabling tissue discrimination based on a rule-of-thumb using the obtained dielectric parameters. A comparative analysis was then performed by analyzing the outcomes of the dielectric investigation with respect to conventional histological results. The experimental procedure took place at Complejo Hospitalario Universitario de Toledo-Hospital Virgen de la Salud, Spain, where excised breast tissues were collected and subsequently analyzed using the dielectric characterization system. A comprehensive statistical evaluation of the probe's performance was carried out, obtaining a sensitivity, specificity, and accuracy of 81.6%, 61.5%, and 73.4%, respectively, compared to conventional histological assessment, considered as the gold standard in this investigation.

Aberrant Water Structure Dynamics in B16 Melanoma-Bearing Mice by Time Domain Refractometry Analysis

Living bodies comprise approximately 55-75% water to maintain homeostasis. However, little is known about the comprehensive differences in in vivo water molecule dynamics (water structure dynamics; WSD) between physiological and pathophysiological statuses. Here, we examined the WSD of ex vivo tumor tissues and organs from tumor-bearing mice with engrafted mouse malignant melanoma cells (B16-F10) in the right flanks to compare with those in healthy mice, using time domain reflectometry of dielectric spectroscopy at days 9, 11, and 14 after engrafting. The relaxation parameters of relaxation time (τ), relaxation time distribution parameter (β), and relaxation strength (∆ε) were measured on tumor tissues and lung, liver, kidney, and skin tissues. Immediately afterward, the water contents (%) in the tumor and the other organs were calculated by measuring their weights before and after freeze-drying. Each parameter of the tumor was compared to that of pooled values of other organs in tumor-bearing (TO) and healthy mice (HO). The tumor water content temporarily increased compared to that of HO at day 11; the tumor volume was also prone to increase. In contrast, tumor tissues exhibited significantly higher values of β close to 1 of ultrapure water and ∆ε compared to TO and HO at all times. Moreover, β in the viscera of TO was prone to increase compared to that of HO with significantly higher levels at day 11. Conclusively, tumor-bearing mice exhibited systemically aberrant WSD, unlike healthy mice. Thus, dielectric spectroscopy in terms of WSD may provide novel pathophysiological perspectives in tumor-bearing living bodies.

Early breast cancer detection and differentiation tool based on tissue impedance characteristics and machine learning

During Basic screening, it is challenging, if not impossible to detect breast cancer especially in the earliest stage of tumor development. However, measuring the electrical impedance of biological tissue can detect abnormalities even before being palpable. Thus, we used impedance characteristics data of various breast tissue to develop a breast cancer screening tool guided and augmented by a deep learning (DL). A DL algorithm was trained to ideally classify six classes of breast cancer based on electrical impedance characteristics data of the breast tissue. The tool correctly predicted breast cancer in data of patients whose breast tissue impedance was reported to have been measured when other methods detected no anomaly in the tissue. Furthermore, a DL-based approach using Long Short-Term Memory (LSTM) effectively classified breast tissue with an accuracy of 96.67%. Thus, the DL algorithm and method we developed accurately augmented breast tissue classification using electrical impedance and enhanced the ability to detect and differentiate cancerous tissue in very early stages. However, more data and pre-clinical is required to improve the accuracy of this early breast cancer detection and differentiation tool.

Fin field-effect-transistor engineered sensor for detection of MDA-MB-231 breast cancer cells: A switching-ratio-based sensitivity analysis

The present study describes the utilization of a gallium-arsenide gate-stack gate-all-around (GaAs-GS-GAA) fin field-effect transistor (FinFET) to accomplish the electrical identification of the breast cancer cell MDA-MB-231 by monitoring the device switching ratio. The proposed sensor uses four nanocavities carved beneath the gate electrodes for enhanced detection sensitivity. MDA-MB-231 (cancerous) and MCF-10A (healthy) breast cells have a distinct dielectric constant, and it changes when exposed to microwave frequencies spanning across 200 MHz and 13.6 GHz, which modifies the electrical characteristics, allowing for early diagnosis. First, a percentage shift in the primary DC characteristics is presented to demonstrate the advantage of GS-GAA FinFET over conventional FinFET. The sensor measures the switching-ratio-based sensitivity, which comes out to be 99.72% for MDA-MB-231 and 47.78% for MCF-10A. The sensor was tested for stability and reproducibility and found to be repeatable and sufficiently stable with settling times of 55.51, 60.80, and 71.58 ps for MDA-MB-231 cells, MCF-10A cells, and air, respectively. It can distinguish between viable and nonviable cells based on electrical response alterations. The possibility of early detection of cancerous breast cells using Bruggeman's model is also discussed. Further, the impact of biomolecule occupancy and frequency variations on the device sensitivity is carried out. This study also explains how to maximize the sensing performance by adjusting the fin height, fin width, work function, channel doping, temperature, and drain voltage. Lastly, this article compared the proposed breast cancer cell detectors to existing literature to evaluate their performance and found considerable improvement. The findings of this research have the potential to establish GaAs-GS-GAA FinFET as a promising contender for MDA-MB-231 breast cancer cell detection.

Determination of a Measurement Procedure for the Study of Cells' Dielectric Properties through Descriptive Statistic

This paper presents a measurement procedure for analyzing the dielectric properties of cells using descriptive statistics. The study focuses on four cancer cell lines (MDA-MB-231 and MCF-7 breast cancer, SaOS-2, and 143B osteosarcoma) and DMEM culture medium, utilizing the Lorentzian fit model of the return-loss function. The measurements are performed using a circular patch resonator with a 40 mm diameter, powered by a miniVNA operating in the frequency range of 1 MHz to 3 GHz. Eight specimens are prepared for each group to ensure reliability, and the return loss is recorded ten times for each specimen. Various statistical parameters are calculated and evaluated, including the average value, standard deviation, coefficient of variation, and relative error between the average and the first values. The results demonstrate that one single acquisition highly represents the entire set of ten data points, especially for the resonant frequency, with an accuracy error lower than 0.05%. These findings have significant implications for the methodological approach to detecting cells' dielectric properties, as they substantially reduce time and preserve the specimens without compromising the accuracy of the experimental results.

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.

Wireless technologies, non-ionizing electromagnetic fields and children: Identifying and reducing health risks

Children today are conceived and live in a sea of wireless radiation that did not exist when their parents were born. The launch of the digital age continues to transform the capacity to respond to emergencies and extend global communications. At the same time that this increasingly ubiquitous technology continues to alter the nature of commerce, medicine, transport and modern life overall, its varied and changing forms have not been evaluated for their biological or environmental impacts. Standards for evaluating radiation from numerous wireless devices were first set in 1996 to avoid heating tissue and remain unchanged since then in the U.S. and many other nations. A wide range of evidence indicates that there are numerous non-thermal effects from wireless radiation on reproduction, development, and chronic illness. Many widely used devices such as phones and tablets function as two-way microwave radios, sending and receiving various frequencies of information-carrying microwave radiation on multiple simultaneously operating antennas. Expert groups advising governments on this matter do not agree on the best approaches to be taken. The American Academy of Pediatrics recommends limited screen time for children under the age of two, but more than half of all toddlers regularly have contact with screens, often without parental engagement. Young children of parents who frequently use devices as a form of childcare can experience delays in speech acquisition and bonding, while older children report feelings of disappointment due to 'technoference'-parental distraction due to technology. Children who begin using devices early in life can become socially, psychologically and physically addicted to the technology and experience withdrawal upon cessation. We review relevant experimental, epidemiological and clinical evidence on biological and other impacts of currently used wireless technology, including advice to include key questions at pediatric wellness checkups from infancy to young adulthood. We conclude that consistent with advice in pediatric radiology, an approach that recommends that microwave radiation exposures be As Low As Reasonably Achievable (ALARA) seems sensible and prudent, and that an independently-funded training, research and monitoring program should be carried out on the long term physical and psychological impacts of rapidly changing technological milieu, including ways to mitigate impacts through modifications in hardware and software. Current knowledge of electrohypersensitivity indicates the importance of reducing wireless exposures especially in schools and health care settings.

Design of Ultra-Wideband Phased Array Applicator for Breast Cancer Hyperthermia Therapy

Focused microwave-hyperthermia therapy has recently emerged as a key technology in the treatment of breast cancer due to non-invasive treatment. An applicator of a three-ring phased array consisting of ultra-wideband (UWB) microstrip antennas was designed for breast cancer therapy and operates at 0.915 GHz and 2.45 GHz. The proposed antenna has an ultra-wideband from 0.7 GHz to 5.5 GHz with resonant frequencies of 0.915 GHz and 2.45 GHz and dimensions of 15 × 43.5 × 1.575 mm³. The number of each ring was chosen to be 12 based on the SAR distribution and the performance indicators of tumor off-center focusing results for four different numbers of single-ring arrays. The homogeneous breast model is applied to a three-ring phased array consisting of 36 elements for focused simulation, and 1 cm³ and 2 cm³ tumors are placed in three different locations in the breast. The simulation results show that the proposed phased array has good performance and the capability to raise the temperature of different volumes of breast cancer above 42.5 °C after choosing a suitable operating frequency. The proposed applicator allows for precise treatment of tumors by selecting the appropriate operating frequency based on the size of the malignant tumor.

High-Frequency (30 MHz-6 GHz) Breast Tissue Characterization Stabilized by Suction Force for Intraoperative Tumor Margin Assessment

A gigahertz (GHz) range antenna formed by a coaxial probe has been applied for sensing cancerous breast lesions in the scanning platform with the assistance of a suction tube. The sensor structure was a planar central layer and a metallic sheath of size of 3 cm² connected to a network analyzer (keySight FieldFox N9918A) with operational bandwidth up to 26.5 GHz. Cancer tumor cells have significantly higher water content (as a dipolar molecule) than normal breast cells, changing their polarization responses and dielectric losses to incoming GHz-based stimulation. Principal component analysis named S₁₁, related to the dispersion ratio of the input signal, is used as a parameter to identify malignant tumor cells in a mouse model (in vivo) and tumor specimens of breast cancer patients (in vitro) (both central and marginal parts). The results showed that S₁₁ values in the frequency range from 5 to 6 GHz were significantly higher in cancer-involved breast lesions. Histopathological analysis was the gold standard for achieving the S₁₁ calibration to distinguish normal from cancerous lesions. Our calibration on tumor specimens presented 82% positive predictive value (PPV), 100% negative predictive value (NPV), and 86% accuracy. Our goal is to apply this system as an in vivo non-invasive tumor margin scanner after further investigations in the future.

Bioelectrical Impedance Spectroscopy for Monitoring Mammalian Cells and Tissues under Different Frequency Domains: A Review

Bioelectrical impedance analysis and bioelectrical impedance spectroscopy (BIA/BIS) of tissues reveal important information on molecular composition and physical structure that is useful in diagnostics and prognostics. The heterogeneity in structural elements of cells, tissues, organs, and the whole human body, the variability in molecular composition arising from the dynamics of biochemical reactions, and the contributions of inherently electroresponsive components, such as ions, proteins, and polarized membranes, have rendered bioimpedance challenging to interpret but also a powerful evaluation and monitoring technique in biomedicine. BIA/BIS has thus become the basis for a wide range of diagnostic and monitoring systems such as plethysmography and tomography. The use of BIA/BIS arises from (i) being a noninvasive and safe measurement modality, (ii) its ease of miniaturization, and (iii) multiple technological formats for its biomedical implementation. Considering the dependency of the absolute and relative values of impedance on frequency, and the uniqueness of the origins of the α-, β-, δ-, and γ-dispersions, this targeted review discusses biological events and underlying principles that are employed to analyze the impedance data based on the frequency range. The emergence of BIA/BIS in wearable devices and its relevance to the Internet of Medical Things (IoMT) are introduced and discussed.

Machine Learning-Based Classification of Abnormal Liver Tissues Using Relative Permittivity

The search for non-invasive, fast, and low-cost diagnostic tools has gained significant traction among many researchers worldwide. Dielectric properties calculated from microwave signals offer unique insights into biological tissue. Material properties, such as relative permittivity (εr) and conductivity (σ), can vary significantly between healthy and unhealthy tissue types at a given frequency. Understanding this difference in properties is key for identifying the disease state. The frequency-dependent nature of the dielectric measurements results in large datasets, which can be postprocessed using artificial intelligence (AI) methods. In this work, the dielectric properties of liver tissues in three mouse models of liver disease are characterized using dielectric spectroscopy. The measurements are grouped into four categories based on the diets or disease state of the mice, i.e., healthy mice, mice with non-alcoholic steatohepatitis (NASH) induced by choline-deficient high-fat diet, mice with NASH induced by western diet, and mice with liver fibrosis. Multi-class classification machine learning (ML) models are then explored to differentiate the liver tissue groups based on dielectric measurements. The results show that the support vector machine (SVM) model was able to differentiate the tissue groups with an accuracy up to 90%. This technology pipeline, thus, shows great potential for developing the next generation non-invasive diagnostic tools.

Low-Cost Antenna-Array-Based Metamaterials for Non-Invasive Early-Stage Breast Tumor Detection in the Human Body

Microstrip patch antennas have been used in many applications since their appearance. Despite their great promise, their narrow bandwidth and the loss at high-frequency bands have limited their usage in medical applications. This work proposes a developed low-cost microstrip patch antenna suitable for microwave imaging (MWI) applications within the wideband frequency range. The proposed antenna is loaded with an artificial magnetic conductor (AMC) to improve the antenna performance. The simulated results obtained using computer simulation technology (CST) indicate that the presence of the AMC has improved the frequency selectivity of the antenna at 8.6 GHz with a peak realized gain of 9.90443 dBi and 10.61 dBi for simulated and measured results, respectively. The proposed microstrip antenna has been fabricated to validate the simulated results, and its performance is tested experimentally. Additionally, the fidelity factor of face-to-face (FtF) and side-by-side (SbS) scenarios have been presented. The breast phantom models with a tumor and the antenna operating as a transceiver have been numerically simulated for the application of cancer tumor cell detection. The work will have a significant impact on the design of electromagnetic biosensors.

Water Dynamics in Cancer Cells: Lessons from Quasielastic Neutron Scattering

The severity of the cancer statistics around the globe and the complexity involving the behavior of cancer cells inevitably calls for contributions from multidisciplinary areas of research. As such, materials science became a powerful asset to support biological research in comprehending the macro and microscopic behavior of cancer cells and untangling factors that may contribute to their progression or remission. The contributions of cellular water dynamics in this process have always been debated and, in recent years, experimental works performed with Quasielastic neutron scattering (QENS) brought new perspectives to these discussions. In this review, we address these works and highlight the value of QENS in comprehending the role played by water molecules in tumor cells and their response to external agents, particularly chemotherapy drugs. In addition, this paper provides an overview of QENS intended for scientists with different backgrounds and comments on the possibilities to be explored with the next-generation spectrometers under construction.

Dopingless Negative Capacitance Ferroelectric TFET for Breast Cancer Cells Detection: Design and Sensitivity Analysis

The current research article reports the electrical detection of breast cancer cell lines (MDA-MB-231, Hs578T, T47D, and MCF-7) by deploying dopingless negative capacitance (NC) ferroelectric (FE) tunnel field-effect transistor (DL-FE-TFET). This device has a double dual metal gate and two nanocavities engraved underneath both gate electrodes for higher detection sensitivity. Our work reports the detection of nontumorigenic cell (MCF-10A) and breast cancer cell lines by combining the NC effect of FE material and dopingless technology synergistically. Here, FE material amplifies the applied gate bias intrinsically. The in-depth electrostatic analysis in terms of surface potential, carrier concentration, energy band diagram, drive current, and electric field has been depicted. Variation of the dielectric constant of these breast cancerous cell lines dictates the detection mechanism in our reported biosensor. The sensitivity has been analyzed in terms of drive current, I_ON/I_OFF ratio, [Formula: see text], and transconductance. The optimized cavity structure demonstrates significantly high drain current sensitivity of the order of 2.88×10⁹ and I_ON/I_OFF ratio sensitivity of the order of 3.2×10⁵ . In addition, the effect of device geometry variation, such as cavity length and FE layer thickness on the drain current sensitivity and I_ON/I_OFF sensitivity, transconductance sensitivity ( S_gm ), and threshold voltage sensitivity ( [Formula: see text]) of the device, has also been investigated. This device structure may be deployed for the array-based screening and diagnosis of breast cancer cells lines, with additional benefits including a simpler mechanism of transduction, cost effectiveness, technology compatibility with CMOS process, adjustable electrical response, and reproducibility.

Recent advances in dielectrophoresis toward biomarker detection: A summary of studies published between 2014 and 2021

Dielectrophoresis is a well-understood phenomenon that has been widely utilized in biomedical applications. Recent advancements in miniaturization have contributed to the development of dielectrophoretic-based devices for a wide variety of biomedical applications. In particular, the integration of dielectrophoresis with microfluidics, fluorescence, and electrical impedance has produced devices and techniques that are attractive for screening and diagnosing diseases. This review article summarizes the recent utility of dielectrophoresis in assays of biomarker detection. Common screening and diagnostic biomarkers, such as cellular, protein, and nucleic acid, are discussed. Finally, the potential use of recent developments in machine learning approaches toward improving biomarker detection performance is discussed. This review article will be useful for researchers interested in the recent utility of dielectrophoresis in the detection of biomarkers and for those developing new devices to address current gaps in dielectrophoretic biomarker detection.

Correlation between electrical characteristics and biomarkers in breast cancer cells

Both electrical properties and biomarkers of biological tissues can be used to distinguish between normal and diseased tissues, and the correlations between them are critical for clinical applications of conductivity (σ) and permittivity (ε); however, these correlations remain unknown. This study aimed to investigate potential correlations between electrical characteristics and biomarkers of breast cancer cells (BCC). Changes in σ and ε of different components in suspensions of normal cells and BCC were analyzed in the range of 200 kHz-5 MHz. Pearson's correlation coefficient heatmap was used to investigate the correlation between σ and ε of the cell suspensions at different stages and biomarkers of cell growth and microenvironment. σ and ε of the cell suspensions closely resembled those of tissues. Further, the correlations between Na⁺/H⁺ exchanger 1 and ε and σ of cell suspensions were extremely significant among all biomarkers (p_ε < 0.001; p_σ < 0.001). There were significant positive correlations between cell proliferation biomarkers and ε and σ of cell suspensions (p_ε/σ < 0.05). The microenvironment may be crucial in the testing of cellular electrical properties. ε and σ are potential parameters to characterize the development of breast cancer.

A Preclinical System Prototype for Focused Microwave Breast Hyperthermia Guided by Compressive Thermoacoustic Tomography

OBJECTIVE

As a newly developed technique, focused microwave breast hyperthermia (FMBH) can provide accurate and cost-effective treatment of breast tumors with low side effect. A clinically feasible FMBH system requires a guidance technique to monitor the microwave power distribution in the breast. Compressive thermoacoustic tomography (CTT) is a suitable guidance approach for FMBH, which is more cost-effective than MRI. However, no experimental validation based on a realized FMBH-CTT system has been reported, which greatly hinders the further advancement of this novel approach.

METHODS

We developed a preclinical system prototype for the FMBH-CTT technique, containing a microwave phased antenna array, a microwave source, an ultrasound transducer array and associated data acquisition module.

RESULTS

Experimental results employing homogeneous and inhomogeneous breast-mimicking phantoms demonstrate that the CTT technique can offer reliable guidance for the entire process of the FMBH. In addition, small phase noises do not deteriorate the overall performance of the system prototype.

CONCLUSION

The realized preclinical FMBH-CTT system prototype is capable for noninvasive, accurate and low-side-effect breast tumor treatment with effective guidance.

SIGNIFICANCE

The experimentally validated FMBH-CTT system prototype provides a feasible paradigm for CTT guided FMBH, establishes a practical platform for future improvement of this technique, and paves the way for potential clinical translation.

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.

Evaluating Performance of Microwave Image Reconstruction Algorithms: Extracting Tissue Types with Segmentation Using Machine Learning

Evaluating the quality of reconstructed images requires consistent approaches to extracting information and applying metrics. Partitioning medical images into tissue types permits the quantitative assessment of regions that contain a specific tissue. The assessment facilitates the evaluation of an imaging algorithm in terms of its ability to reconstruct the properties of various tissue types and identify anomalies. Microwave tomography is an imaging modality that is model-based and reconstructs an approximation of the actual internal spatial distribution of the dielectric properties of a breast over a reconstruction model consisting of discrete elements. The breast tissue types are characterized by their dielectric properties, so the complex permittivity profile that is reconstructed may be used to distinguish different tissue types. This manuscript presents a robust and flexible medical image segmentation technique to partition microwave breast images into tissue types in order to facilitate the evaluation of image quality. The approach combines an unsupervised machine learning method with statistical techniques. The key advantage for using the algorithm over other approaches, such as a threshold-based segmentation method, is that it supports this quantitative analysis without prior assumptions such as knowledge of the expected dielectric property values that characterize each tissue type. Moreover, it can be used for scenarios where there is a scarcity of data available for supervised learning. Microwave images are formed by solving an inverse scattering problem that is severely ill-posed, which has a significant impact on image quality. A number of strategies have been developed to alleviate the ill-posedness of the inverse scattering problem. The degree of success of each strategy varies, leading to reconstructions that have a wide range of image quality. A requirement for the segmentation technique is the ability to partition tissue types over a range of image qualities, which is demonstrated in the first part of the paper. The segmentation of images into regions of interest corresponding to various tissue types leads to the decomposition of the breast interior into disjoint tissue masks. An array of region and distance-based metrics are applied to compare masks extracted from reconstructed images and ground truth models. The quantitative results reveal the accuracy with which the geometric and dielectric properties are reconstructed. The incorporation of the segmentation that results in a framework that effectively furnishes the quantitative assessment of regions that contain a specific tissue is also demonstrated. The algorithm is applied to reconstructed microwave images derived from breasts with various densities and tissue distributions to demonstrate the flexibility of the algorithm and that it is not data-specific. The potential for using the algorithm to assist in diagnosis is exhibited with a tumor tracking example. This example also establishes the usefulness of the approach in evaluating the performance of the reconstruction algorithm in terms of its sensitivity and specificity to malignant tissue and its ability to accurately reconstruct malignant tissue.

Malignant cell characterization via mathematical analysis of bio impedance and optical properties

Diagnosis in the early stage of breast cancer is crucial for the onset of preliminary treatment. Non-radiative bioimpedance measurement in the microwave frequency range can contribute to electrode-medium interface error and the malaise of electrode placement on the patient to take measurements. These reasons account for alternate diagnosis procedure and improved reliability of retrieved mensuration. Non-invasive optical diagnosis in the near infra-red (NIR) and visible light of the electromagnetic range is the shifting paradigm for healthcare diagnosis. An accurate quantitative measurement is unparalleled to circumvent false positives. The focus of this paper is to perform quantitative mathematical analysis for bioimpedance and optical properties for sample breast cancer cells for meticulous interpretation of malignant cell diagnosis. The analytical solution of the Cole-Cole plot, relaxation frequency, and capacitance measurement showed reliability with previous experimental findings. The dissimilitude of the frequency-dependent refractive index measurement of the malignant and healthy cell can be used by clinicians for pronouncement. The diffusion theory is also used to interpret the pathlength of the source light particle and the absorption property of the malignant cell. The synergistic analytical solutions of the bioimpedance and optical parameters can be used by licensed Physicians or Clinical Practitioners (CP) to meticulously interpret the diagnosis result. The quantitative parameters obtained from the dispersed bandwidth range from microwave to visible light offers a comprehensive understanding of the biophysical properties of the malignant cell.

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.