3-D Microwave Imaging for Breast Cancer

We introduce a novel microwave imaging technique for breast cancer detection. Our approach provides a one-pass inverse image solution, which is completely new and unprecedented, unrelated to tomography or radar-based algorithms, and unburdened by the optimization toil which lies at the heart of numerical schemes. It operates effectively at a single frequency, without requiring the bandwidth of radar techniques. Underlying this new method is our unique Field Mapping Algorithm (FMA), which transforms electromagnetic fields acquired upon one surface, be it through outright measurement or some auxiliary computation, into those upon another in an exact sense

Application of the inhomogeneous Lippmann-Schwinger equation to inverse scattering problems

In this paper we present a hybrid approach to numerically solve two-dimensional electromagnetic inverse scattering problems, whereby the unknown scatterer is hosted by a possibly inhomogeneous background. The approach is `hybrid' in that it merges a qualitative and a quantitative method to optimize the way of exploiting the a priori information on the background within the inversion procedure, thus improving the quality of the reconstruction and reducing the data amount necessary for a satisfactory result. In the qualitative step, this a priori knowledge is utilized to implement the linear sampling method in its near-field formulation for an inhomogeneous background, in order to identify the region where the scatterer is located. On the other hand, the same a priori information is also encoded in the quantitative step by extending and applying the contrast source inversion method to what we call the `inhomogeneous Lippmann-Schwinger equation': the latter is a generalization of the classical Lippmann-Schwinger equation to the case of an inhomogeneous background, and in our paper is deduced from the differential formulation of the direct scattering problem to provide the reconstruction algorithm with an appropriate theoretical basis. Then, the point values of the refractive index are computed only in the region identified by the linear sampling method at the previous step. The effectiveness of this hybrid approach is supported by numerical simulations presented at the end of the paper.Comment: accepted in SIAM Journal on Applied Mathematic

Cancer Detection Using Advanced UWB Microwave Technology

Medical diagnosis and subsequent treatment efficacy hinge on innovative imaging modalities. Among these, Microwave Imaging (MWI) has emerged as a compelling approach, offering safe and cost-efficient visualization of the human body. This comprehensive research explores the potential of the Huygens principle-based microwave imaging algorithm, specifically focusing on its prowess in cancer, lesion, and infection detection. Extensive experimentation employing meticulously crafted phantoms validates the algorithm’s robustness. In the context of lung infections, this study harnesses the power of Huygens-based microwave imaging to detect lung-COVID-19 infections. Employing Microstrip and horn antennas within a frequency range of 1 to 5 GHz and a multi-bistatic setup in an anechoic chamber, the research utilizes phantoms mimicking human torso dimensions and dielectric properties. Notably, the study achieves a remarkable detection capability, attaining a signal-to-clutter ratio of 7 dB during image reconstruction using S21 signals.A higher SCR ratio indicates better contrast and clarity of the detected inclusion, which is essential for reliable medical imaging. It is noteworthy that this achievement is realized in free space without necessitating coupling liquid, underscoring the algorithm’s practicality. Furthermore, the research delves into the validation of Huygens Principle (HP)-based microwave imaging in detecting intricate lung lesions. Utilizing a meticulously designed multi-layered phantom with characteristics closely mirroring human anatomy, the study spans frequency bands from 0.5 GHz to 3 GHz within an anechoic chamber. The outcomes are compelling, demonstrating consistent lesion detection within reconstructed images. Impressively, the signal-to-clutter ratio post-artifact removal surges to 13.4 dB, affirming the algorithm’s potential in elevating medical imaging precision. To propel the capabilities of MWI further, this research unveils a novel device: 3D microwave imaging rooted in Huygens principle. Leveraging MammoWave device’s capabilities, the study ventures into 3D image reconstruction. Dedicated phantoms housing 3D structured inclusions, each embodying distinct dielectric properties, serve as the experimental bedrock. Through an intricate interplay of data acquisition and processing, the study attains a laudable feat: seamless 3D visualization of inclusions across various z-axis planes, accompanied by minimal dimensional error not exceeding 7.5%. In a parallel exploration, spiral-like measurement configurations enter the spotlight. These configurations, meticulously tailored along the z-axis, yield promising results. The research unveils an innovative approach to reducing measurement time while safeguarding imaging fidelity. Notably, spiral-like measurements achieve a notable 50% reduction in measurement time, albeit with slight trade-offs. Signal-to-clutter ratios experience a modest reduction, and there is a minor increase in dimensional analysis error, which remains within the confines of 3.5%. The research findings serve as a testament to MWI’s efficacy across diverse medical domains. The success in lung infection and lesion detection underscores its potential impact on medical diagnostics. Moreover, the foray into 3D imaging and the strategic exploration of measurement configurations lay the foundation for future advancements in microwave imaging technologies. As a result, the outcomes of this research promise to reshape the landscape of accurate and efficient medical imaging modalities

Ocjena preciznog dielektičnog modela i izabranih patenta o otkrivanju raka dojke pomoću mikrovalova

Advances in microwave breast cancer detection and imaging during last decade are reported in this review paper. An introduction to breast cancer and detection methods and detailed information about microwave imaging and selected patents are presented. The advantages and disadvantages of the presented patents and also state of breast cancer detection and imaging are discussed. Microwave imaging for breast tumor detection is considered to be promising, as it is believed that there is a significant or detectable contrast in malignant, benign and normal tissues over a broad frequency range. Also, there have been many dielectric models, especially the double Debye model has been used to define the dielectric response of different biological tissues. On the other hand, double Debye model is not accurate for human breast tissue because there are knowledge limitations about the structure, dynamics, and macroscopic behavior of breast tissue. It is vital that, according to frequency, accurate dielectric model should be chosen in detection systems.Ovaj rad govori o naprecima u otkrivanju i snimanju raka dojke pomoću mikrovalova u posljednjem desetljeću. Dan je uvod o raku dojke i metodama otkrivanja te detaljne informacije o snimanju pomoću mikrovalova i izabranim patentima. Raspravljene su prednosti i nedostaci prezentiranih patenata kao i trenutno stanje u detektiranju i snimanju raka dojke. Snimanje mikrovalovima kako bi se otkrio rak dojke metoda je od koje se mnogo očekuje, pošto se smatra kako postoje znatni ili primjetni kontrasti između malignih, benignih i normalnih tkiva kroz široki raspon frekvencija. Također, postoje mnogi dielektrični modeli, posebno se dvostruki Debye model koristio u definiranju dielektričnog odziva raznih bioloških tkiva. S druge strane, dvostruki Debye model nije precizan prilikom korištenja za ljudska tkiva, jer postoje ograničenja u saznanjima oko strukture, dinamike i makroskopskog ponašanja tkiva dojke. Neophodno je, ovisno o frekvenciji, izabrati ispravan dielektrični model u sustavima za detekciju

Dielectric properties of colon polyps, cancer, and normal mucosa: Ex vivo measurements from 0.5 to 20 GHz

This is the accepted version of the following article: Guardiola, M. , Buitrago, S. , Fernández‐Esparrach, G. , O'Callaghan, J. M., Romeu, J. , Cuatrecasas, M. , Córdova, H. , González Ballester, M. Á. and Camara, O. (2018), Dielectric properties of colon polyps, cancer, and normal mucosa: Ex vivo measurements from 0.5 to 20 GHz. Med. Phys., 45: 3768-3782. doi:10.1002/mp.13016, which has been published in final form at https://aapm.onlinelibrary.wiley.com/doi/pdf/10.1002/mp.13016. This article may be used for non-commercial purposes in accordance with the Wiley Self-Archiving Policy [http://olabout.wiley.com/WileyCDA/Section/id-820227.html].Colorectal cancer is highly preventable by detecting and removing polyps, which are the precursors. 20 Currently, the most accurate test is colonoscopy, but still misses 22% of polyps due to visualization limitations. In this paper we preliminary assess the potential of microwave imaging and dielectric properties (e.g. complex permittivity) as a complementary method for detecting polyps and cancer tissue in the colon. The dielectric properties of biological tissues have been used in a wide variety of applications, including safety assessment of wireless technologies and design of medical diagnostic or therapeutic techniques 25 (microwave imaging, hyperthermia and ablation). The main purpose of this work is to measure the complex permittivity of different types of colon polyps, cancer and normal mucosa in ex vivo human samples to study if the dielectric properties are appropriate for classification purposes.Peer ReviewedPostprint (author's final draft

Lung tumour detection using ultra-wideband microwave imaging approach

The use of Ultra-Wideband (UWB) microwave imaging for tumour detection has gained increasing popularity within the bio-medical field. Microwave imaging turned out more efficiently accurate to some body parts such as breast and brain imaging. This work presents on the possibility and the effectiveness of UWB microwave  imaging technique on lung tumour detection. Simple technique of using reflection method was studied and then applied for lung tumour detection by using UWB antenna. The simulated results show that the proposed method is capable to detect a lung tumour with minimum radius size of 4 mm for different positions inside the lungs at the frequency of 3.67 GHz. It is a promising technique to be further developed in modern UWB imaging systems which demand perfect results at very low cost.Keywords: ultra-wideband; microwave imaging; lung tumour; Antenna

FDTD Investigations into UWB Radar Technique of Breast Tumor Detection and Location

In this paper, a finite difference time domain (FDTD) method is applied to investigate capabilities of an ultra-wide band (UWB) radar system to detect and locate a breast tumor. The investigations are divided into three parts. The first part concerns an EM field analysis of a phantom formed by a plastic container with liquid and a small highly reflecting target. In the second part, a three-dimensional numerical breast model is used to perform more advanced studies. In the carried out 3D FDTD simulations, a quasi-plane wave is used as an incident wave. Various time snap shots of the electromagnetic field are recorded to learn about the physical phenomenon of reflection and scattering in different layers of the phantoms. The third part of the investigations concerns a two dimensional (cylindrical) image reconstruction, which is performed by means of 2D FDTD. The obtained results should form the ground for working out suitable guidelines for designing an optimal microwave breast imaging apparatus based on the UWB radar technique

The effects of dielectric values, breast and tumor size on the detection of breast tumor

Although breast cancer is the second main cause of female deaths after lung cancer, early diagnosis plays a crucial role to diminish the death rate. Many techniques have been improved to detect the cancerous cells. At different microwave frequencies, the malignant cells indicate different electrical characteristics as compared to the normal cells. According to these frequencies, the breast tissue is more permeable than other tissues such as the brain and muscle. Due to this property of the breast tissue, microwaves can be used for the detection of breast cancer. In this study, the breast prototype was modelled using the CST STUDIO SUITE electromagnetic simulation software with respect to different breast size, tumor size and dielectric values tested at a range of the 0-3.0 GHz frequency. The objective of this paper is to investigate the effects of each factor and the interactions of factors on detecting cancer cells using the factorial analysis. The results indicate that the factors such as fat and skin permittivity, tumor and breast sizes are more effective in the detection of breast tumor. Although the effect of fibro permittivity is not significant alone, there are considerable interaction effects of a large breast size and small tumor size through low-to-high values of fibro permittivity. Furthermore, the combinations of a breast radius smaller than almost 8.5 cm with a high level tumor radius and breast radius larger than 8.5 cm with a low level tumor radius are desirable for lessening the return loss value

Tissue temperature monitoring using thermoacoustic and photoacoustic techniques

Real-time temperature monitoring with high spatial resolution (~1 mm) and high temperature sensitivity (1 °C or better) is needed for the safe deposition of heat energy in surrounding healthy tissue and efficient destruction of tumor and abnormal cells during thermotherapy. A temperature sensing technique using thermoacoustic and photoacoustic measurements combined with a clinical Philips ultrasound imaging system (iU22) has been explored in this study. Using a tissue phantom, this noninvasive method has been demonstrated to have high temporal resolution and temperature sensitivity. Because both photoacoustic and thermoacoustic signal amplitudes depend on the temperature of the source object, the signal amplitudes can be used to monitor the temperature. The signal is proportional to the dimensionless Grueneisen parameter of the object, which in turn varies with the temperature of the object. A temperature sensitivity of 0.5 °C was obtained at a temporal resolution as short as 3.6 s with 50 signal averages

Classifying Breast Tumors using Medical Microwave Radar Imaging

Medical Microwave Imaging (MMI) has been studied in the past years to develop techniques to detect breast cancer at the earliest stages of development. Particularly, ultra-wideband (UWB) micro-wave radar imaging systems can detect and classify tumors as benign or malignant since this technique yields information about the size and shape of tumors. In this study we used this technology to classify tumors. The primary goal of this dissertation is two-folded. First, producing breast tumor numerical mod-els and using them in 2D MMI simulations that recreate the conditions of a UWB microwave radar imaging system. The breast tumor numerical produced resemble real tumor morphologies since they are made from breast MRI exams segmentations. Second, the data of the backscattered UWB microwave signals produced by the MMI simulations was used to classify tumors according to their size and histol-ogy, which is relevant to assess potential of UWB microwave radar imaging systems as a reliable alter-native method for the classification of breast tumors in the field of Medical Microwave Imaging. The Classification Algorithms used in this work were Pseudo Linear Discriminant Analysis (Pseudo-LDA), Pseudo Quadratic Discriminant Analysis (pseudo-QDA), and k-Nearest Neighbors (KNN), alongside with a feature extraction algorithm – Principal Component Analysis (PCA).A Imagem Médica por Microondas (do inglês, MMI) tem sido estudada nos últimos anos de forma a desenvolver técnicas de deteção do cancro da mama nas primeiras fases de desenvolvimento. Em particular, os sistemas de imagem de radar por microondas em banda ultralarga (do inglês UWB) podem detetar e classificar os tumores como benignos ou malignos, uma vez que esta técnica produz informação sobre o tamanho e a forma dos tumores. Neste estudo, utilizámos esta tecnologia para classificar os tumores. A dissertação tem dois objetivos principais. Primeiro, produzir fantomas de tumores mamários e utilizá-los em simulações de MMI em 2D que recriam as condições de um sistema de imagem de radar por microondas UWB. Os fantomas numéricos de tumores mamários produzidos possuem morfologias semelhantes a tumores reais, uma vez que são feitos a partir de segmentações de exames de ressonância magnética da mama. Em segundo lugar, as reflexões dos sinais de microondas UWB produzidos pelas simulações de MMI foram utilizados para classificar tumores de acordo com o seu tamanho e histologia, o que é relevante para avaliar o potencial dos sistemas de imagem de radar por microondas UWB como um método alternativo e fiável para a classificação de tumores mamários no campo da MMI. Os Algo-ritmos de Classificação utilizados neste trabalho foram a Pseudo Linear Discriminant Analysis (Pseudo-LDA), Pseudo Quadratic Discriminant Analysis (pseudo-QDA), e a K-Nearest Neighbors (KNN), jun-tamente com um algoritmo de extração de features - Análise de Componentes Principais (do inglês PCA)