Special Issue "Electromagnetic Technologies for Medical Diagnostics: Fundamental Issues, Clinical Applications and Perspectives"

A special issue of Diagnostics (ISSN 2075-4418).

Deadline for manuscript submissions: 31 October 2018

Special Issue Editors

Guest Editor
Dr. Lorenzo Crocco

IREA - Institute for the Electromagnetic Sensing of the Environment;
CNR - National Research Council of Italy, Via Diocleziano 328, I-80124 Naples, Italy
Website | E-Mail
Interests: electromagnetics; imaging; radar; inverse problems
Guest Editor
Dr. Panos Kosmas

Department of Informatics, King’s College London, UK
Website | E-Mail
Interests: computational electrodynamics (FDTD); antennas and microwave engineering; physics-based signal processing; medical imaging

Special Issue Information

Dear Colleagues,

Electromagnetic (EM) technologies for medical imaging represent an emerging alternative diagnostic modality, which is attracting the attention of many researchers worldwide, thanks to unique features such as the non-ionizing nature and the intrinsic low cost of equipment. At the European level, this research area has gained significant momentum through two COST Actions (MiMed—TD1301; EMF-MED BM1309), which have brought together the efforts of a number of scholars and practitioners in the push towards translating this emerging technology into clinics.

This Special Issue aims at providing a comprehensive picture on this lively research area by gathering contributions covering all aspects related to this research, starting from fundamental questions (e.g., dielectric property measurements of tissue, development of imaging methodologies, modelling of EM scattering), to experimental validation in laboratory and in vivo, down to clinical trials and applications (e.g., breast cancer imaging, neuroimaging, biomedical sensing and monitoring of vital parameters). Contributions may be, therefore, related, but not limited, to microwave imaging, microwave radiometry, combined modalities, electrical property tomography, and low frequency imaging methods, such as electric impedance tomography, contrast enhanced imaging, and bioradar.

Dr. Lorenzo Crocco
Dr. Panos Kosmas
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diagnostics is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 550 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Microwave imaging
  • Inverse scattering
  • Cancer
  • Electromagnetics
  • Biomedical radar
  • Biomedical sensing

Published Papers (7 papers)

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Research

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Open AccessArticle Challenges and Potential Solutions of Psychophysiological State Monitoring with Bioradar Technology
Diagnostics 2018, 8(4), 73; https://doi.org/10.3390/diagnostics8040073
Received: 18 September 2018 / Revised: 3 October 2018 / Accepted: 15 October 2018 / Published: 17 October 2018
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Abstract
Psychophysiological state monitoring provides a promising way to detect stress and accurately assess wellbeing. The purpose of the present work was to investigate the advantages of utilizing a new unobtrusive multi-transceiver system on the accuracy of remote psychophysiological state monitoring by means of
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Psychophysiological state monitoring provides a promising way to detect stress and accurately assess wellbeing. The purpose of the present work was to investigate the advantages of utilizing a new unobtrusive multi-transceiver system on the accuracy of remote psychophysiological state monitoring by means of a bioradar technique. The technique was tested in laboratory conditions with the participation of 35 practically healthy volunteers, who were asked to perform arithmetic and physical workload tests imitating different types of stressors. Information about any variation in vital signs, registered by a bioradar with two transceivers, was used to detect mental or physical stress. Processing of the experimental results showed that the designed two-channel bioradar can be used as a simple and relatively easy approach to implement a non-contact method for stress monitoring. However, individual specificity of physiological responses to mental and physical workloads makes the creation of a universal stress-detector classifier that is suitable for people with different levels of stress tolerance a challenging task. For non-athletes, the proposed method allows classification of calm state/mental workload and calm state/physical workload with an accuracy of 89% and 83% , respectively, without the usage of any additional a priori information on the subject. Full article
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Open AccessArticle Effects of the Plastic of the Realistic GeePS-L2S-Breast Phantom
Diagnostics 2018, 8(3), 61; https://doi.org/10.3390/diagnostics8030061
Received: 29 June 2018 / Revised: 28 August 2018 / Accepted: 29 August 2018 / Published: 1 September 2018
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Abstract
A breast phantom developed at the Supelec Institute was interrogated to study its suitability for microwave tomography measurements. A microwave measurement system based on 16 monopole antennas and a vector network analyzer was used to study how the S-parameters are influenced by insertion
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A breast phantom developed at the Supelec Institute was interrogated to study its suitability for microwave tomography measurements. A microwave measurement system based on 16 monopole antennas and a vector network analyzer was used to study how the S-parameters are influenced by insertion of the phantom. The phantom is a 3D-printed structure consisting of plastic shells that can be filled with tissue mimicking liquids. The phantom was filled with different liquids and tested with the measurement system to determine whether the plastic has any effects on the recovered images or not. Measurements of the phantom when it is filled with the same liquid as the surrounding coupling medium are of particular interest. In this case, the phantom plastic has a substantial effects on the measurements which ultimately detracts from the desired images. Full article
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Open AccessArticle Comparison of X-ray-Mammography and Planar UWB Microwave Imaging of the Breast: First Results from a Patient Study
Diagnostics 2018, 8(3), 54; https://doi.org/10.3390/diagnostics8030054
Received: 25 June 2018 / Revised: 9 August 2018 / Accepted: 15 August 2018 / Published: 21 August 2018
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Abstract
Hemispherical and cylindrical antenna arrays are widely used in radar-based and tomography-based microwave breast imaging systems. Based on the dielectric contrast between healthy and malignant tissue, a three-dimensional image could be formed to locate the tumor. However, conventional X-ray mammography as the golden
[...] Read more.
Hemispherical and cylindrical antenna arrays are widely used in radar-based and tomography-based microwave breast imaging systems. Based on the dielectric contrast between healthy and malignant tissue, a three-dimensional image could be formed to locate the tumor. However, conventional X-ray mammography as the golden standard in breast cancer screening produces two-dimensional breast images so that a comparison between the 3D microwave image and the 2D mammogram could be difficult. In this paper, we present the design and realisation of a UWB breast imaging prototype for the frequency band from 1 to 9 GHz. We present a refined system design in light of the clinical usage by means of a planar scanning and compare microwave images with those obtained by X-ray mammography. Microwave transmission measurements were processed to create a two-dimensional image of the breast that can be compared directly with a two-dimensional mammogram. Preliminary results from a patient study are presented and discussed showing the ability of the proposed system to locate the tumor. Full article
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Open AccessArticle On-Site Validation of a Microwave Breast Imaging System, before First Patient Study
Diagnostics 2018, 8(3), 53; https://doi.org/10.3390/diagnostics8030053
Received: 29 June 2018 / Revised: 31 July 2018 / Accepted: 8 August 2018 / Published: 18 August 2018
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Abstract
This paper presents the Wavelia microwave breast imaging system that has been recently installed at the Galway University Hospital, Ireland, for a first-in-human pilot clinical test. Microwave breast imaging has been extensively investigated over the last two decades as an alternative imaging modality
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This paper presents the Wavelia microwave breast imaging system that has been recently installed at the Galway University Hospital, Ireland, for a first-in-human pilot clinical test. Microwave breast imaging has been extensively investigated over the last two decades as an alternative imaging modality that could potentially bring complementary information to state-of-the-art modalities such as X-ray mammography. Following an overview of the main working principles of this technology, the Wavelia imaging system architecture is presented, as are the radar signal processing algorithms that are used in forming the microwave images in which small tumors could be detectable for disease diagnosis. The methodology and specific quality metrics that have been developed to properly evaluate and validate the performance of the imaging system using complex breast phantoms that are scanned at controlled measurement conditions are also presented in the paper. Indicative results from the application of this methodology to the on-site validation of the imaging system after its installation at the hospital for pilot clinical testing are thoroughly presented and discussed. Given that the imaging system is still at the prototype level of development, a rigorous quality assessment and system validation at nominal operating conditions is very important in order to ensure high-quality clinical data collection. Full article
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Open AccessArticle Impact of Information Loss on Reconstruction Quality in Microwave Tomography for Medical Imaging
Diagnostics 2018, 8(3), 52; https://doi.org/10.3390/diagnostics8030052
Received: 20 June 2018 / Revised: 2 August 2018 / Accepted: 6 August 2018 / Published: 14 August 2018
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Abstract
This paper studies how limited information in data acquired by a wideband microwave tomography (MWT) system can affect the quality of reconstructed images. Limitations can arise from experimental errors, mismatch between the system and its model in the imaging algorithm, or losses in
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This paper studies how limited information in data acquired by a wideband microwave tomography (MWT) system can affect the quality of reconstructed images. Limitations can arise from experimental errors, mismatch between the system and its model in the imaging algorithm, or losses in the immersion and coupling medium which are required to moderate this mismatch. We also present a strategy for improving reconstruction performance by discarding data that is dominated by experimental errors. The approach relies on recording transmitted signals in a wide frequency range, and then correlating the data in different frequencies. We apply this method to our wideband MWT prototype, which has been developed in our previous work. Using this system, we present results from simulated and experimental data which demonstrate the practical value of the frequency selection approach. We also propose a K-neighbour method to identify low quality data in a robust manner. The resulting enhancement in imaging quality suggests that this approach can be useful for various medical imaging scenarios, provided that data from multiple frequencies can be acquired and used in the reconstruction process. Full article
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Open AccessArticle Diagnosing Breast Cancer with Microwave Technology: Remaining Challenges and Potential Solutions with Machine Learning
Diagnostics 2018, 8(2), 36; https://doi.org/10.3390/diagnostics8020036
Received: 14 April 2018 / Revised: 15 May 2018 / Accepted: 16 May 2018 / Published: 19 May 2018
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Abstract
Currently, breast cancer often requires invasive biopsies for diagnosis, motivating researchers to design and develop non-invasive and automated diagnosis systems. Recent microwave breast imaging studies have shown how backscattered signals carry relevant information about the shape of a tumour, and tumour shape is
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Currently, breast cancer often requires invasive biopsies for diagnosis, motivating researchers to design and develop non-invasive and automated diagnosis systems. Recent microwave breast imaging studies have shown how backscattered signals carry relevant information about the shape of a tumour, and tumour shape is often used with current imaging modalities to assess malignancy. This paper presents a comprehensive analysis of microwave breast diagnosis systems which use machine learning to learn characteristics of benign and malignant tumours. The state-of-the-art, the main challenges still to overcome and potential solutions are outlined. Specifically, this work investigates the benefit of signal pre-processing on diagnostic performance, and proposes a new set of extracted features that capture the tumour shape information embedded in a signal. This work also investigates if a relationship exists between the antenna topology in a microwave system and diagnostic performance. Finally, a careful machine learning validation methodology is implemented to guarantee the robustness of the results and the accuracy of performance evaluation. Full article
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Review

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Open AccessReview Open-Ended Coaxial Probe Technique for Dielectric Measurement of Biological Tissues: Challenges and Common Practices
Diagnostics 2018, 8(2), 40; https://doi.org/10.3390/diagnostics8020040
Received: 30 April 2018 / Revised: 24 May 2018 / Accepted: 2 June 2018 / Published: 5 June 2018
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Abstract
Electromagnetic (EM) medical technologies are rapidly expanding worldwide for both diagnostics and therapeutics. As these technologies are low-cost and minimally invasive, they have been the focus of significant research efforts in recent years. Such technologies are often based on the assumption that there
[...] Read more.
Electromagnetic (EM) medical technologies are rapidly expanding worldwide for both diagnostics and therapeutics. As these technologies are low-cost and minimally invasive, they have been the focus of significant research efforts in recent years. Such technologies are often based on the assumption that there is a contrast in the dielectric properties of different tissue types or that the properties of particular tissues fall within a defined range. Thus, accurate knowledge of the dielectric properties of biological tissues is fundamental to EM medical technologies. Over the past decades, numerous studies were conducted to expand the dielectric repository of biological tissues. However, dielectric data is not yet available for every tissue type and at every temperature and frequency. For this reason, dielectric measurements may be performed by researchers who are not specialists in the acquisition of tissue dielectric properties. To this end, this paper reviews the tissue dielectric measurement process performed with an open-ended coaxial probe. Given the high number of factors, including equipment- and tissue-related confounders, that can increase the measurement uncertainty or introduce errors into the tissue dielectric data, this work discusses each step of the coaxial probe measurement procedure, highlighting common practices, challenges, and techniques for controlling and compensating for confounders. Full article
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