Foam density mapping via THz imaging.

Plastic foams, near-ubiquitous in everyday life and industry, show properties that depend primarily on density. Density measurement, although straightforward in principle, is not always easy. As such, while several methods are available, plastic foam industry is not yet supported with a standard technique that effectively enables to control density maps. To overcome this issue, this paper proposes Terahertz (THz) time-of-flight imaging using normal reflection measurements as a fast, relatively cheap, contactless, non-destructive and non-dangerous way to map plastic foam density, based on the expected relationship between density and refractive index. The approach is demonstrated in the case of polypropylene foams. First, the relationship between the estimated effective refractive index and the polypropylene foam density is derived by characterizing a set of carefully crafted samples having uniform density in the range 70-900 kg/m3. The obtained calibration curve subtends a linear relationship between the density and the refractive index in the range of interest. This relationship is validated against a set of test samples, whose estimated average densities are consistent with the nominal ones, with an absolute error lower than 10 kg/m3 and a percentage error on the estimate of 5%. Exploiting the calibration curve, it is possible to build quantitative images depicting the spatial distribution of the sample density. THz images are able to reveal the non-uniform density distribution of some samples, which cannot be appreciated from visual inspection. Finally, the complex spatial density pattern of a graded foam sample is characterized and quantitatively compared with the density map obtained via X-ray microscopy. The comparison confirms that the proposed THz approach successfully determines the density pattern with an accuracy and a spatial scale variability compliant with those commonly required for plastic foam density estimate.

Hyperthermia Treatment Monitoring via Deep Learning Enhanced Microwave Imaging: A Numerical Assessment.

The paper deals with the problem of monitoring temperature during hyperthermia treatments in the whole domain of interest. In particular, a physics-assisted deep learning computational framework is proposed to provide an objective assessment of the temperature in the target tissue to be treated and in the healthy one to be preserved, based on the measurements performed by a microwave imaging device. The proposed concept is assessed in-silico for the case of neck tumors achieving an accuracy above 90%. The paper results show the potential of the proposed approach and support further studies aimed at its experimental validation.

Field and Temperature Shaping for Microwave Hyperthermia: Recent Treatment Planning Tools to Enhance SAR-Based Procedures.

The aim of the article is to provide a summary of the work carried out in the framework of a research project funded by the Italian Ministry of Research. The main goal of the activity was to introduce multiple tools for reliable, affordable, and high-performance microwave hyperthermia for cancer therapy. The proposed methodologies and approaches target microwave diagnostics, accurate in vivo electromagnetic parameters estimation, and improvement in treatment planning using a single device. This article provides an overview of the proposed and tested techniques and shows their complementarity and interconnection. To highlight the approach, we also present a novel combination of specific absorption rate optimization via convex programming with a temperature-based refinement method implemented to mitigate the effect of thermal boundary conditions on the final temperature map. To this purpose, numerical tests were carried out for both simple and anatomically detailed 3D scenarios for the head and neck region. These preliminary results show the potential of the combined technique and improvements in the temperature coverage of the tumor target with respect to the case wherein no refinement is adopted.

A Simple Differential Microwave Imaging Approach for In-Line Inspection of Food Products.

Microwave imaging has been recently proposed as alternative technology for in-line inspection of packaged products in the food industry, thanks to its non-invasiveness and the low-cost of the equipment. In this framework, simple and effective detection/imaging strategies, able to reveal the presence of foreign bodies that may have contaminated the product during the packaging stage, are needed to allow real-time and reliable detection, thus avoiding delays along the production line and limiting occurrence of false detections (either negative or positive). In this work, a novel detection/imaging approach meeting these requirements is presented. The approach performs the detection/imaging of the contaminant by exploiting the symmetries usually characterizing the food items. Such symmetries are broken by the presence of foreign bodies, thereby determining a differential signal that can be processed to reveal their presence. In so doing, the approach does not require the prior measurement of a reference, defect-free, item. With respect to the quite common case of homogeneous food packaged in circular plastic/glass jars, numerical analyses are provided to show the effectiveness of the proposed approach.

An Effective Framework for Deep-Learning-Enhanced Quantitative Microwave Imaging and Its Potential for Medical Applications.

Microwave imaging is emerging as an alternative modality to conventional medical diagnostics technologies. However, its adoption is hindered by the intrinsic difficulties faced in the solution of the underlying inverse scattering problem, namely non-linearity and ill-posedness. In this paper, an innovative approach for a reliable and automated solution of the inverse scattering problem is presented, which combines a qualitative imaging technique and deep learning in a two-step framework. In the first step, the orthogonality sampling method is employed to process measurements of the scattered field into an image, which explicitly provides an estimate of the targets shapes and implicitly encodes information in their contrast values. In the second step, the images obtained in the previous step are fed into a neural network (U-Net), whose duty is retrieving the exact shape of the target and its contrast value. This task is cast as an image segmentation one, where each pixel is classified into a discrete set of permittivity values within a given range. The use of a reduced number of possible permittivities facilitates the training stage by limiting its scope. The approach was tested with synthetic data and validated with experimental data taken from the Fresnel database to allow a fair comparison with the literature. Finally, its potential for biomedical imaging is demonstrated with a numerical example related to microwave brain stroke diagnosis.

A Simple Microwave Imaging System for Food Product Inspection through a Symmetry-Based Microwave Imaging Approach.

In the food industry, there is a growing demand for cost-effective methods for the inline inspection of food items able to non-invasively detect small foreign bodies that may have contaminated the product during the production process. Microwave imaging may be a valid alternative to the existing technologies, thanks to its inherently low-cost and its capability of sensing low-density contaminants. In this paper, a simple microwave imaging system specifically designed to enable the inspection of a large variety of food products is presented. The system consists of two circularly loaded antipodal Vivaldi antennas with a very large operative band, from 1 to 15 GHz, thus allowing a suitable spatial resolution for different food products, from mostly fatty to high water-content foods. The antennas are arranged in such a way as to collect a signal that can be used to exploit a recently proposed real-time microwave imaging strategy, leveraging the inherent symmetries that usually characterize food items. The system is experimentally characterized, and the achieved results compare favorably with the design specifications and numerical simulations. Relying on these positive results, the first experimental proof of the effectiveness of the entire system is presented confirming its efficacy.

Influence of Magnetic Scaffold Loading Patterns on Their Hyperthermic Potential Against Bone Tumors.

Magnetic scaffolds have been investigated as promising tools for the interstitial hyperthermia treatment of bone cancers, to control local recurrence by enhancing radio- and chemotherapy effectiveness. The potential of magnetic scaffolds motivates the development of production strategies enabling tunability of the resulting magnetic properties. Within this framework, deposition and drop-casting of magnetic nanoparticles on suitable scaffolds offer advantages such as ease of production and high loading, although these approaches are often associated with a non-uniform final spatial distribution of nanoparticles in the biomaterial. The implications and the influences of nanoparticle distribution on the final therapeutic application have not yet been investigated thoroughly. In this work, poly-caprolactone scaffolds are magnetized by loading them with synthetic magnetic nanoparticles through a drop-casting deposition and tuned to obtain different distributions of magnetic nanoparticles in the biomaterial. The physicochemical properties of the magnetic scaffolds are analyzed. The microstructure and the morphological alterations due to the reworked drop-casting process are evaluated and correlated to static magnetic measurements. THz tomography is used as an innovative investigation technique to derive the spatial distribution of nanoparticles. Finally, multiphysics simulations are used to investigate the influence on the loading patterns on the interstitial bone tumor hyperthermia treatment.

Experimental Validation of a Microwave System for Brain Stroke 3-D Imaging.

This paper experimentally validates the capability of a microwave prototype device to localize hemorrhages and ischemias within the brain as well as proposes an innovative calibration technique based on the measured data. In the reported experiments, a 3-D human-like head phantom is considered, where the brain is represented either with a homogeneous liquid mimicking brain dielectric properties or with ex vivo calf brains. The microwave imaging (MWI) system works at 1 GHz, and it is realized with a low-complexity architecture formed by an array of twenty-four printed monopole antennas. Each antenna is embedded into the "brick" of a semi-flexible dielectric matching medium, and it is positioned conformal to the head upper part. The imaging algorithm exploits a differential approach and provides 3-D images of the brain region. It employs the singular value decomposition of the discretized scattering operator obtained via accurate numerical models. The MWI system analysis shows promising reconstruction results and extends the device validation.

Towards a Microwave Imaging System for Continuous Monitoring of Liver Tumor Ablation: Design and In Silico Validation of an Experimental Setup.

Liver cancer is one of the most common liver malignancies worldwide. Thermal ablation has been recognized as a promising method for its treatment, with a significant impact on clinical practice. However, the treatment's effectiveness is heavily dependent on the experience of the clinician and would improve if paired with an image-guidance device for treatment monitoring. Conventional imaging modalities, such as computed tomography, ultrasound, and magnetic resonance imaging, show some disadvantages, motivating interest in alternative technologies. In this framework, microwave imaging was recently proposed as a potential candidate, being capable of implementing real-time monitoring by means of low-cost and portable devices. In this work, the in silico assessment of a microwave imaging device specifically designed for liver ablation monitoring is presented. To this end, an imaging experiment involving eight Vivaldi antennas in an array configuration and a practically realizable liver phantom mimicking the evolving treatment was simulated. In particular, since the actual phantom will be realized by 3D printing technology, the effect of the plastic shells containing tissues mimicking materials was investigated and discussed. The outcomes of this study confirm that the presence of printing materials does not impair the significance of the experiments and that the designed device is capable of providing 3D images of the ablated region conveying information on its extent and evolution. Moreover, the observed results suggest possible improvements to the system, paving the way for the next stage in which the device will be implemented and experimentally assessed in the same conditions as those simulated in this study.

Experimental Characterization of Spurious Signals in Magnetic Nanoparticles Enhanced Microwave Imaging of Cancer.

Magnetic nanoparticles enhanced microwave imaging relies on the capability of modulating the response of such nanocomponents at microwaves by means of a (low frequency) polarizing magnetic field. In medical imaging, this capability allows for the detection and imaging of tumors loaded with nanoparticles. As the useful signal is the one which arises from nanoparticles, it is crucial to remove sources of undesired disturbance to enable the diagnosis of early-stage tumors. In particular, spurious signals arise from instrumental drift, as well as from the unavoidable interaction between the polarizing field and the imaging system. In this paper, we experimentally assess and characterize such spurious effects in order to set the optimal working conditions for magnetic nanoparticles enhanced microwave imaging of cancer. To this end, simple test devices, which include all components typically comprised in a microwave imaging system, have been realized and exploited. The experiment's results allow us to derive design formulas and guidelines useful for limiting the impact of unwanted magnetic effects, as well as that relative to the instrumental drift on the signal generated by the magnetic nanoparticles-loaded tumor.

A feasibility study on microwave imaging of bone for osteoporosis monitoring.

The dielectric properties of bones are found to be influenced by the demineralisation of bones. Therefore, microwave imaging (MWI) can be used to monitor in vivo dielectric properties of human bones and hence aid in the monitoring of osteoporosis. This paper presents the feasibility analysis of the MWI device for monitoring osteoporosis. Firstly, the dielectric properties of tissues present in the human heel are analysed. Secondly, a transmission line (TL) formalism approach is adopted to examine the feasible frequency band and the matching medium for MWI of trabecular bone. Finally, simplified numerical modelling of the human heel was set to monitor the penetration of E-field, the received signal strength, and the power loss in a numerical model of the human heel. Based on the TL formalism approach, 0.6-1.9-GHz frequency band is found to feasible for bone imaging purpose. The relative permittivity of the matching medium can be chosen between 15 and 40. The average percentage difference between the received signal for feasible and inconvenient frequency band was found to be 82%. The findings based on the dielectric contrast of tissues in the heel, the feasible frequency band, and the finite difference time domain simulations support the development of an MWI prototype for monitoring osteoporosis.

A Prototype Microwave System for 3D Brain Stroke Imaging.

This work focuses on brain stroke imaging via microwave technology. In particular, the open issue of monitoring patients after stroke onset is addressed here in order to provide clinicians with a tool to control the effectiveness of administered therapies during the follow-up period. In this paper, a novel prototype is presented and characterized. The device is based on a low-complexity architecture which makes use of a minimum number of properly positioned and designed antennas placed on a helmet. It exploits a differential imaging approach and provides 3D images of the stroke. Preliminary experiments involving a 3D phantom filled with brain tissue-mimicking liquid confirm the potential of the technology in imaging a spherical target mimicking a stroke of a radius equal to 1.25 cm.

Predictive value of SAR based quality indicators for head and neck hyperthermia treatment quality.

PURPOSE: Hyperthermia treatment quality determines treatment effectiveness as shown by the clinically derived thermal-dose effect relations. SAR based optimization factors are used as possible surrogate for temperature, since they are not affected by thermal tissue properties uncertainty and variations. Previously, target coverage (TC) at the 25% and 50% iso-SAR level was shown predictive for treatment outcome in superficial hyperthermia and the target-to-hot-spot-quotient (THQ) was shown to highly correlate with predictive temperature in deep pelvic hyperthermia. Here, we investigate the correlation with temperature for THQ and TC using an 'intermediate' scenario: semi-deep hyperthermia in the head & neck region using the HYPERcollar3D. METHODS: Fifteen patient-specific models and two different planning approaches were used, including random perturbations to circumvent optimization bias. The predicted SAR indicators were compared to predicted target temperature distribution indicators T50 and T90, i.e., the median and 90th percentile temperature respectively. RESULTS: The intra-patient analysis identified THQ, TC25 and TC50 as good temperature surrogates: with a mean correlation coefficient R2T50 = 0.72 and R2T90=0.66. The inter-patient analysis identified the highest correlation with TC25 (R2T50 = 0.76, R2T90=0.54) and TC50 (R2T50 = 0.74, R2T90 = 0.56). CONCLUSION: Our investigation confirmed the validity of our current strategy for deep hyperthermia in the head & neck based on a combination of THQ and TC25. TC50 was identified as the best surrogate since it enables optimization and patient inclusion decision making using one single parameter.

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

The application of microwave technologies in medical imaging and diagnostics is an emerging topic within the electromagnetic (EM) engineering community [...].

Monitoring Thermal Ablation via Microwave Tomography: An Ex Vivo Experimental Assessment.

Thermal ablation treatments are gaining a lot of attention in the clinics thanks to their reduced invasiveness and their capability of treating non-surgical patients. The effectiveness of these treatments and their impact in the hospital's routine would significantly increase if paired with a monitoring technique able to control the evolution of the treated area in real-time. This is particularly relevant in microwave thermal ablation, wherein the capability of treating larger tumors in a shorter time needs proper monitoring. Current diagnostic imaging techniques do not provide effective solutions to this issue for a number of reasons, including economical sustainability and safety. Hence, the development of alternative modalities is of interest. Microwave tomography, which aims at imaging the electromagnetic properties of a target under test, has been recently proposed for this scope, given the significant temperature-dependent changes of the dielectric properties of human tissues induced by thermal ablation. In this paper, the outcomes of the first ex vivo experimental study, performed to assess the expected potentialities of microwave tomography, are presented. The paper describes the validation study dealing with the imaging of the changes occurring in thermal ablation treatments. The experimental test was carried out on two ex vivo bovine liver samples and the reported results show the capability of microwave tomography of imaging the transition between ablated and untreated tissue. Moreover, the discussion section provides some guidelines to follow in order to improve the achievable performances.

Optimization of the Working Conditions for Magnetic Nanoparticle-Enhanced Microwave Diagnostics of Breast Cancer.

Magnetic nanoparticle-aided microwave imaging is recently gaining an increasing interest as a potential tool for breast cancer diagnostics. This is due to the peculiar features of magnetic nanoparticles, which are biocompatible, can be selectively targeted to the tumor, and may change their microwave magnetic response when modulated by a polarizing magnetic field. This latter aspect is particularly appealing, as it enables the physical separation of the microwave signal due the malignancy, targeted by the nanoparticles, from that due to healthy tissue. This increases the specificity of the diagnostic tool, in principle allowing a diagnosis based solely on the detection of the signal due to the nanoparticles response. In this respect, a proper choice of the polarizing field modulation can remarkably increase the detection performances. This paper deals with this issue, by providing the mathematical framework for such an optimization and a procedure for estimating the required quantities from a set of proper measurements. The procedure is then experimentally demonstrated by applying it to a recently developed ultrawideband radar system for the magnetic nanoparticle-aided detection of breast cancer. For such a system, the optimal magnetic field modulation is determined.

On the optimal measurement configuration for magnetic nanoparticles-enhanced breast cancer microwave imaging.

Magnetic nanoparticles-enhanced microwave imaging has been recently proposed as an effective and reliable means to detect breast cancer. Thanks to the nonmagnetic nature of human tissues, the imaging problem corresponds to the retrieval of a weak magnetic anomaly hosted into an unknown nonmagnetic scenario. Hence, properly targeted magnetic nanoparticles in principle allow to avoid false positives and reduce occurrence of false negatives. In this paper, we outline some guidelines for the design of the imaging device based on an optimized measurement configuration. In particular, we determine the nonredundant number of probes and their collocation needed to ensure a reliable solution of the underlying inverse scattering problem. The analysis exploits the spectral properties of the relevant mathematical operators and it is corroborated by reporting numerical results exploiting the phantoms' repository from the University of Wisconsin. It is shown that magnetic nanoparticles-enhanced microwave imaging can reliably detect cancer lesions even using low-complexity arrangements, designed according to the devised guidelines.

Wavelet-based regularization for robust microwave imaging in medical applications.

Microwave imaging (MWI) is an emerging tool for medical diagnostics, potentially offering unique advantages such as the capability of providing quantitative images of the inspected tissues. This involves, however, solving a challenging nonlinear and ill-posed electromagnetic inverse scattering problem. This paper presents a robust method for quantitative MWI in medical applications where very little, if any, a priori information on the imaging scenario is available. This is accomplished by employing a distorted Born iterative method and a regularization by projection technique, which reconstructs the tissue parameters using a wavelet basis expansion to represent the unknown contrast. This approach is suited for any microwave medical imaging application where the requirement for increased resolution dictates the use of higher frequency data and, consequently, a robust regularization strategy. To demonstrate the robustness of the proposed approach, this paper presents reconstructions of highly heterogeneous anatomically realistic numerical breast phantoms in a canonical 2-D configuration.

An effective procedure for MNP-enhanced breast cancer microwave imaging.

Magnetic nanoparticles-enhanced microwave imaging has been recently proposed to overcome the limitations of conventional microwave imaging methods for breast cancer monitoring. In this paper, we discuss how to tackle the linear inverse scattering problem underlying this novel technique in an effective way. In particular, our aim is to minimize the required a priori patient-specific information, avoid occurrence of false positives, and keep the computational burden low. By relying on an extensive numerical analysis in realistic conditions, we show that the method can provide accurate and reliable images without information on the inner structure of the inspected breast and with an only rough knowledge of its shape. Notably, this allows moving to an offline stage the computationally intensive part of the image formation procedure. In addition, we show how to appraise the total amount of magnetic contrast agent targeted in the tumor.

Phaseless imaging with experimental data: facts and challenges.

Two-dimensional target characterization using inverse profiling approaches with total-field phaseless data is discussed. Two different inversion schemes are compared. In the first one, the intensity-only data are exploited in a minimization scheme, thanks to a proper definition of the cost functional. Specific normalization and starting guess are introduced to avoid the need for global optimization methods. In the second scheme [J. Opt. Soc. Am. A21, 622 (2004)], one exploits the field properties and the theoretical results on the inversion of quadratic operators to derive a two-step solution strategy, wherein the (complex) scattered fields embedded in the available data are retrieved first and then a traditional inverse scattering problem is solved. In both cases, the analytical properties of the fields allow one to properly fix the measurement setup and identify the more convenient strategy to adopt. Also, indications on the number and types of sources and receivers to be used are given. Results from experimental data show the efficiency of these approaches and the tools introduced.