Assessing Patient-Specific Microwave Breast Imaging in Clinical Case Studies.

Microwave breast imaging has seen increasing use in clinical investigations in the past decade with over eight systems having being trialled with patients. The majority of systems use radar-based algorithms to reconstruct the image shown to the clinician which requires an estimate of the dielectric properties of the breast to synthetically focus signals to reconstruct the image. Both simulated and experimental studies have shown that, even in simplified scenarios, misestimation of the dielectric properties can impair both the image quality and tumour detection. Many methods have been proposed to address the issue of the estimation of dielectric properties, but few have been tested with patient images. In this work, a leading approach for dielectric properties estimation based on the computation of many candidate images for microwave breast imaging is analysed with patient images for the first time. Using five clinical case studies of both healthy breasts and breasts with abnormalities, the advantages and disadvantages of computational patient-specific microwave breast image reconstruction are highlighted.

Microwave Hydration Monitoring: System Assessment Using Fasting Volunteers.

Hydration is an important aspect of human health, as water is a critical nutrient used in many physiological processes. However, there is currently no clinical gold standard for non-invasively assessing hydration status. Recent work has suggested that permittivity in the microwave frequency range provides a physiologically meaningful metric for hydration monitoring. Using a simple time of flight technique for estimating permittivity, this study investigates microwave-based hydration assessment using a population of volunteers fasting during Ramadan. Volunteers are measured throughout the day while fasting during Ramadan and while not fasting after Ramadan. Comparing the estimated changes in permittivity to changes in weight and the time s fails to establish a clear relationship between permittivity and hydration. Assessing the subtle changes in hydration found in a population of sedentary, healthy adults proves difficult and more work is required to determine approaches suitable for tracking subtle changes in hydration over time with microwave-based hydration assessment techniques.

Study of the Dielectric Properties of Artificial Sweat Mixtures at Microwave Frequencies.

Analysis of sweat is of interest for a variety of diagnosis and monitoring applications in healthcare. In this work, detailed measurements of the dielectric properties of solutions representing the major components of sweat are presented. The measurements include aqueous solutions of sodium chloride (NaCl), potassium chloride (KCl), urea, and lactic acid, as well as their mixtures. Moreover, mixtures of NaCl, KCl, urea, and lactic acid, mimicking artificial sweat at different hydration states, are characterized, and the data are fitted to a Cole-Cole model. The complex dielectric permittivity for all prepared solutions and mixtures is studied in the range of 1-20 GHz, at temperature of 23 °C, with ionic concentrations in the range of 0.01-1.7 mol/L.

Conformal and Disposable Antenna-Based Sensor for Non-Invasive Sweat Monitoring.

This paper presents a feasibility study for a non-wearable, conformal, low cost, and disposable antenna-based sensor for non-invasive hydration monitoring using sweat. It is composed of a patch antenna implemented on a cellulose filter paper substrate and operating in the range 2⁻4 GHz. The paper substrate can absorb liquids, such as sweat on the skin, through two slots incorporated within the antenna structure. Thus, the substrate dielectric properties are altered according to the properties of the absorbed liquid. Changes in reflection-based measurements are used to analyze salt solutions and artificial sweat, specifically the amount of sampled solution and the sodium chloride (NaCl) concentration. Using the shift in resonant frequency and magnitude of the reflection coefficient, NaCl concentrations in the range of 8.5⁻200 mmol/L, representing different hydration states, are detected. The measurements demonstrate the feasibility of using microwave based measurements for hydration monitoring using sweat.

Engineering Approaches to Assessing Hydration Status.

Dehydration is a common condition characterized by a decrease in total body water. Acute dehydration can cause physical and cognitive impairment, heat stroke and exhaustion, and, if severe and uncorrected, even death. The health effects of chronic mild dehydration are less well studied with urolithiasis (kidney stones) the only condition consistently associated with it. Aside from infants and those with particular medical conditions, athletes, military personnel, manual workers, and older adults are at particular risk of dehydration due to their physical activity, environmental exposure, and/or challenges in maintaining fluid homeostasis. This review describes the different approaches that have been explored for hydration assessment in adults. These include clinical indicators perceived by the patient or detected by a practitioner and routine laboratory analyses of blood and urine. These techniques have variable accuracy and practicality outside of controlled environments, creating a need for simple, portable, and rapid hydration monitoring devices. We review the wide array of devices proposed for hydration assessment based on optical, electromagnetic, chemical, and acoustical properties of tissue and bodily fluids. However, none of these approaches has yet emerged as a reliable indicator in diverse populations across various settings, motivating efforts to develop new methods of hydration assessment.

Metrics for Assessing the Similarity of Microwave Breast Imaging Scans of Healthy Volunteers.

Microwave radar imaging is promising as a complementary medical imaging modality. However, the unique nature of the images means interpretation can be difficult. As a result, it is important to understand the sources of image differences, and how much variability is inherent in the imaging system itself. To address this issue, we compare the effectiveness of six different measures of image similarity for quantifying the similarity (or difference) between two microwave radar images. The structural similarity index has become the de facto standard for image comparison, but we propose that useful information can be acquired from a measure known as the Modified Hausdorff Distance. We apply each measure to image pairs from sequential scans of both phantoms and volunteers. We find that rather than using a single value to quantify the image similarity, by computing a number of values that are designed to capture different image aspects, we can better assess the ways in which the images differ.

Evaluation of Image Reconstruction Algorithms for Confocal Microwave Imaging: Application to Patient Data.

Confocal Microwave Imaging (CMI) for the early detection of breast cancer has been under development for over two decades and is currently going through early-phase clinical evaluation. The image reconstruction algorithm is a key signal processing component of any CMI-based breast imaging system and impacts the efficacy of CMI in detecting breast cancer. Several image reconstruction algorithms for CMI have been developed since its inception. These image reconstruction algorithms have been previously evaluated and compared, using both numerical and physical breast models, and healthy volunteer data. However, no study has been performed to evaluate the performance of image reconstruction algorithms using clinical patient data. In this study, a variety of imaging algorithms, including both data-independent and data-adaptive algorithms, were evaluated using data obtained from a small-scale patient study conducted at the University of Calgary. Six imaging algorithms were applied to reconstruct 3D images of five clinical patients. Reconstructed images for each algorithm and each patient were compared to the available clinical reports, in terms of abnormality detection and localisation. The imaging quality of each algorithm was evaluated using appropriate quality metrics. The results of the conventional Delay-and-Sum algorithm and the Delay-Multiply-and-Sum (DMAS) algorithm were found to be consistent with the clinical information, with DMAS producing better quality images compared to all other algorithms.

Adaptive Monostatic System for Measuring Microwave Reflections from the Breast.

A second-generation monostatic radar system to measure microwave reflections from the human breast is presented and analyzed. The present system can measure the outline of the breast with an accuracy of ±1 mm and precisely place the microwave sensor in an adaptive matter such that microwaves are normally incident on the skin. Microwave reflections are measured between 10 MHz to 12 GHz with sensitivity of 65 to 75 dB below the input power and a total scan time of 30 min for 140 locations. The time domain reflections measured from a volunteer show fidelity above 0.98 for signals in a single scan. Finally, multiple scans of a breast phantoms demonstrate the consistency of the system in terms of recorded reflection, outline measurement, and image reconstruction.

Automated 3D method for the construction of flexible and reconfigurable numerical breast models from MRI scans.

Anatomically realistic numerical breast models are essential tools for microwave breast imaging, supporting feasibility analysis, performance verification, and design improvements. Patient-specific models also assist in interpreting the results of the patient studies conducted on microwave imaging prototype systems. The proposed method employs automated and robust 3D processing techniques to construct flexible and reconfigurable breast models. These techniques include noise and artifact suppression with a principal component analysis (PCA) approach, and oversampling of the magnetic resonance imaging (MRI) data to enhance the intensity continuity. The k-means clustering segmentation identifies fatty and fibroglandular tissues and further segments these regions into a selected number of tissues, providing reconfigurable models. A peak Gaussian fitting technique maps the model clusters to the dielectric properties. The robustness of the proposed method is verified by applying it to both 1.5- and 3-T MRI scans as well as to scans of varying breast densities.

Estimating the Effective Permittivity for Reconstructing Accurate Microwave-Radar Images.

We present preliminary results from a method for estimating the optimal effective permittivity for reconstructing microwave-radar images. Using knowledge of how microwave-radar images are formed, we identify characteristics that are typical of good images, and define a fitness function to measure the relative image quality. We build a polynomial interpolant of the fitness function in order to identify the most likely permittivity values of the tissue. To make the estimation process more efficient, the polynomial interpolant is constructed using a locally and dimensionally adaptive sampling method that is a novel combination of stochastic collocation and polynomial chaos. Examples, using a series of simulated, experimental and patient data collected using the Tissue Sensing Adaptive Radar system, which is under development at the University of Calgary, are presented. These examples show how, using our method, accurate images can be reconstructed starting with only a broad estimate of the permittivity range.

Average dielectric property analysis of complex breast tissue with microwave transmission measurements.

Prior information about the average dielectric properties of breast tissue can be implemented in microwave breast imaging techniques to improve the results. Rapidly providing this information relies on acquiring a limited number of measurements and processing these measurement with efficient algorithms. Previously, systems were developed to measure the transmission of microwave signals through breast tissue, and simplifications were applied to estimate the average properties. These methods provided reasonable estimates, but they were sensitive to multipath. In this paper, a new technique to analyze the average properties of breast tissues while addressing multipath is presented. Three steps are used to process transmission measurements. First, the effects of multipath were removed. In cases where multipath is present, multiple peaks were observed in the time domain. A Tukey window was used to time-gate a single peak and, therefore, select a single path through the breast. Second, the antenna response was deconvolved from the transmission coefficient to isolate the response from the tissue in the breast interior. The antenna response was determined through simulations. Finally, the complex permittivity was estimated using an iterative approach. This technique was validated using simulated and physical homogeneous breast models and tested with results taken from a recent patient study.

Contact geometry affects lesion formation in radio-frequency cardiac catheter ablation.

One factor which may be important for determining proper lesion creation during atrial ablation is catheter-endocardial contact. Little information is available that relates geometric contact, depth and angle, to ablation lesion formation. We present an electrothermal computer model of ablation that calculated lesion volume and temperature development over time. The Pennes bioheat equation was coupled to a quasistatic electrical problem to investigate the effect of catheter penetration depth, as well as incident catheter angle as may occur in practice. Biological experiments were performed to verify the modelling of electrical phenomena. Results show that for deeply penetrating tips, acute catheter angles reduced the rate of temperature buildup, allowing larger lesions to form before temperatures elevated excessively. It was also found that greater penetration did not lead to greater transmurality of lesions. We conclude that catheter contact angle plays a significant role in lesion formation, and the time course must be considered. This is clinically relevant because proper identification and prediction of geometric contact variables could improve ablation efficacy.

Safety assessment of ultra-wideband antennas for microwave breast imaging.

This article deals with the safety assessment of several ultra-wideband (UWB) antenna designs for use in prototype microwave breast imaging systems. First, the performances of the antennas are validated by comparison of measured and simulated data collected for a simple test case. An efficient approach to estimating the specific energy absorption (SA) is introduced and validated. Next, SA produced by the UWB antennas inside more realistic breast models is computed. In particular, the power levels and pulse repetition periods adopted for the SA evaluation follow the measurement protocol employed by a tissue sensing adaptive radar (TSAR) prototype system. Results indicate that the SA for the antennas examined is below limits prescribed in standards for exposure of the general population; however, the difficulties inherent in applying such standards to UWB exposures are discussed. The results also suggest that effective tools for the rapid evaluation of new sensors have been developed.

Laser surface estimation for microwave breast imaging systems.

Microwave breast imaging techniques involve collecting measurements from a breast that is positioned in a scanner. While the patient interface typically includes a hole through which the breast is placed when the patient lies in the prone position, the exact location and shape of breast are not known. In this paper, we explore the addition of a laser sensor and associated algorithms in order to provide a rapid and accurate estimate of the breast surface location. We demonstrate that the laser is capable of estimating surfaces with improved accuracy compared to microwave measurements. The impact of accurate surface estimation on images is shown, and results obtained from human scans are presented.

Cathether contact geometry affects lesion formation in radio-frequency cardiac catheter ablation.

One factor which may be important for determining proper lesion creation in an atrial ablation procedure is catheter-endocardial contact. Little information is available that relates geometric contact, depth and angle, to ablation lesion formation. We present an electrothermal computer model of ablation that calculates lesion volume and temperature development over time. The Pennes bioheat equation was coupled to a quasistatic electrical problem. This method simulates importantly, not just catheter penetration depth, but also several different incident catheter angles as may occur in practise. Results show that for deeply penetrating tips, greater catheter angles reduce the rate of temperature buildup, allowing for larger lesions to form before temperatures become dangerous. It was also found that greater penetration may not lead to greater transmurality in lesion formation. We conclude that catheter contact angle plays a significant role in lesion formation, and the time course must be considered. This is clinically relevant because it makes proper identification and prediction of geometric contact variables a necessity in order to improve ablation efficacy and safety.

An improved technique to predict the time-of-arrival of a tumor response in radar-based breast imaging.

Radar-based microwave imaging has been proposed as a complementary modality for early-stage breast cancer screening. This paper presents an algorithm that may be used to accurately predict the time-of-arrival (TOA) of a tumor response contained in sample data acquired from a small number of antennas in a realistic scenario. The TOA information may be used by many of the existing radar-based methods to detect and localize a tumor response. The robustness of the algorithm is demonstrated with data generated from realistic numerical breast models.

Breast surface estimation for radar-based breast imaging systems.

Radar-based microwave breast-imaging techniques typically require the antennas to be placed at a certain distance from or on the breast surface. This requires prior knowledge of the breast location, shape, and size. The method proposed in this paper for obtaining this information is based on a modified tissue sensing adaptive radar algorithm. First, a breast surface detection scan is performed. Data from this scan are used to localize the breast by creating an estimate of the breast surface. If required, the antennas may then be placed at specified distances from the breast surface for a second tumor-sensing scan. This paper introduces the breast surface estimation and antenna placement algorithms. Surface estimation and antenna placement results are demonstrated on three-dimensional breast models derived from magnetic resonance images.

Reduction of skin reflections in radar-based microwave breast imaging.

Radar-based microwave breast imaging is a prospective complementary imaging method that relies on dielectric property differences. One of the main challenges is removing the overwhelming reflection associated with the skin. In this paper, a skin subtraction method that can be applied to data generated with a realistic three dimensional breast model is presented. The method estimates the skin response of the target antenna as a filtered combination of its neighbors with the use of a modified recursive least squares algorithm and a generalized cross validation technique. The neighbors are selected based on their proximity and their spatial correlation to the target antenna. The method's ability to subtract the skin response and preserve the tumor response is demonstrated.

Robust approach to skin location estimation for radar-based breast imaging systems.

Increasingly complex breast models are being used to test emerging microwave imaging modalities. With the increased complexity, waveforms received from skin reflections may consist of contributions from multiple locations, resulting in signatures not examined with simpler models. For example, antennas placed near the chest wall or at significant distances from the breast have been found to receive multiple skin reflections. With these received signals, simple methods used to estimate skin location, such as peak detection, do not provide reliable results. In this paper, we apply a deconvolution technique to find the impulse response with respect to a known reflected signal. Results demonstrate that this method provides more reliable estimates of skin location and shows the ability to estimate two skin locations from a waveform exhibiting two dominant skin reflections.

Tumor response estimation in radar-based microwave breast cancer detection.

Radar-based microwave imaging techniques have been proposed for early stage breast cancer detection. A considerable challenge for the successful implementation of these techniques is the reduction of clutter, or components of the signal originating from objects other than the tumor. In particular, the reduction of clutter from the late-time scattered fields is required in order to detect small (subcentimeter diameter) tumors. In this paper, a method to estimate the tumor response contained in the late-time scattered fields is presented. The method uses a parametric function to model the tumor response. A maximum a posteriori estimation approach is used to evaluate the optimal values for the estimates of the parameters. A pattern classification technique is then used to validate the estimation. The ability of the algorithm to estimate a tumor response is demonstrated by using both experimental and simulated data obtained with a tissue sensing adaptive radar system.