Dielectric Properties Of Breast Tissues Research Articles

INVESTIGATION OF CLASSIFIERS FOR TUMOR DETECTION WITH AN EXPERIMENTAL TIME-DOMAIN BREAST SCREENING SYSTEM

In this work we examine, for the flrst time, the use of classiflcation algorithms for early- stage tumor detection with an experimental time-domain microwave breast screening system. The experimental system contains a 16-element antenna array, and testing is done on breast phantoms that mimic breast tissue dielectric properties. We obtain experimental data from multiple breast phantoms with two possible tumor locations. In this work, we investigate a method for detecting the tumors within the breast but without the usual complexity inherent to image-generation methods, and conflrm its feasibility on experimental data. The proposed method uses machine learning techniques, namely Support Vector Machines (SVM) and Linear Discriminant Analysis (LDA), to determine whether the current breast being scanned is tumor-free. Our results show that both SVM and LDA methods have promise as algorithms supporting early breast cancer microwave screening.

Study of the Effects of Changing Physiological Conditions on Dielectric Properties of Breast Tissues

This paper addresses the changes in the physical characteristics (temperature and water/blood content) of breast tissue under different physiological conditions. We examined ex vivo specimens of breast tissue excised at the time of surgery to study the effects of physiological conditions on dielectric properties. We observed that the dielectric properties strongly depend on tissue physiological state. When the biological tissues undergo physiological changes, such as those due to disease or those induced by external changes such as variations in the environmental temperature, the microscopic processes deviate from their normal state and impact the overall dielectric properties. This suggests that microwave imaging might be used to monitor the physiological conditions of the body.

MEASUREMENT OF ELECTRICAL CHARACTERISTICS OF FEMALE BREAST TISSUES FOR THE DEVELOPMENT OF THE BREAST CANCER DETECTOR

In this paper, dielectric characteristics of female breast tissues were measured. Breast Tissues were mainly composed of fat, flbro-glandular and tumor. Measured tissues were directly extracted from mice and a rat just before the measurements to maintain the tissues as fresh as living ones before degeneration. This makes the measured results more accurate. Because the extracted tissues were very thin, they were measured by two methods using HP probe and a newly designed two-port sample holder. Numerical results for the two- port sample holder were obtained for both the forward and inverse problems. Dielectric properties of breast tissues were measured in the frequency range between 50MHz and 5GHz. We calculated the electrical constant with the measured data from the two-port sample holder. As a result of the measurement, the dispersion characteristics of the female breast tissues were fltted into the flrst Cole-Cole model.

Heterogeneous breast phantom development for microwave imaging using regression models.

As new algorithms for microwave imaging emerge, it is important to have standard accurate benchmarking tests. Currently, most researchers use homogeneous phantoms for testing new algorithms. These simple structures lack the heterogeneity of the dielectric properties of human tissue and are inadequate for testing these algorithms for medical imaging. To adequately test breast microwave imaging algorithms, the phantom has to resemble different breast tissues physically and in terms of dielectric properties. We propose a systematic approach in designing phantoms that not only have dielectric properties close to breast tissues but also can be easily shaped to realistic physical models. The approach is based on regression model to match phantom's dielectric properties with the breast tissue dielectric properties found in Lazebnik et al. (2007). However, the methodology proposed here can be used to create phantoms for any tissue type as long as ex vivo, in vitro, or in vivo tissue dielectric properties are measured and available. Therefore, using this method, accurate benchmarking phantoms for testing emerging microwave imaging algorithms can be developed.

Real time breast microwave radar image reconstruction using circular holography: A study of experimental feasibility

The purpose of this paper is to assess the experimental feasibility of a novel breast microwave radar reconstruction approach, circular holography, using realistic experimental datasets recorded using a preclinical experimental setup. The performance of this approach was quantitatively evaluated by calculating the signal to noise ratio, contrast to noise ratio, spatial accuracy, and reconstruction time. Six datasets were recorded, three corresponding to fatty cases and three containing synthetic dense tissue structures. Five of these datasets contained an 8 mm inclusion that emulated a malignant lesion. The data were acquired from synthetic phantoms that mimic the dielectric properties of breast tissues in the 1-6 GHz range using a custom experimental breast microwave radar system. The spatial accuracy and signal to noise ratio of the reconstructed was calculated for all the reconstructed images. The contrast to noise ratio of the reconstructed images corresponding to the datasets containing fibroglandular tissue regions was determined. This was done to evaluate the ability of the circular holographic method to provide images in which the responses from tumors can be distinguished from adjacent dense tissue structures. The execution time required to form the images was also measured to evaluate the data throughput of the holographic approach. For all the reconstructed datasets, the location of the synthetic tumors in the experimental setup was consistent with its position in the reconstructed image. The average spatial error was 2.2 mm, which is less than half the spatial resolution of the data acquisition system. The average signal to noise ratio of the reconstructed images containing an artificial malignant lesion was 8.5 dB, while the average contrast to noise ratio was 6.7 dB. The reconstructed images presented no artifacts. The average execution time of the images formed using the proposed approach was 5 ms, which is six orders of magnitude faster than current state of the art breast microwave radar (BMR) reconstruction algorithms. The results show that circular holography is capable of forming accurate images with signal to noise levels higher than 8 dB in quasi real time. Compared to BMR reconstruction algorithms tested on datasets containing dense tissue structures, the holographic approach generated images of similar spatial accuracy with higher signal to noise ratios and an acceleration factor of one order of magnitude.

Heterogeneous anthropomorphic phantoms with realistic dielectric properties for microwave breast imaging experiments

We present a technique for fabricating realistic breast phantoms for microwave imaging experiments. Using oil-in-gelatin dispersions that mimic breast tissue dielectric properties at microwave frequencies, we constructed four heterogeneous phantoms spanning the full range of volumetric breast densities. We performed CT scans and dielectric properties measurements to characterize each phantom.

Three‐dimensional microwave imaging of realistic numerical breast phantoms via a multiple‐frequency inverse scattering technique

Breast density measurement has the potential to play an important role in individualized breast cancer risk assessment and prevention decisions. Routine evaluation of breast density will require the availability of a low-cost, nonionizing, three-dimensional (3-D) tomographic imaging modality that exploits a strong properties contrast between dense fibroglandular tissue and less dense adipose tissue. The purpose of this computational study is to investigate the performance of 3-D tomography using low-power microwaves to reconstruct the spatial distribution of breast tissue dielectric properties and to evaluate the modality for application to breast density characterization. State-of-the-art 3-D numerical breast phantoms that are realistic in both structural and dielectric properties are employed. The test phantoms include one sample from each of four classes of mammographic breast density. Since the properties of these phantoms are known exactly, these testbeds serve as a rigorous benchmark for the imaging results. The distorted Born iterative imaging method is applied to simulated array measurements of the numerical phantoms. The forward solver in the imaging algorithm employs the finite-difference time-domain method of solving the time-domain Maxwell's equations, and the dielectric profiles are estimated using an integral equation form of the Helmholtz wave equation. A multiple-frequency, bound-constrained, vector field inverse scattering solution is implemented that enables practical inversion of the large-scale 3-D problem. Knowledge of the frequency-dependent characteristic of breast tissues at microwave frequencies is exploited to obtain a parametric reconstruction of the dispersive dielectric profile of the interior of the breast. Imaging is performed on a high-resolution voxel basis and the solution is bounded by a known range of dielectric properties of the constituent breast tissues. The imaging method is validated using a breast phantom with a single, high-contrast interior scattering target in an otherwise homogeneous interior. The method is then used to image a set of realistic numerical breast phantoms of varied fibroglandular tissue density. Imaging results are presented for each numerical phantom and show robustness of the method relative to tissue density. In each case, the distribution of fibroglandular tissues is well represented in the resulting images. The resolution of the images at the frequencies employed is wider than the feature dimensions of the normal tissue structures, resulting in a smearing of their reconstruction. The results of this study support the utility of 3-D microwave tomography for imaging the distribution of normal tissues in the breast, specifically, dense fibroglandular tissue versus less dense adipose tissue, and suggest that further investigation of its use for volumetric evaluation of breast density is warranted.

ROTATING ANTENNA MICROWAVE IMAGING SYSTEM FOR BREAST CANCER DETECTION

Breast imaging using Confocal Microwave Imaging (CMI) has becoming a di-cult problem, primarily due to the recently- established dielectric heterogeneity of normal breast tissue. CMI for breast cancer detection was originally developed based on several assumptions regarding the dielectric properties of normal and cancerous breast tissue. Historical studies which examined the dielectric properties of breast tissue concluded that the breast was primarily dielectrically homogeneous, and that and that the propagation, attenuation and phase characteristics of normal breast tissue allowed for the constructive addition of the Ultra Wideband (UWB) returns from dielectric scatterers within the breast. However, recent studies by Lazebnik et al. have highlighted a very signiflcant dielectric contrast between normal adipose and flbroglandular tissue within the breast. Lazebnik also established that there was an almost negligible dielectric contrast between flbroglandular and cancerous breast tissue at microwave frequencies. This dielectric heterogeneity presents a considerably more challenging imaging scenario, where constructive addition of the UWB returns, and therefore tumor detection, is much more di-cult. Therefore, more sophisticated signal acquisition and beamforming algorithms need to be developed. In this paper, a novel imaging algorithm is described, which uses a rotating antenna system to increase the number of unique propagation paths to and from the tumor to create an improved image of the breast. This approach is shown to provide improved images of more dielectrically heterogeneous breasts than the traditional flxed-antenna delay and sum beamformer from which it is derived.

The correlation of in vivo and ex vivo tissue dielectric properties to validate electromagnetic breast imaging: initial clinical experience

Electromagnetic (EM) breast imaging provides low-cost, safe and potentially a more specific modality for cancer detection than conventional imaging systems. A primary difficulty in validating these EM imaging modalities is that the true dielectric property values of the particular breast being imaged are not readily available on an individual subject basis. Here, we describe our initial experience in seeking to correlate tomographic EM imaging studies with discrete point spectroscopy measurements of the dielectric properties of breast tissue. The protocol we have developed involves measurement of in vivo tissue properties during partial and full mastectomy procedures in the operating room (OR) followed by ex vivo tissue property recordings in the same locations in the excised tissue specimens in the pathology laboratory immediately after resection. We have successfully applied all of the elements of this validation protocol in a series of six women with cancer diagnoses. Conductivity and permittivity gauged from ex vivo samples over the frequency range 100 Hz–8.5 GHz are found to be similar to those reported in the literature. A decrease in both conductivity and permittivity is observed when these properties are gauged from ex vivo samples instead of in vivo. We present these results in addition to a case study demonstrating how discrete point spectroscopy measurements of the tissue can be correlated and used to validate EM imaging studies.

Development of Anatomically Realistic Numerical Breast Phantoms With Accurate Dielectric Properties for Modeling Microwave Interactions With the Human Breast

Computational electromagnetics models of microwave interactions with the human breast serve as an invaluable tool for exploring the feasibility of new technologies and improving design concepts related to microwave breast cancer detection and treatment. In this paper, we report the development of a collection of anatomically realistic 3-D numerical breast phantoms of varying shape, size, and radiographic density which can readily be used in finite-difference time-domain computational electromagnetics models. The phantoms are derived from T1-weighted MRIs of prone patients. Each MRI is transformed into a uniform grid of dielectric properties using several steps. First, the structure of each phantom is identified by applying image processing techniques to the MRI. Next, the voxel intensities of the MRI are converted to frequency-dependent and tissue-dependent dielectric properties of normal breast tissues via a piecewise-linear map. The dielectric properties of normal breast tissue are taken from the recently completed large-scale experimental study of normal breast tissue dielectric properties conducted by the Universities of Wisconsin and Calgary. The comprehensive collection of numerical phantoms is made available to the scientific community through an online repository.

Test of the method of differentiation between healthy and anomalous breast tissues using the open-ended dielectric probe covered by a dielectric film

Dielectric properties of breast tissue obtained from 131 patients were investigated by an open-ended probe separated from the tissue by a dielectric film (plastic foil). The film decreases the measured capacitance, but the content of blood and body liquids has little effect on the measured quantity. We found that in cancerous tissue the electric capacity (related to the permittivity) measured at f ⩾ 10 MHz using the modified probe is higher than that in normal tissue. The dielectric assignment was confirmed by histopathology in 94% of investigated cases. High efficiency in differentiation between normal and cancer breast tissues and the feasibility of fulfilling of aseptic conditions (a film covering the probe) are promising in intra-operative cancer diagnostics.

Estimating the Breast Surface Using UWB Microwave Monostatic Backscatter Measurements

This paper presents an algorithm for estimating the location of the breast surface from scattered ultrawideband (UWB) microwave signals recorded across an antenna array. Knowing the location of the breast surface can improve imaging performance if incorporated as a priori information into recently proposed microwave imaging algorithms. These techniques transmit low-power microwaves into the breast using an antenna array, which in turn measures the scattered microwave signals for the purpose of detecting anomalies or changes in the dielectric properties of breast tissue. Our proposed surface identification algorithm consists of three procedures, the first of which estimates M points on the breast surface given M channels of measured microwave backscatter data. The second procedure applies interpolation and extrapolation to these M points to generate N > M points that are approximately uniformly distributed over the breast surface, while the third procedure uses these N points to generate a 3-D estimated breast surface. Numerical as well as experimental tests indicate that the maximum absolute error in the estimated surface generated by the algorithm is on the order of several millimeters. An error analysis conducted for a basic microwave radar imaging algorithm (least-squares narrowband beamforming) indicates that this level of error is acceptable. A key advantage of the algorithm is that it uses the same measured signals that are used for UWB microwave imaging, thereby minimizing patient scan time and avoiding the need for additional hardware.

Highly Accurate Debye Models for Normal and Malignant Breast Tissue Dielectric Properties at Microwave Frequencies

The finite difference time domain (FDTD) method is widely used as a computational tool for development, validation, and optimization of emerging microwave breast cancer detection and treatment techniques. When expressed in terms of Debye parameters, dispersive breast tissue dielectric properties can be efficiently incorporated into FDTD codes. Previously, we experimentally characterized the dielectric properties of a large number of excised normal and malignant breast tissue samples from 0.5 to 20 GHz. We subdivided the large database of normal tissue data into three groups based on the percent adipose tissue present in a particular sample. In addition, we formed a group of all cancer samples that contained at least 30% malignant tissue. We summarized the data using one-pole Cole-Cole models that were rigorously fit to the median dielectric properties of the three normal tissue groups and one malignant tissue group. In this letter, we present computationally simpler one- and two-pole Debye models that retain the high accuracy of the Cole-Cole models. Model parameters are derived for two sets of frequency ranges: the entire measurement frequency range from 0.5 to 20 GHz, and the 3.1-10.6 GHz FCC band allocated for ultrawideband medical applications. The proposed Debye models provide a means for creating computationally efficient FDTD breast models with realistic wideband dielectric properties derived from the largest and most comprehensive experimental study conducted to date on human breast tissue.

Estimation of the Frequency-Dependent Average Dielectric Properties of Breast Tissue Using a Time-Domain Inverse Scattering Technique

Ultrawideband (UWB) microwave radar imaging techniques for breast cancer detection typically require estimates of the spatially averaged dielectric properties of breast tissue. We propose an algorithm for estimating patient-specific, frequency-dependent average dielectric properties from scattered UWB microwave signals. The algorithm is a variation of an iterative finite-difference time-domain (FDTD) technique for solving the time-domain inverse scattering problem. The assumption is made that the breast consists of two homogeneous regions: skin and underlying tissue. This two-medium geometry results in an inverse scattering problem that is not as ill-posed as those typically encountered in microwave tomography because the number of unknowns being sought is very small. We test the performance of the algorithm on data simulated using anatomically realistic 2-D numerical breast phantoms

Effects of mechanical flaws in open-ended coaxial probes for dielectric spectroscopy

A detailed study of dielectric properties of breast tissue in the 0.1 to 20 GHz frequency range currently under way uses open-ended teflon coaxial probes as sensors. This letter quantifies the effects of small mechanical imperfections at the probe aperture on the measured reflection coefficient. The mechanical flaws in the probe can lead to significant errors, thus probes for dielectric spectroscopy of breast tissue have to be carefully manufactured.