Microwave imaging for tissue assessment: initial evaluation in multitarget tissue-equivalent phantoms

A Tuned Microwave Resonant System for Subcutaneous Imaging

A compact and planar imaging system was developed using a flexible polymer substrate that can distinguish subcutaneous tissue abnormalities, such as breast tumors, based on electromagnetic-wave interactions in materials where permittivity variations affect wave reflection. The sensing element is a tuned loop resonator operating in the industrial, scientific, and medical (ISM) band at 2.423 GHz, providing a localized high-intensity electric field that penetrates into tissues with sufficient spatial and spectral resolutions. The resonant frequency shifts and magnitudes of the reflection coefficients indicate the boundaries of abnormal tissues under the skin due to their high contrasts to normal tissues. The sensor was tuned to the desired resonant frequency with a reflection coefficient of -68.8 dB for a radius of 5.7 mm, with a tuning pad. Quality factors of 173.1 and 34.4 were achieved in simulations and measurements in phantoms. An image-processing method was introduced to fuse raster-scanned 9 × 9 images of resonant frequencies and reflection coefficients for image-contrast enhancement. The results showed a clear indication of the tumor's location at a depth of 15 mm and the capability to identify two tumors both at the depth of 10 mm. The sensing element can be expanded to a four-element phased array for deeper field penetration. Field analysis showed the depths of -20 dB attenuation were improved from 19 to 42 mm, giving wider coverage in tissues at resonance. Results showed that a quality factor of 152.5 was achieved and a tumor could be identified at a depth of up to 50 mm. In this work, simulations and measurements were conducted to validate the concept, showing great potential for subcutaneous imaging in medical applications in a noninvasive, efficient, and lower-cost way.

Use of multi-angle ultra-wide band microwave sounding for high resolution breast imaging

PURPOSE

This report proposes an approach to develop a method of microwave imaging for early, non-invasive diagnosis of breast tumors. Here we describe a data-processing method for obtaining radio images of biological heterogeneities and a new method for filtering static noise in received signals.

METHODS

A specialized radar system was developed in the present study and used to perform sounding of synthetic phantoms with the dielectric properties of breast tissue in the range of 2-8 GHz. Datasets thus contained synthetic structures that imitated the dielectric properties of breast tissues and tumors. The permittivity values of the created artificial materials were verified using a waveguide cell. Tumors were simulated via plastic balls with a diameter of 1 cm that were filled with saline. A special ultra-wide band (UWB) radar system developed at Tomsk State University was used to register radar responses from the phantoms. The radar system included the vector reflectometer, the UWB antenna, and the mechanical scanner that provided sounding in the hemisphere. We also used the time-domain signals processing method to obtain the radio image signals. In this method, all signals received during scanning in the hemisphere are added with calculated delay for the given focus point. Special filtering of the constant components of the signal at each of the angular sounding latitudes was used to eliminate clutter in the received signal. This solution allowed us to account for additive clutter in the received signal from structural elements during scanning in the hemisphere. The influence of the number of angles on the quality of the resulting radio image was evaluated.

RESULTS

The phantoms of a female breast and a malignant tumor from artificial materials with electrophysical characteristics close to those of real tissues have been developed. This facilitated verification of the proposed method for constructing radio images under more clinically relevant conditions. The proposed filtering of the constant components of the signal effectively doubled the signal-to-noise ratio in the resulting radio image compared with the standard algorithm of clutter filtering. The influence of different numbers of scan points on the quality of the final radio image are presented herein. It is concluded that it is sufficient to use not more than 600-800 sounding points for acceptable image quality. A further increase in the number of angles does not significantly improve image quality despite increasing the scan time.

CONCLUSIONS

Scanning in the hemisphere of the breast phantom using the proposed method of clutter filtering show that multi-angle microwave imaging can form accurate three-dimensional (3D) images with double the level of signal-to-clutter compared with the standard filtering approach. The images of artificial tumors were obtained when sounding in the range of 2-8 GHz with the resolution of about 5-7 mm.

Recent Advances in Microwave Imaging for Breast Cancer Detection

Breast cancer is a disease that occurs most often in female cancer patients. Early detection can significantly reduce the mortality rate. Microwave breast imaging, which is noninvasive and harmless to human, offers a promising alternative method to mammography. This paper presents a review of recent advances in microwave imaging for breast cancer detection. We conclude by introducing new research on a microwave imaging system with time-domain measurement that achieves short measurement time and low system cost. In the time-domain measurement system, scan time would take less than 1 sec, and it does not require very expensive equipment such as VNA.

Feasibility of non-invasive temperature estimation by the assessment of the average gray-level content of B-mode images

This paper assesses the potential of the average gray-level (AVGL) from ultrasonographic (B-mode) images to estimate temperature changes in time and space in a non-invasive way. Experiments were conducted involving a homogeneous bovine muscle sample, and temperature variations were induced by an automatic temperature regulated water bath, and by therapeutic ultrasound. B-mode images and temperatures were recorded simultaneously. After data collection, regions of interest (ROIs) were defined, and the average gray-level variation computed. For the selected ROIs, the AVGL-Temperature relation were determined and studied. Based on uniformly distributed image partitions, two-dimensional temperature maps were developed for homogeneous regions. The color-coded temperature estimates were first obtained from an AVGL-Temperature relation extracted from a specific partition (where temperature was independently measured by a thermocouple), and then extended to the other partitions. This procedure aimed to analyze the AVGL sensitivity to changes not only in time but also in space. Linear and quadratic relations were obtained depending on the heating modality. We found that the AVGL-Temperature relation is reproducible over successive heating and cooling cycles. One important result was that the AVGL-Temperature relations extracted from one region might be used to estimate temperature in other regions (errors inferior to 0.5 °C) when therapeutic ultrasound was applied as a heating source. Based on this result, two-dimensional temperature maps were developed when the samples were heated in the water bath and also by therapeutic ultrasound. The maps were obtained based on a linear relation for the water bath heating, and based on a quadratic model for the therapeutic ultrasound heating. The maps for the water bath experiment reproduce an acceptable heating/cooling pattern, and for the therapeutic ultrasound heating experiment, the maps seem to reproduce temperature profiles consistent with the pressure field of the transducer, and in agreement with temperature maps developed by COMSOL®MultiPhysics simulations.

A prototype device for non-invasive continuous monitoring of intracerebral hemorrhage

A prototype for a non-invasive, real-time, monitoring device was developed to detect changes in the brain secondary to disease or injury such as intracerebral hemorrhage (ICH). The eventual goal is a non-invasive, real time sensor that can alert the clinician to alterations in the comatose patient's brain resulting from hemorrhage, seizure or stroke. In this work, a 400 MHz electromagnetic (EM) signal was transmitted with an antenna (T), incident on a 'brain gel' in vitro ICH model, and received by a receiving (R) antenna. Changes in the received signal were found to be induced by the presence of blood. The received power (P(R)) was found to be a linear function of the cross sectional area of blood, as measured normal to the incident wave. In addition, the sensor was able to detect as little as 1 mL of blood in this 1000 mL in vitro model.

Noninvasive thermometry assisted by a dual-function ultrasound transducer for mild hyperthermia

Mild hyperthermia is increasingly important for the activation of temperature-sensitive drug delivery vehicles. Noninvasive ultrasound thermometry based on a 2-D speckle tracking algorithm was examined in this study. Here, a commercial ultrasound scanner, a customized co-linear array transducer, and a controlling PC system were used to generate mild hyperthermia. Because the co-linear array transducer is capable of both therapy and imaging at widely separated frequencies, RF image frames were acquired during therapeutic insonation and then exported for off-line analysis. For in vivo studies in a mouse model, before temperature estimation, motion correction was applied between a reference RF frame and subsequent RF frames. Both in vitro and in vivo experiments were examined; in the in vitro and in vivo studies, the average temperature error had a standard deviation of 0.7°C and 0.8°C, respectively. The application of motion correction improved the accuracy of temperature estimation, where the error range was 1.9 to 4.5°C without correction compared with 1.1 to 1.0°C following correction. This study demonstrates the feasibility of combining therapy and monitoring using a commercial system. In the future, real-time temperature estimation will be incorporated into this system.

Application of the no-sampling linear sampling method to breast cancer detection

In this paper, the no-sampling linear sampling method is applied to microwave imaging of cancerous tissues in realistic models of female breast obtained from magnetic resonance imaging (MRI). The adopted formulation is based on a modified version of the far-field equation, sensitive to anomalies with respect to the healthy breast. The healthy configuration is taken into account through the related Green's function, which is numerically computed. The adopted imaging technique is assessed against the inspection of tumors of several positions and sizes in noisy environments. Moreover, a numerical analysis of the robustness of the method is performed when the model parameters used for evaluating the Green's function are not exactly known.

Photoacoustics, thermoacoustics, and acousto-optics for biomedical imaging

Recently there have been significant advances in developing hybrid techniques combining electromagnetic waves with ultrasound for biomedical imaging, namely photoacoustic, thermoacoustic, and acousto-optic (or ultrasound modulated optical) tomography. All three techniques take advantage of tissue contrast offered by electromagnetic (EM) waves, while achieving good spatial resolution in deeper tissue facilitated by ultrasound. In this review the principles of the three techniques are introduced. A description of existing experimental and image reconstruction techniques is provided. Some recent key developments are highlighted and current issues in each of the areas are discussed.

Non-invasive estimation of hyperthermia temperatures with ultrasound

Ultrasound is an attractive modality for temperature monitoring because it is non-ionizing, convenient, inexpensive and has relatively simple signal processing requirements. This modality may be useful for temperature estimation if a temperature-dependent ultrasonic parameter can be identified, measured and calibrated. The most prominent methods for using ultrasound as a non-invasive thermometer exploit either (1) echo shifts due to changes in tissue thermal expansion and speed of sound (SOS), (2) variation in the attenuation coefficient or (3) change in backscattered energy from tissue inhomogeneities. The use of echo shifts has received the most attention in the last decade. By tracking scattering volumes and measuring the time shift of received echoes, investigators have been able to predict the temperature from a region of interest both theoretically and experimentally in phantoms, in isolated tissue regions in vitro and preliminary in vivo studies. A limitation of this method for general temperature monitoring is that prior knowledge of both SOS and thermal-expansion coefficients is necessary. Acoustic attenuation is dependent on temperature, but with significant changes occurring only at temperatures above 50 degrees C, which may lead to its use in thermal ablation therapies. Minimal change in attenuation, however, below this temperature range reduces its attractiveness for use in clinical hyperthermia. Models and measurements of the change in backscattered energy suggest that, over the clinical hyperthermia temperature range, changes in backscattered energy are dependent on the properties of individual scatterers or scattering regions. Calibration of the backscattered energy from different tissue regions is an important goal of this approach. All methods must be able to cope with motion of the image features on which temperature estimates are based. A crucial step in identifying a viable ultrasonic approach to temperature estimation is its performance during in vivo tests.

A soft-computing methodology for noninvasive time-spatial temperature estimation

The safe and effective application of thermal therapies is restricted due to lack of reliable noninvasive temperature estimators. In this paper, the temporal echo-shifts of backscattered ultrasound signals, collected from a gel-based phantom, were tracked and assigned with the past temperature values as radial basis functions neural networks input information. The phantom was heated using a piston-like therapeutic ultrasound transducer. The neural models were assigned to estimate the temperature at different intensities and points arranged across the therapeutic transducer radial line (60 mm apart from the transducer face). Model inputs, as well as the number of neurons were selected using the multiobjective genetic algorithm (MOGA). The best attained models present, in average, a maximum absolute error less than 0.5 degrees C, which is pointed as the borderline between a reliable and an unreliable estimator in hyperthermia/diathermia. In order to test the spatial generalization capacity, the best models were tested using spatial points not yet assessed, and some of them presented a maximum absolute error inferior to 0.5 degrees C, being "elected" as the best models. It should be also stressed that these best models present implementational low-complexity, as desired for real-time applications.

Noninvasive estimation of temperature elevations in biological tissues using acoustic nonlinearity parameter imaging

A method for noninvasively imaging temperature would assist the development of hyperthermia. In this study, the relationships between the acoustic nonlinearity parameters and the temperatures in porcine fat and liver were obtained. The temperature elevations induced by ultrasound irradiation of porcine fat and liver were then derived inversely from acoustic nonlinearity parameter imaging. These temperature elevations were compared with theoretical predictions and with those measured by a thermocouple. The temperature elevations at the focus in the fat and liver samples measured via a thermocouple were 21.1 +/- 0.8 degrees C and 15.7 +/- 0.6 degrees C, respectively, which coincided with those obtained by acoustic nonlinearity parameter imaging (22.0 +/- 1.4 degrees C in fat and 16.9 +/- 1.1 degrees C in liver). These may be compared with the theoretical predictions of elevations of 24.0 degrees C in fat and 19.7 degrees C in liver. The results of this study show that acoustic nonlinearity imaging may be a novel method for temperature evaluation in hyperthermia. (E-mail: xzliu@nju.edu.cn).

Ultrasonic temperature imaging for guiding focused ultrasound surgery: effect of angle between imaging beam and therapy beam

Ultrasonic temperature imaging is a promising technique for guiding focused ultrasound surgery (FUS). The FUS system is run at an initial, nonablative intensity and a diagnostic transducer images the heat-induced echo strain, which is proportional to the temperature rise. The echo strain image portrays an elliptical "hot spot" corresponding to the focal region of the therapy transducer. It is anticipated that such images will be used to predict the location of the thermal lesion that would be produced at an ablative intensity. We demonstrated in vitro that heat-induced echo strain images can visualize a spatial peak temperature rise of <2 degrees C (starting at room temperature). However, the imaging beam was perpendicular to the treatment beam in these experiments, whereas the most convenient approach in vivo would be to mount the imaging probe within the housing of the therapy transducer such that the two beams are coaxial. A previous simulation experiment predicted that echo strain images would be noisier for the coaxial configuration because sharp lateral gradients in axial displacement cause increased RF signal decorrelation within the beam width. The aim of the current study was to verify this prediction in vitro. We found, that for a temperature rise of approximately 4 degrees C, the mean contrast-to-noise ratio for coaxial and perpendicular echo strain images was 0.37 (+/-0.24) and 2.00 (+/-0.72) respectively. Furthermore, the decorrelation noise seen in the coaxial images obscured the posterior axial border of the hot spot. We conclude that the coaxial configuration will be useful for localizing the hot spot in the lateral direction. However, it may not be able to depict the axial extent of the hot spot or to portray a parameter that is directly related to temperature rise.

Real-time calibration of temperature estimates during radiofrequency ablation

Radiofrequency ablation is an interstitial focal ablative therapy that can be used in a percutaneous fashion and permits in situ destruction of hepatic tumors. Recurrence rates after rf therapy are as high as 34-55%, due to difficulties in accurately identifying the zone of necrosis (thermal lesion) because of the low intrinsic acoustic contrast between normal and ablated liver tissue. Our goal is to provide real-time ultrasonic tracking of temperature changes over the large range of temperatures traditionally used (40-100 degrees C) in rfablation procedures using an external ultrasound transducer. Temperature estimates are obtained using a cross-correlation algorithm applied to rf ultrasound echo signal data acquired at discrete intervals during heating. Apparent tissue displacement estimates obtained at these discrete time-intervals are accumulated to obtain a cumulative displacement map, whose gradient provides after appropriate scaling provides a temperature map at the specified elapsed ablation duration. Temperature maps are used to display the initial temperature rise and to continuously update a thermal map of the treated region. In this paper, we develop calibration curves that relate the echo shift due to the change in the speed of sound and thermal expansion to the corresponding temperature increase on in-vitro tissue specimens. These calibration curves can then be utilized for the real time calibration and analysis of temperature estimates obtained from the rf echo signals during ablation. Temperature maps obtained using the calibration curve compare favorably to temperature estimates observed using the invasive thermosensor readings on the ablation electrode and previous results that utilized a linear calibration factor.

Noninvasive temperature estimation based on the energy of backscattered ultrasound

Hyperthermia has been used as a cancer treatment in which tumors are elevated to cytotoxic temperatures to aid in their control. A noninvasive method for volumetrically determining temperature distribution during treatment would greatly enhance the ability to uniformly heat tumors at therapeutic levels. Ultrasound is an attractive modality for this purpose. We investigated changes in backscattered energy (CBE) from pulsed ultrasound with temperature. Our predicted changes in backscattered energy were matched by in vitro measurements in samples of bovine liver, turkey breast, and pork rib muscle. We studied CBE in tissue regions with multiple scatterers, of isolated individual scatterers, and in collections of individual scatterers. The latter appears to have the most potential. We measured the CBE with a focused circular transducer with a center frequency of 7.5 MHz. The standard deviation of the CBE of 75-125 scattering regions from 0.3 to 0.5 cm3 volumes increased nearly monotonically from 37 degrees C to 50 degrees C in each tissue type. Although the slopes were different, the curve for each type of tissue was well matched by a second-degree polynomial, with a correlation coefficient of 0.99 in each case. Thus the use of the CBE of ultrasound for temperature estimation may have clinical promise with a convenient, low cost modality. Because our approach exploits the inhomogeneities present in tissue, we believe that if it is successful in vitro, it holds promise for in vivo application.

Quantification of 3-D field effects during 2-D microwave imaging

Two-dimensional (2-D) approaches to microwave imaging have dominated the research landscape primarily due to the moderate levels of measurement data, data-acquisition time, and computational costs required. Three-dimensional (3-D) approaches have been investigated in simulation, phantom, and animal experiments. While 3-D approaches are certainly important in terms of the potential to improve image quality, their associated costs are significant at this time. In addition, benchmarks are needed to evaluate these new generation systems as more 3-D methods begin to appear. In this paper, we present a systematic series of experiments which assess the capability of our 2-D system to image classical 3-D geometries. We demonstrate where current methods suffer from 3-D effects but also identify situations where they remain quite useful. Comparisons between reconstructions utilizing phantom measurements and simulated 3-D data are also shown to validate the results. These findings suggest that for certain biomedical applications, 2-D approaches remain quite attractive.

Pre-scaled two-parameter Gauss-Newton image reconstruction to reduce property recovery imbalance

Gauss-Newton image reconstruction in microwave imaging can be formulated in terms of a single complex quantity, the wave number squared (k2), with the understanding that the relative permittivity and conductivity images can be extracted afterwards through a simple constitutive relationship. However, this approach ignores the fact that the magnitude of the average real and imaginary components can be considerably out of balance depending on the operating frequency and tissue characteristics which can inadvertently imbalance the process in favour of one parameter over the other. In an effort to achieve property recovery which is balanced, we introduce a pre-scaling procedure at the property update stage of the reconstruction. Utilization of this concept in conjunction with our two-step regularization process for both simulation and phantom experiments demonstrates that the penalty term weighting parameters for the optimal mean-squared property errors for the two recovered distributions (relative permittivity and conductivity) together with that yielding the lowest least-squared electric field error coincide only when the scaling is applied. The scheme provides a means for simultaneous optimization of the two permittivity and conductivity images.

Experimental validation of a linear model for data reduction in chirp-pulse microwave CT

Chirp-pulse microwave computerized tomography (CP-MCT) is an imaging modality developed at the Department of Biocybernetics, University of Niigata (Niigata, Japan), which intends to reduce the microwave-tomography problem to an X-ray-like situation. We have recently shown that data acquisition in CP-MCT can be described in terms of a linear model derived from scattering theory. In this paper, we validate this model by showing that the theoretically computed response function is in good agreement with the one obtained from a regularized multiple deconvolution of three data sets measured with the prototype of CP-MCT. Furthermore, the reliability of the model as far as image restoration in concerned, is tested in the case of space-invariant conditions by considering the reconstruction of simple on-axis cylindrical phantoms.

Ultrasound monitoring of temperature change during radiofrequency ablation: preliminary in-vivo results

Radiofrequency (RF) ablation is an interstitial focal ablative therapy that can be used in a percutaneous fashion and permits in situ destruction of hepatic tumors. However, local tumor recurrence rates after RF ablative therapy are as high as 34% to 55%, which may be due in part to the inability to monitor accurately temperature profiles in the tissue being ablated, and to visualize the subsequent zone of necrosis (thermal lesion) formed. The goal of the work described in this paper was to investigate methods for the real-time and in vivo monitoring of the spatial distribution of heating and temperature elevation to achieve better control of the degree of tissue damage during RF ablation therapy. Temperature estimates are obtained using a cross-correlation algorithm applied to RF ultrasound (US) echo signal data acquired at discrete intervals during heating. These temperature maps were used to display the initial temperature rise and to continuously update a thermal map of the treated region. Temperature monitoring is currently performed using thermosensors on the prongs (tines) of the RF ablation probe. However, monitoring the spatial distribution of heating is necessary to control the degree of tissue damage produced.

Three-dimensional microwave tomography: initial experimental imaging of animals

The purpose of this study was to construct a microwave tomographic system capable of conducting experiments with whole scale biological objects and to demonstrate the feasibility of microwave tomography for imaging such objects using a canine model. Experiments were conducted using a three-dimensional (3-D) microwave tomographic system with working chamber dimensions of 120 cm in diameter and 135 cm in height. The operating frequency was 0.9 GHz. The object under study was located in the central area of the tomographic chamber filled with a salt solution. Experimentally measured attenuation of the electromagnetic field through the thorax was about -120 dB. To obtain images, we used various two-dimensional and 3-D reconstruction schemes. Images of the canine were obtained. In spite of imperfections, the images represent a significant milestone in the development of microwave tomography for whole body imaging and demonstrate its feasibility.

A two-stage microwave image reconstruction procedure for improved internal feature extraction

We have developed a two-stage Gauss-Newton reconstruction process with an automatic procedure for determining the regularization parameter. The combination is utilized by our microwave imaging system and has facilitated recovery of quantitatively improved images. The first stage employs a Levenberg-Marquardt regularization along with a spatial filtering technique for a few iterations to produce an intermediate image. In effect, the first set of iterative image reconstruction steps synthesizes a priori information from the measurement data versus actually requiring physical prior information on the interrogated object. Because of the interaction of the Levenberg-Marquardt regularization and spatial filtering at each iteration, the intermediate image produced from the first reconstruction stage represents an improvement in terms of the least squared error over the initial uniform guess; however, it has not completely converged in a least squared sense. The second stage involves using this distribution as a priori information in an iteratively regularized Gauss-Newton reconstruction with a weighted Euclidean distance penalty term. The penalized term restricts the final image to a vicinity (determined by the scale of the weighting parameter) about the intermediate image while allowing more flexibility in extracting internal object structures. The second stage makes use of an empirical Bayesian/random effects model that enables an optimal determination of the weighting parameter of the penalized term. The new approach demonstrates quantifiably improved images in simulation, phantom and in vivo experiments with particularly striking improvements with respect to the recovery of heterogeneities internal to large, high contrast scatterers such as encountered when imaging the human breast in a water-coupled configuration.

Computational modeling of three-dimensional microwave tomography of breast cancer

Microwave tomographic approach is proposed to detect and image breast cancers. Taking into account the big difference in dielectrical properties between normal and malignant tissues, we have proposed using the microwave tomographic method to image a human breast. Because of the anatomical features of the objects, this case has to be referred to the tomography with a limited angle of observation. As a result of computer experiments we have established that multiview cylindrical configurations are able to provide microwave tomograms of the breast with a small size tumor inside. Using the gradient method, we have developed a computer code to create images of the three-dimensional objects in dielectrical properties on microwave frequencies.

Microwave image reconstruction utilizing log-magnitude and unwrapped phase to improve high-contrast object recovery

Reconstructing images of large high-contrast objects with microwave methods has proved difficult. Successful images have generally been obtained by using a priori information to constrain the image reconstruction to recover the correct electromagnetic property distribution. In these situations, the measured electric field phases as a function of receiver position around the periphery of the imaging field-of-view vary rapidly often undergoing changes of greater than pi radians especially when the object contrast and illumination frequency increase. In this paper, we introduce a modified form of a Maxwell equation model-based image reconstruction algorithm which directly incorporates log-magnitude and phase of the measured electric field data. By doing so, measured phase variation can be unwrapped and distributed over more than one Rieman sheet in the complex plane. Simulation studies and microwave imaging experiments demonstrate that significant image quality enhancements occur with this approach for large high-contrast objects. Simple strategies for visualizing and unwrapping phase values as a function of the transmitter and receiver positions within our microwave imaging array are described. Metrics of the degree of phase variation expressed in terms of the amount and extent of phase wrapping are defined and found to be figures-of-merit which estimate when it is critical to deploy the new image reconstruction approach. In these cases, the new algorithm recovers high-quality images without resorting to the use of a priori information on object contrast and/or size as previously required.

Image restoration in chirp-pulse microwave CT (CP-MCT)

Chirp-pulse microwave computed tomography (CP-MCT) is a technique for imaging the distribution of temperature variations inside biological tissues. Even if resolution and contrast are adequate to this purpose, a further improvement of image quality is desirable. In this paper, we discuss the blur of CP-MCT images and we propose a method for estimating the corresponding point spread function (PSF). To this purpose we use both a measured and a computed projection of a cylindrical phantom. We find a good agreement between the two cases. Finally the estimated PSF is used for deconvolving data corresponding to various kinds of cylindrical phantoms. We use an iterative nonlinear deconvolution method which assures nonnegative solutions and we demonstrate the improvement of image quality which can be obtained in such a way.

Three-dimensional microwave tomography: experimental prototype of the system and vector born reconstruction method

A method of image reconstruction in three-dimensional (3-D) microwave tomography in a weak dielectric contrast case has been developed. By utilizing only one component of the vector electromagnetic field this method allows successful reconstruction of images of 3-D mathematical phantoms. A prototype of the 3-D microwave tomographic system capable of imaging 3-D objects has been constructed. The system operates at a frequency of 2.36 GHz and utilizes a code-division technique. With dimensions of the cylindrical working chamber z = 40 cm and d = 60 cm, the system allows measurement of an attenuation up to 120 dB having signal-to-noise ratio about 30 dB. The direct problem solutions for different mathematical approaches were compared with an experimentally measured field distribution inside the working chamber. The tomographic system and the reconstruction method were tested in simple experimental imaging.

Nonactive antenna compensation for fixed-array microwave imaging: Part II--Imaging results

Model-based imaging techniques utilizing microwave signal illumination rely heavily on the ability to accurately represent the wave propagation with a suitable numerical model. To date, the highest quality images from our prototype system have been achieved utilizing a single transmitter/single receiver measurement system where both antennas are manually repositioned to facilitate multiple illuminations of the imaging region, thus requiring long data acquisition times. In an effort to develop a system that can acquire data in a real time manner, a 32-channel network has been fabricated with all ports capable of being electronically selected for either transmit or receive mode. The presence of a complete array of antenna elements at data collection time perturbs the field distributions being measured, which can subsequently degrade the image reconstruction due to increased data-model mismatch. Incorporating the nonactive antenna-compensation model from Part I of this paper into our hybrid element near field image reconstruction algorithm is shown to restore image quality when fixed antenna-array data acquisition is used. Improvements are most dramatic for inclusions located in near proximity to the antenna array itself, although cases of improvement in the recovery of centered heterogeneities are also illustrated. Increases in the frequency of illumination are found to warrant an increased need for nonactive antenna compensation. Quantitative measures of recovered inclusion shape and position reveal a systematic improvement in image reconstruction quality when the nonactive antenna-compensation model is employed. Improvements in electrical property value recovery of localized heterogeneities are also observed. Image reconstructions in freshly excised breast tissue illustrate the applicability of the approach when used with our two-dimensional microwave imaging system.

Nonactive antenna compensation for fixed-array microwave imaging--Part I: Model development

Fixed-array microwave imaging with multisensor data acquisition can suffer from nonactive antenna element interactions which cause distortions in the measurements. In Part I of a two-part paper, we develop a nonactive antenna compensation model for incorporation in model-based near-field microwave image reconstruction methods. The model treats the nonactive members of the antenna array as impedance boundary conditions applied over a cylindrical surface of finite radius providing two parameters, the effective antenna radius and impedance factor, which can be determined empirically from measured data. Results show that the effective radius and impedance factor provide improved fits to experimental data in homogeneous phantoms where measurements are obtained with and without the presence of the nonactive antenna elements. Once deduced, these parameters are incorporated into the nonactive antenna compensation model and lead to systematic data-model match improvements in heterogeneous phantoms. While the improvements afforded by the nonactive antenna model are small on a per measurement basis, they are not insignificant. As shown in Part II, inclusion of this new model for nonactive antenna compensation produces significantly higher quality image reconstructions from measurements obtained with a fixed-array data acquisition system over the frequency band 500-900 MHz.

Non-invasive thermal assessment of tissue phantoms using an active near field microwave imaging technique

An active microwave imaging system for non-invasive temperature sensing has been developed and evaluated. The system is designed to assess biological tissues undergoing thermal therapy. This paper presents results that demonstrate the imaging capabilities of the microwave method using simulated and experimental phantom materials. Results from both numerical studies and laboratory experiments have been analysed and are presented. The imaging system uses a 16 channel fixed monopole array transceiver unit operating over a bandwidth of 300-900 MHz. The annular array diameter is 14.75 cm and is immersed in a 0.9% saline solution. Standard heterodyning principles are used for signal detection leading to a dynamic range of the system of better than 115dB. Image formation is accomplished with a 2-D finite element based, near-field iterative technique. This allows the simultaneous reconstruction of both the real and imaginary components of the dielectric property distribution in tissue equivalent phantoms. Data acquisition currently captures 144 complex field measurements per image. Image reconstruction requires approximately 2 min per iteration with a typical convergence in less than 10 steps. Experiments performed to evaluate the temperature dependence of biological phantoms (saline with variable salt concentrations) are described. The numerical accuracy and precision of the reconstruction algorithm based upon these phantom studies are presented. Simple laboratory models of localized hyperthermia have been used to evaluate the experimental accuracy and precision of the imaging system. A numerical precision of 0.02 degrees C and an accuracy of 0.37 degrees C have been observed with the current algorithm. In laboratory experiments, images have been reconstructed at different target temperatures and target saline concentrations. The effect of placing high contrast biological phantoms (i.e. bone/fat simulants) along with the heated objects have also been studied. Localized heating of the biological phantom is achieved by pumping a saline solution of pre-selected concentration through enclosed ends of hollow dielectric cylinders having approximately 5cm inner diameter and 4 mm wall thickness. The temperature of the heated zone is preset and maintained to +/-0.2 degrees C by an external heater and circulator. The results currently show that a maximum temperature precision of 0.98 degrees C and maximum relative accuracy of 0.56 degrees C has been achieved in the laboratory using the current generation of the prototype system.

Quantitative microwave imaging with a 2.45-GHz planar microwave camera

This paper presents microwave tomographic reconstructions of the complex permittivity of lossy dielectric objects immersed in water from experimental multiview near-field data obtained with a 2.45-GHz planar active microwave camera. An iterative reconstruction algorithm based on the Levenberg-Marquardt method was used to solve the nonlinear matrix equation which results when applying a moment method to the electric field integral representation. The effects of uncertainties in experimental parameters such as the exterior medium complex permittivity, the imaging system geometry and the incident field at the object location are illustrated by means of reconstructions from synthetic data. It appears that the uncertainties in the incident field have the strongest impact on the reconstructions. A receiver calibration procedure has been implemented and some ways to access to the incident field at the object location have been assessed.

Two-dimensional temperature estimation using diagnostic ultrasound

A two-dimensional temperature estimation method was developed based on the detection of shifts in echo location of backscattered ultrasound from a region of tissue undergoing thermal therapy. The echo shifts are due to the combination of the local temperature dependence of speed of sound and thermal expansion in the heated region. A linear relationship between these shifts and the underlying tissue temperature rise is derived from first principles and experimentally validated. The echo shifts are estimated from the correlation of successive backscattered ultrasound frames, and the axial derivative of the accumulated echo shifts is shown to be proportional to the temperature rise. Sharp lateral gradients in the temperature distribution introduce ripple on the estimates of the echo shifts due to a thermo-acoustic lens effect. This ripple can be effectively reduced by filtering the echo shifts along the axial and lateral directions upon differentiation. However, this is achieved at the expense of spatial resolution. Experimental evaluation of the accuracy (0.5 degrees C) and spatial resolution (2 mm) of the algorithm in tissue mimicking phantoms was conducted using a diagnostic ultrasound imaging scanner and a therapeutic ultrasound unit. The estimated temperature maps were overlaid on the gray-scale ultrasound images to illustrate the applicability of this technique for image guidance of focused ultrasound thermal therapy.