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

Microwave Antenna System for Muscle Rupture Imaging with a Lossy Gel to Reduce Multipath Interference

Injuries to the hamstring muscles are an increasing problem in sports. Imaging plays a key role in diagnosing and managing athletes with muscle injuries, but there are several problems with conventional imaging modalities with respect to cost and availability. We hypothesized that microwave imaging could provide improved availability and lower costs and lead to improved and more accurate diagnostics. In this paper, a semicircular microwave imaging array with eight antennae was investigated. A key component in this system is the novel antenna design, which is based on a monopole antenna and a lossy gel. The purpose of the gel is to reduce the effects of multipath signals and improve the imaging quality. Several different gels have been manufactured and evaluated in imaging experiments. For comparison, corresponding simulations were performed. The results showed that the gels can effectively reduce the multipath signals and the imaging experiments resulted in significantly more stable and repeatable reconstructions when a lossy gel was used compared to when an almost non-lossy gel was used.

Quantitative Interpretation of UWB Radar Images for Non-Invasive Tissue Temperature Estimation during Hyperthermia

The knowledge of temperature distribution inside the tissue to be treated is essential for patient safety, workflow and clinical outcomes of thermal therapies. Microwave imaging represents a promising approach for non-invasive tissue temperature monitoring during hyperthermia treatment. In the present paper, a methodology for quantitative non-invasive tissue temperature estimation based on ultra-wideband (UWB) radar imaging in the microwave frequency range is described. The capabilities of the proposed method are demonstrated by experiments with liquid phantoms and three-dimensional (3D) Delay-and-Sum beamforming algorithms. The results of our investigation show that the methodology can be applied for detection and estimation of the temperature induced dielectric properties change.

Addressing Multipath Signal Corruption in Microwave Tomography and the Influence on System Design and Algorithm Development

In developing a microwave tomography system, we started by examining the fundamental signal measurement challenges-i.e., how to interrogate the target while suppressing unwanted multi-path signals. Beginning with a lossy coupling bath to suppress unwanted surface waves, we have developed a robust and reliable system that is both simple and low profile. However, beyond the basic measurement configuration, the lossy coupling medium concept has also informed our choice of array antenna and imaging algorithms. The synergism of these concepts has produced a novel concept which is embodied in a system that has been successfully translated to the clinic.

3D microwave tomography of the breast using prior anatomical information

PURPOSE

The authors have developed a new 3D breast image reconstruction technique that utilizes the soft tissue spatial resolution of magnetic resonance imaging (MRI) and integrates the dielectric property differentiation from microwave imaging to produce a dual modality approach with the goal of augmenting the specificity of MR imaging, possibly without the need for nonspecific contrast agents. The integration is performed through the application of a soft prior regularization which imports segmented geometric meshes generated from MR exams and uses it to constrain the microwave tomography algorithm to recover nearly uniform property distributions within segmented regions with sharp delineation between these internal subzones.

METHODS

Previous investigations have demonstrated that this approach is effective in 2D simulation and phantom experiments and also in clinical exams. The current study extends the algorithm to 3D and provides a thorough analysis of the sensitivity and robustness to misalignment errors in size and location between the spatial prior information and the actual data.

RESULTS

Image results in 3D were not strongly dependent on reconstruction mesh density, and the changes of less than 30% in recovered property values arose from variations of more than 125% in target region size-an outcome which was more robust than in 2D. Similarly, changes of less than 13% occurred in the 3D image results from variations in target location of nearly 90% of the inclusion size. Permittivity and conductivity errors were about 5 times and 2 times smaller, respectively, with the 3D spatial prior algorithm in actual phantom experiments than those which occurred without priors.

CONCLUSIONS

The presented study confirms that the incorporation of structural information in the form of a soft constraint can considerably improve the accuracy of the property estimates in predefined regions of interest. These findings are encouraging and establish a strong foundation for using the soft prior technique in clinical studies, where their microwave imaging system and MRI can simultaneously collect breast exam data in patients.

Can we settle with single-band radiometric temperature monitoring during hyperthermia treatment of chestwall recurrence of breast cancer using a dual-mode transceiving applicator?

The total thermal dose that can be delivered during hyperthermia treatments is frequently limited by temperature heterogeneities in the heated tissue volume. Reliable temperature information on the heated area is thus vital for the optimization of clinical dosimetry. Microwave radiometry has been proposed as an accurate, quick and painless temperature sensing technique for biological tissue. Advantages include the ability to sense volume-averaged temperatures from subsurface tissue non-invasively, rather than with a limited set of point measurements typical of implanted temperature probes. We present a procedure to estimate the maximum tissue temperature from a single radiometric brightness temperature which is based on a numerical simulation of 3D tissue temperature distributions induced by microwave heating at 915 MHz. The temperature retrieval scheme is evaluated against errors arising from unknown variations in thermal, electromagnetic and design model parameters. Whereas realistic deviations from base values of dielectric and thermal parameters have only marginal impact on performance, pronounced deviations in estimated maximum tissue temperature are observed for unanticipated variations of the temperature or thickness of the bolus compartment. The need to pay particular attention to these latter applicator construction parameters in future clinical implementation of the thermometric method is emphasized.

Microwave thermal imaging: initial in vivo experience with a single heating zone

The deployment of hyperthermia as a routine adjuvant to radiation or chemotherapy is limited largely by the inability to devise treatment plans which can be monitored through temperature distribution feedback during therapy. A non-invasive microwave tomographic thermal imaging system is currently being developed which has previously exhibited excellent correlation between the recovered electrical conductivity of a heated zone and its actual temperature change during phantom studies. To extend the validation of this approach in vivo, the imaging system has been re-configured for small animal experiments to operate within the bore of a CT scanner for anatomical and thermometry registration. A series of 5-7 day old pigs have been imaged during hyperthermia with a monopole antenna array submerged in a saline tank where a small plastic tube surgically inserted the length of the abdomen has been used to create a zone of heated saline at pre-selected temperatures. Tomographic microwave data over the frequency range of 300-1000 MHz of the pig abdomen in the plane perpendicular to the torso is collected at regular intervals after the tube saline temperatures have settled to the desired settings. Images are reconstructed over a range of operating frequencies. The tube location is clearly visible and the recovered saline conductivity varies linearly with the controlled temperature values. Difference images utilizing the baseline state prior to heating reinforces the linear relationship between temperature and imaged saline conductivity. Demonstration of in vivo temperature recovery and correlation with an independent monitoring device is an important milestone prior to clinical integration of this non-invasive imaging system with a thermal therapy device.

Optimization of electromagnetic phased-arrays for hyperthermia via magnetic resonance temperature estimation

A technique for the optimization of electromagnetic annular phased arrays (APAs) for therapeutic hyperthermia has been developed and implemented. The controllable inputs are the amplitudes and phases of the driving signals of each element of the array. Magnetic resonance imaging (MRI) is used to estimate noninvasively the temperature distribution based on the temperature dependence of the proton resonance frequency (PRF). A parametric model of the dynamics that couple the control inputs to the resultant temperature elevations is developed based on physical considerations. The unknown parameters of this model are estimated during a pretreatment identification phase and can be continuously updated as new measurement data become available. Based on the parametric model, a controller automatically chooses optimal phases and amplitudes of the driving signals of the APA. An advantage of this approach to optimizing the APA is that no a priori information is required, eliminating the need for patient-specific computational modeling and optimization. Additionally, this approach represents a first step toward employing temperature feedback to make the optimization of the APA robust with respect to modeling errors and physiological changes. The ability of the controller to choose therapeutically beneficial driving amplitudes and phases is demonstrated via simulation. Experimental results are presented which demonstrate the ability of the controller to choose optimal phases for the APA using only information from magnetic resonance thermometry (MRT).

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.

Engineering aspects of hyperthermia therapy

The continuing accrual of positive results in clinical cancer trials of adjunctive, synergistic hyperthermia therapy remains a strong motivation for the development of improved hyperthermia equipment and software. Indeed, the lack of needed engineering tools can be viewed as the major stumbling block to hyperthermia's effective clinical implementation. Developing clinically effective systems will be difficult, however, because (a) it requires solving several complex engineering problems, for which (b) setting appropriate design and evaluation goals is currently difficult owing to a lack of critical biological, physiological, and clinical knowledge, two tasks which must (c) be accomplished within a complicated social/political structure.

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.

Confidence maps and confidence intervals for near infrared images in breast cancer

This paper extends basic concepts of statistical hypothesis testing and confidence intervals to images generated by a new procedure for near infrared spectroscopic tomography being developed for use in breast cancer diagnosis. By estimating the covariance matrix of the pixels of an image from data used in the image reconstruction process, confidence maps for statistical tests on individual pixels and confidence intervals for entire images are displayed as an aid to research and clinical personnel interpreting possibly noisy images. The methods are applied to simulated and phantom-based images.