Approximately 1 in 8 women will develop breast cancer in their lifetime. Estimates suggest 230,500 new
cases of invasive breast cancer in 2011, resulting in approximately 40,000 deaths. Traditional screening
technologies, such as X-ray mammography use ionizing radiation and suffer from high false-positive
and false-negative rates. Due to the high contrast that exists between the dielectric properties of normal
and abnormal breast tissue, microwave-imaging spectroscopy has proven an attractive breast cancer
imaging modality. We have shown that the incorporation of a volume’s internal structural information
into our image reconstruction algorithm can increase the accuracy of recovered dielectric properties.
Additionally, image reconstruction has benefited from the use of a custom reconstruction mesh
generated from the imaged volume’s perimeter boundary. This information is used in a conformal
microwave image (CMI) reconstruction process, and has increased the accuracy of recovered high
contrast regions within the volume’s perimeter without the use of prior internal spatial information. In
simulation and phantom experiments with regular geometries, boundary information is obtained
through spatial measurements. For irregularly shaped boundaries, alternative means are necessary for
accurate boundary extraction. In this paper we demonstrate the MR-guided CMI reconstruction
process for an irregularly shaped boundary; boundary information extracted from MR images will be
used to generate a custom boundary-derived mesh for microwave image reconstruction. Results from
images reconstructed using the MR-guided CMI reconstruction process will be compared with
uniformly reconstructed images, highlighting the increased accuracy of high contrast features within
the volume without the use of prior internal spatial information.
KEYWORDS: Microwave imaging, 3D image processing, Dielectrics, Microwave radiation, Tissues, Chemical elements, Breast cancer, Magnetic resonance imaging, Reconstruction algorithms, Breast
Microwave imaging for biomedical applications, especially for early detection of breast cancer and effective treatment
monitoring, has attracted increasing interest in last several decades. This fact is due to the high contrast between the
dielectric properties of the normal and malignant breast tissues at microwave frequencies. The available range of
dielectric properties for different soft tissue can provide important functional information about tissue health.
Nonetheless, one of the limiting weaknesses of microwave imaging is that unlike conventional modalities, such as X-ray
CT or MRI, it inherently cannot provide high-resolution images. The conventional modalities can produce highly
resolved anatomical information but often cannot provide the functional information required for diagnoses. Previously,
we have developed a regularization strategy that can incorporate prior anatomical information from MR or other sources
and use it in a way to refine the resolution of the microwave images, while also retaining the functional nature of the
reconstructed property values. In the present work, we extend the use of prior structural information in microwave
imaging from 2D to 3D. This extra dimension adds a significant layer of complexity to the entire image reconstruction
procedure. In this paper, several challenges with respect to the 3D microwave imaging will be discussed and the results
of a series of 3D simulation and phantom experiments with prior structural information will be studied.
KEYWORDS: Microwave radiation, Ultrasonography, Liver, Transducers, Temperature metrology, Tissues, Dielectrics, Antennas, In vivo imaging, Thermography
High intensity focused ultrasound (HIFU) uses focused ultrasound beams to ablate localized tumors noninvasively.
Multiple clinical trials using HIFU treatment of liver, kidney, breast, pancreas and brain tumors have been conducted,
while monitoring the temperature distribution with various imaging modalities such as MRI, CT and ultrasound. HIFU
has achieved only minimal acceptance partially due to insufficient guidance from the limited temperature monitoring
capability and availability. MR proton resonance frequency (PRF) shift thermometry is currently the most effective
monitoring method; however, it is insensitive in temperature changes in fat, susceptible to motion artifacts, and is high
cost. Exploiting the relationship between dielectric properties (i.e. permittivity and conductivity) and tissue temperature,
in vivo dielectric property distributions of tissue during heating were reconstructed with our microwave tomographic
imaging technology. Previous phantom studies have demonstrated sub-Celsius temperature accuracy and sub-centimeter
spatial resolution in microwave thermal imaging. In this paper, initial animal experiments have been conducted to further
investigate its potential. In vivo conductivity changes inside the piglet's liver due to focused ultrasound heating were
observed in the microwave images with good correlation between conductivity changes and temperature.
Microwave imaging for biomedical applications, especially for early detection of breast cancer and effective treatment
monitoring, has attracted increasing interest in last several decades. This fact is due to the high contrast between the
dielectric properties of the normal and malignant breast tissues at microwave frequencies ranging from high megahertz to
low gigahertz. The available range of dielectric properties for different soft tissue can provide considerable functional
information about tissue health. Nonetheless, one of the limiting weaknesses of microwave imaging is, unlike that for
conventional modalities such as X-ray CT or MRI, it cannot inherently provide high-resolution images. The conventional
modalities can produce highly resolved anatomical information but often cannot provide the functional information
required for diagnoses. We have developed a soft prior regularization strategy that can incorporate the prior anatomical
information from X-ray CT, MR or other sources, and use it in a way to exploit the resolution of these images while also
retaining the functional nature of the microwave images. The anatomical information is first used to create an imaging
zone mesh, which segments separate internal substructures, and an associated weighting matrix that numerically groups
the values of closely related nodes within the mesh. This information is subsequently used as a regularizing term for the
Gauss-Newton reconstruction algorithm. This approach exploits existing technology in a systematic way without
making potentially biased assumptions about the properties of visible structures. In this paper we continue our initial
investigation on this matter with a series of breast-shaped simulation and phantom experiments.
Microwave imaging for breast cancer detection is becoming a promising alternative technique to current imaging
modalities. The significant contrast between dielectric properties of normal and malignant breast tissues makes
microwave imaging a useful technique to provide important functional information for diagnoses. However, one of its
limitations is that it intrinsically cannot produce high resolution images as other conventional techniques such as MRI or
X-ray CT do. Those modalities are capable of producing high quality anatomical images, but unlike microwave imaging,
they often cannot provide the necessary functional information about tissue health. In order to refine the resolution of the
microwave images while also preserving the functional information, we have recently developed a new strategy, called
soft prior regularization. In this new approach, the prior anatomical information of the tissue from either x-ray, MR or
other sources is incorporated into our microwave imaging reconstruction algorithm through the following steps: First, the
anatomical information is used to create a reconstruction mesh which defines the boundaries of different internal regions.
Second, based on location of each mesh node, an associated weighting matrix is defined, such that all nodes within each
region are grouped with each other. Finally, the soft prior matrix is used as a regularizing term for our original Gauss-
Newton reconstruction algorithm. Results from initial phantom experiments show a significant improvement in the
recovered dielectric properties.
We are developing a microwave tomographic imaging system for
non-invasive monitoring of temperature changes
during thermal therapy, based on the known tissue conductivity temperature dependence. As with any monitoring
system, the actual integration with a therapy device is a significant challenge. The combined high intensity focused
ultrasound (HIFU)/microwave imaging approach is intriguing because the necessary characteristics for the microwave
data gathering (highly EM attenuating coupling liquid) are not compromised by the HIFU requirements (low ultrasound
attenuating coupling liquid) since the physics of the two wave propagations are quite different. We have previously
reported results for a configuration for use in breast cancer treatment where the HIFU transducer was positioned within
the array of coaxial support rods of the antennas which surrounded the breast while the ultrasound beam propagated
towards the breast without being obstructed by the antennas. For our new implementation, we have positioned the
heating device outside the antenna array and aimed the beam directly past the monopole antennas to the target tissue
within. This configuration is particularly useful for various other anatomical sites where it is not possible to position the
transducer inside the antenna array, such as for vital organs in the torso. Our initial results illustrate that the ultrasound
beam is not significantly impaired by the presence of the microwave antennas and that the beam is readily steerable to
desired locations. Additional dynamic experiments demonstrate good correlation between actual temperature rise and
conductivity decreases in targeted positions. These results set the stage for actual animal experiments.
KEYWORDS: Microwave radiation, Magnetic resonance imaging, Tissues, Absorption, Magnetism, Scanners, Computer programming, Magnetoencephalography, Waveguides, Signal to noise ratio
We have used phase contrast magnetic resonance gradients to image small displacements induced by a pulsed 434
MHz microwave field. Thermoelastic expansions, which are related to the tissues' local microwave absorption
properties and the applied microwave field distribution are encoded into the phase of MR images. The imaging
principles are applicable to other irradiation sources. Initial efforts to develop the signal generation and control
necessary for synchronous pulsed microwave power deposition and MR image acquisition have been successful.
Preliminary results suggest that MR phase accumulation associated with microwave power deposition in a
localized absorber has been observed.
We are developing a scanned focused ultrasound system for hyperthermia treatment of breast cancer. Focused ultrasound has significant potential as a therapy delivery device because it can focus sufficient heating energy below the skin surface with minimal damage to intervening tissue. However, as a practical therapy system, the focal zone is generally quite small and requires either electronic (in the case of a phased array system) or mechanical steering (for a fixed bowl transducer) to cover a therapeutically useful area. We have devised a simple automated steering system consisting of a focused bowl transducer supported by three vertically movable rods which are connected to computer controlled linear actuators. This scheme is particularly attractive for breast cancer hyperthermia where the support rods can be fed through the base of a liquid coupling tank to treat tumors within the breast while coupled to our noninvasive microwave thermal imaging system. A MATLAB routine has been developed for controlling the rod motion such that the beam focal point scans a horizontal spiral and the subsequent heating zone is cylindrical. In coordination with this effort, a 3D finite element thermal model has been developed to evaluate the temperature distributions from the scanned focused heating. In this way, scanning protocols can be optimized to deliver the most uniform temperature rise to the desired location.
Microwave imaging has been investigated as a method of non-invasively estimating tissue electrical properties especially the conductivity, which is highly temperature dependent, as a means of monitoring thermal therapy. The technique we have chosen utilizes an iterative Gauss-Newton approach to converge on the correct property distribution. A previous implementation utilizing the complex form (CF) of the electric fields along with a sub-optimal phantom experimental configuration resulted in imaging temperature accuracy of only 1.6°C. Applying the log-magnitude/phase form (LMPF) of the algorithm has resulted in imaging accuracy on the order of 0.3°C which is a significant advance for the area of treatment monitoring. The LMPF algorithm was originally introduced as a way to reconstruct images of large, high-contrast scatterers as is the case in breast imaging. However, recent analysis of the Jacobian matrices for the comparable implementations has shown that the reconstruction problem in the new formulation more closely resembles a linear task as is the case in x-ray computed tomography. The comparisons were performed by examining plots of the Jacobian matrix terms for fixed transmit and receive antennas which demonstrated higher sensitivity in the center of the imaging zone along with narrower paths of senstivity between the atnenna pair for the LMPF algorithm. Animal model experiments have also been performed to validate these capabilities in a more realistic setting. Finally, the overall computational efficiency has been significantly enhanced through the use of the adjoint image reconstruction approach. This enables us to reconstruct images in roughly one minute which is essential if the approach is to be used as a therapy feedback mechanism.
The desire for noninvasive monitoring of thermal therapy is readily apparent given its intent to be a minimally-invasive form of treatment. Electromagnetic properties of tissue vary with temperature; hence, the opportunity exists to exploit these variations as a means of following thermally-based therapeutic interventions. The review describes progress in electrical impedance tomography and active microwave imaging towards the realization of noninvasive temperature estimation. Examples are drawn from the author's experiences with these technologies in order to illustrate the principles and practices associated with electromagnetic imaging in the therapy monitoring context.
A laboratory scale multi-illumination microwave imaging system has been successfully demonstrated for the reconstruction of biologically relevant materials and has also been shown to be sensitive to thermally induced electrical property changes. Several challenges are currently being addressed in an effort to bring the system to the clinic for use in non-invasive thermometry. These include: (1) increasing the size of the imaging region, (2) reducing image artifacts due to the presence of multiple antennas during illumination, and (3) developing a solid illumination chamber to replace the saline bath tank. The first two are intimately related. As the imaging system size is increased to clinically useful dimensions, we must inevitably reduce the lossiness of the surrounding medium which will subsequently increase the antenna-antenna interactions. This is being addressed both in terms of the design of the individual antennas and in terms of introducing compensating techniques into the numerical model. Investigating these areas will provide insight into the ultimate capability of this imaging modality. Additionally, a solid material is being developed with electrical properties close to that of saline. Working in such a lossy medium has significant advantages in terms of the antenna performance and the reduction of unwanted multi- path signals propagating into and out of the desired imaging plane. With these tasks completed, quantification of the system's ability to recover electrical property distributions and thermal profiles based on difference imaging techniques will be investigated for both phantom and in vitro experiments.
Knowledge of the spatial distribution of intensity loss from an ultrasonic beam is critical to predicting lesion formation in focused ultrasound surgery. To date most models have used linear propagation models to predict the intensity profiles needed to compute the temporally varying temperature distributions. These can be used to compute thermal dose contours that can in turn be used to predict the extent of thermal damage. However, these simulations fail to adequately describe the abnormal lesion formation behavior observed for in vitro experiments in cases where the transducer drive levels are varied over a wide range. For these experiments, the extent of thermal damage has been observed to move significantly closer to the transducer with increasing transducer drive levels than would be predicted using linear propagation models. The simulations described herein, utilize the KZK (Khokhlov-Zabolotskaya-Kuznetsov) nonlinear propagation model with the parabolic approximation for highly focused ultrasound waves, to demonstrate that the positions of the peak intensity and the lesion do indeed move closer to the transducer. This illustrates that for accurate modeling of heating during FUS, nonlinear effects must be considered.
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