KEYWORDS: Tomography, 3D image processing, Breast, Signal attenuation, Breast imaging, Reconstruction algorithms, Breast cancer, Mammography, Visualization, Ultrasonography, 3D modeling, Wave propagation, Transducers, Cancer
Frequency-domain ultrasound waveform tomography is a promising method for the visualization and characterization of breast disease. It has previously been shown to accurately reconstruct the sound speed distributions of breasts of varying densities. The reconstructed images show detailed morphological and quantitative information that can help differentiate different types of breast disease including benign and malignant lesions. The attenuation properties of an ex vivo phantom have also been assessed. However, the reconstruction algorithms assumed a 2D geometry while the actual data acquisition process was not. Although clinically useful sound speed images can be reconstructed assuming this mismatched geometry, artifacts from the reconstruction process exist within the reconstructed images. This is especially true for registration across different modalities and when the 2D assumption is violated. For example, this happens when a patient’s breast is rapidly sloping. It is also true for attenuation imaging where energy lost or gained out of the plane gets transformed into artifacts within the image space. In this paper, we will briefly review ultrasound waveform tomography techniques, give motivation for pursuing the 3D method, discuss the 3D reconstruction algorithm, present the results of 3D forward modeling, show the mismatch that is induced by the violation of 3D modeling via numerical simulations, and present a 3D inversion of a numerical phantom.
KEYWORDS: Tomography, Signal attenuation, Ultrasonography, Breast, Mammography, Breast cancer, Breast imaging, Visualization, Reconstruction algorithms, Tumor growth modeling, Tissues, Numerical simulations, Transducers, Data modeling, Cancer
Ultrasound waveform tomography techniques have shown promising results for the visualization and characterization of breast disease. By using frequency-domain waveform tomography techniques and a gradient descent algorithm, we have previously reconstructed the sound speed distributions of breasts of varying densities with different types of breast disease including benign and malignant lesions. By allowing the sound speed to have an imaginary component, we can model the intrinsic attenuation of a medium. We can similarly recover the imaginary component of the velocity and thus the attenuation. In this paper, we will briefly review ultrasound waveform tomography techniques, discuss attenuation and its relations to the imaginary component of the sound speed, and provide both numerical and ex vivo examples of waveform tomography attenuation reconstructions.
KEYWORDS: Breast imaging, Ultrasound tomography, Ultrasonography, Data modeling, Breast, Image filtering, Wave propagation, Data acquisition, Transducers, Signal attenuation, Image quality
Conventional ultrasonography reconstruction techniques, such as B-mode, are based on a simple wave propagation model derived from a high frequency approximation. Therefore, to minimize model mismatch, the central frequency of the input pulse is typically chosen between 3 and 15 megahertz. Despite the increase in theoretical resolution, operating at higher frequencies comes at the cost of lower signal-to-noise ratio. This ultimately degrades the image contrast and overall quality at higher imaging depths. To address this issue, we investigate a reflection imaging technique, known as reverse time migration, which uses a more accurate propagation model for reconstruction. We present preliminary simulation results as well as physical phantom image reconstructions obtained using data acquired with a breast imaging ultrasound tomography prototype. The original reconstructions are filtered to remove low-wavenumber artifacts that arise due to the inclusion of the direct arrivals. We demonstrate the advantage of using an accurate sound speed model in the reverse time migration process. We also explain how the increase in computational complexity can be mitigated using a frequency domain approach and a parallel computing platform.
KEYWORDS: Tomography, Breast, Magnetic resonance imaging, Prototyping, Tissues, Data acquisition, Tumors, In vivo imaging, Ultrasonography, Ultrasound tomography
Ultrasound tomography is a promising modality for breast imaging. Many current ultrasound tomography imaging algorithms are based on ray theory and assume a homogeneous background which is inaccurate for complex heterogeneous regions. They fail when the size of lesions approaches the wavelength of ultrasound used. Therefore, to accurately image small lesions, wave theory must be used in ultrasound imaging algorithms to properly handle the heterogeneous nature of breast tissue and the diffraction effects that it induces. Using frequency-domain ultrasound waveform tomography, we present sound speed reconstructions of both a tissue-mimicking breast phantom and in vivo data sets. Significant improvements in contrast and resolution are made upon the previous ray based methods. Where it might have been difficult to differentiate a high sound speed tumor from bulk breast parenchyma using ray based methods, waveform tomography improves the shape and margins of a tumor to help more accurately differentiate it from the bulk breast tissue. Waveform tomography sound speed imaging might improve the ability of finding lesions in very dense tissues, a difficult environment for mammography. By comparing the sound speed images produced by waveform tomography to MRI, we see that the complex structures in waveform tomography are consistent with those in MRI. The robustness of the method is established by reconstructing data acquired by two different ultrasound tomography prototypes.
KEYWORDS: Breast, Cancer, Tissues, Ultrasonography, In vivo imaging, Mammography, Elastography, Signal attenuation, Ultrasound tomography, Imaging systems
A number of clinical trials have shown that screening ultrasound, supplemental to mammography, detects additional cancers in women with dense breasts. However, labor intensity, operator dependence and high recall rates have limited adoption. This paper describes the use of ultrasound tomography for whole-breast tissue stiffness measurements as a first step toward addressing the issue of high recall rates. The validation of the technique using an anthropomorphic phantom is described. In-vivo applications are demonstrated on 13 breast masses, indicating that lesion stiffness correlates with lesion type as expected. Comparison of lesion stiffness measurements with standard elastography was available for 11 masses and showed a strong correlation between the 2 measures. It is concluded that ultrasound tomography can map out the 3 dimensional distribution of tissue stiffness over the whole breast. Such a capability is well suited for screening where additional characterization may improve the specificity of screening ultrasound, thereby lowering barriers to acceptance.
We describe the clinical performance of SoftVue, a breast imaging device based on the principles of ultrasound tomography. Participants were enrolled in an IRB-approved study at Wayne State University, Detroit, MI. The main research findings indicate that SoftVue is able to image the whole uncompressed breast up to cup size H. Masses can be imaged in even the densest breasts with the ability to discern margins and mass shapes. Additionally, it is demonstrated that multi-focal disease can also be imaged. The system was also tested in its research mode for additional imaging capabilities. These tests demonstrated the potential for generating tissue stiffness information for the entire breast using through-transmission data. This research capability differentiates SoftVue from the other whole breast systems on the market. It is also shown that MRI-like images can be generated using alternative processing of the echo data. Ongoing research is focused on validating and quantifying these findings in a larger sample of study participants and quantifying SoftVue's ability to differentiate benign masses from cancer.
Ultrasound tomography is a modality that can be used to image various characteristics of the breast, such as sound speed, attenuation, and reflectivity. In the considered setup, the breast is immersed in water and scanned along the coronal axis from the chest wall to the nipple region. To improve image visualization, it is desirable to remove the water background. To this end, the 3D boundary of the breast must be accurately estimated. We present an iterative algorithm based on active contours that automatically detects the boundary of a breast using a 3D stack of attenuation images obtained from an ultrasound tomography scanner. We build upon an existing method to design an algorithm that is fast, fully automated, and reliable. We demonstrate the effectiveness of the proposed technique using clinical data sets.
KEYWORDS: Tomography, Signal attenuation, Ultrasonography, Breast, Data modeling, Breast imaging, Tissues, Ultrasound tomography, Medical imaging, Wave propagation
Ultrasound tomography is an emerging modality for breast imaging. However, most current ultrasonic tomography imaging algorithms, historically hindered by the limited memory and processor speed of computers, are based on ray theory and assume a homogeneous background which is inaccurate for complex heterogeneous regions. Therefore, wave theory, which accounts for diffraction effects, must be used in ultrasonic imaging algorithms to properly handle the heterogeneous nature of breast tissue in order to accurately image small lesions. However, application of waveform tomography to medical imaging has been limited by extreme computational cost and convergence. By taking advantage of the computational architecture of Graphic Processing Units (GPUs), the intensive processing burden of waveform tomography can be greatly alleviated. In this study, using breast imaging methods, we implement a frequency domain waveform tomography algorithm on GPUs with the goal of producing high-accuracy and high-resolution breast images on clinically relevant time scales. We present some simulation results and assess the resolution and accuracy of our waveform tomography algorithms based on the simulation data.
For women with dense breast tissue, who are at much higher risk for developing breast cancer, the performance of mammography is at its worst. Consequently, many early cancers go undetected when they are the most treatable. Improved cancer detection for women with dense breasts would decrease the proportion of breast cancers diagnosed at later stages, which would significantly lower the mortality rate. The emergence of whole breast ultrasound provides good performance for women with dense breast tissue, and may eliminate the current trade-off between the cost effectiveness of mammography and the imaging performance of more expensive systems such as magnetic resonance imaging. We report on the performance of SoftVue, a whole breast ultrasound imaging system, based on the principles of ultrasound tomography. SoftVue was developed by Delphinus Medical Technologies and builds on an early prototype developed at the Karmanos Cancer Institute. We present results from preliminary testing of the SoftVue system, performed both in the lab and in the clinic. These tests aimed to validate the expected improvements in image performance. Initial qualitative analyses showed major improvements in image quality, thereby validating the new imaging system design. Specifically, SoftVue’s imaging performance was consistent across all breast density categories and had much better resolution and contrast. The implications of these results for clinical breast imaging are discussed and future work is described.
Conventional sonography, which performs well in dense breast tissue and is comfortable and radiation-free, is
not practical for screening because of its operator dependence and the time needed to scan the whole breast.
While magnetic resonance imaging (MRI) can significantly improve on these limitations, it is also not
practical because it has long been prohibitively expensive for routine use. There is therefore a need for an
alternative breast imaging method that obviates the constraints of these standard imaging modalities. The
lack of such an alternative is a barrier to dramatically impacting mortality (about 45,000 women in the US per
year) and morbidity from breast cancer because, currently, there is a trade-off between the cost effectiveness
of mammography and sonography on the one hand and the imaging accuracy of MRI on the other. This paper
presents a progress report on our long term goal to eliminate this trade-off and thereby improve breast cancer
survival rates and decrease unnecessary biopsies through the introduction of safe, cost-effective, operatorindependent
sonography that can rival MRI in accuracy.
The objective of the study described in this paper was to design and build an improved ultrasound
tomography (UST) scanner in support of our goals. To that end, we report on a design that builds on our
current research prototype. The design of the new scanner is based on a comparison of the capabilities of our
existing prototype and the performance needed for clinical efficacy. The performance gap was quantified by
using clinical studies to establish the baseline performance of the research prototype, and using known MRI
capabilities to establish the required performance. Simulation software was used to determine the basic
operating characteristics of an improved scanner that would provide the necessary performance. Design
elements focused on transducer geometry, which in turn drove the data acquisition system and the image
reconstruction engine specifications. The feasibility of UST established by our earlier work and that of other
groups, forms the rationale for developing a UST system that has the potential to become a practical, low-cost
device for breast cancer screening and diagnosis.
Accurate time delay estimation is critical for a wide range of remote sensing applications. We propose a technique
that exploits the redundancy between absolute and relative time delays in transducer arrays as a means to reduce
the level of noise present in the measurements. We formalize the problem of interest and present two different
strategies to solve it. The first strategy is optimal in the mean square sense but requires a quadratic programming
solver. The second approach is based on a sub-optimal iterative denoising technique. The effectiveness of our
approach is demonstrated in the context of travel time tomographic imaging using numerical and physical breast
mimicking phantoms as well as patient data.
KEYWORDS: Transducers, Calibration, Denoising, Signal to noise ratio, Ultrasonography, Error analysis, Breast cancer, Ultrasound tomography, Tomography, Time metrology
Accurate calibration is a requirement of many array signal processing techniques. We investigate the calibration
of a transducer array using time delays. We derive a strategy based on the mean square error criterion and
discuss how time delays that are not available can be interpolated from existing ones. The proposed method is
made robust to noise and model mismatch by means of a novel iterative technique for distance matrix denoising.
The convergence of the method is proved. Finally, the accuracy of the proposed calibration algorithm is assessed
both in simulated scenarios and using experimental data obtained from an ultrasound scanner designed for breast
cancer detection.
Conventional ultrasound techniques use beam-formed, constant sound speed ray models for fast image reconstruction.
However, these techniques are inadequate for the emerging new field of ultrasound tomography (UST). We
present a new technique for the reconstruction of reflection images from UST data. We have extended the planar Kirchhoff
migration method used in geophysics, and combined it with sound speed and attenuation data obtained from the
transmission signals to create reflection ultrasound images that are corrected for refractive and attenuative effects. The
resulting technique was applied to in-vivo breast data obtained with an experimental prototype. The results indicate that
sound speed and attenuation corrections lead to considerable improvements in image quality, particularly in dense tissues
where the refractive and scattering effects are the greatest.
We present a bent ray reconstruction algorithm for an ultrasound tomography (UT) scanner designed for breast
screening. The scanner consists of a circular array of transmitters and receivers which encloses the object to be
imaged. By solving a nonlinear system of equations, the reconstruction algorithm estimates the sound speed of
the object using the set of travel-time measurements. The main difficulty in this inverse problem is to ensure the
convergence and robustness to noise. In this paper, we propose a gradient method to find a solution for which
the corresponding travel-times are closest to the measured travel-times in the least squares sense. To this end,
first the gradient of the cost function is derived using Fermat's Principle. Then, the iterative nonlinear conjugate
gradient algorithm solves the minimization problem. This is combined with the backtracking line search method
to efficiently find the step size in each iteration. This approach is guaranteed to converge to a local minimum
of the cost function where the convergence point depends on the initial guess. Moreover, the method has the
potential to easily incorporate regularity constraints such as sparsity as a priori information on the model. The method is tested both numerically and using in vivo data obtained from a UT scanner. The results confirm the stability and robustness of our approach for breast screening applications.
We present preliminary results obtained using a time domain wave-based reconstruction algorithm for an ultrasound
transmission tomography scanner with a circular geometry. While a comprehensive description of this type of algorithm has already been given elsewhere, the focus of this work is on some practical issues arising with this approach. In fact, wave-based reconstruction methods suffer from two major drawbacks which limit their application in a practical setting: convergence is difficult to obtain and the computational cost is prohibitive. We address the first problem by appropriate initialization using a ray-based reconstruction. Then, the complexity of the method is reduced by means of an efficient parallel implementation on graphical processing units (GPU). We provide a mathematical derivation of the wave-based method under consideration, describe some details of our implementation and present simulation results obtained with a numerical phantom designed for a breast cancer detection application. The source code of our GPU implementation is freely available on the web at www.usense.org.
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