Both mammography and standard ultrasound (US) rely upon subjective criteria within the breast imaging reporting and data system (BI-RADS) to provide more uniform interpretation outcomes, as well as differentiation and risk stratification of associated abnormalities. In addition, the technical performance and professional interpretation of both tests suffer from machine and operator dependence. Breast MR has become the new gold standard for screening of high-risk women but has cost and access limitations in extending screening to the entire population. We have been developing a new technique for breast imaging that is based on ultrasound tomography which quantifies tissue characteristics while also producing 3-D images of breast anatomy. Results are presented from clinical studies that utilize this method.
Informed consent was obtained from all patients, prospectively recruited in an IRB-approved protocol following HIPAA guidelines. Images were produced by tomographic algorithms for reflection, sound speed and attenuation. All images were reviewed by a board-certified radiologist who has more than 20 years of experience in breast imaging and US-technology development. In the first phase of the study, UST images were compared to multi-modal imaging to determine the appearance of lesions and breast parenchyma. In the second phase of the study, correlative comparisons with MR breast imaging were used to establish basic operational capabilities of the UST system including the identification and characterization of parenchymal patterns. Our study demonstrated a high degree of correlation of breast tissue structures relative to fat subtracted contrast enhanced MRI. With a scan duration of ~ 1-3 minutes, no significant motion artifacts were observed.
Mammography is not sufficiently effective for women with dense breast tissue – women who are at much higher risk for developing breast cancer. Consequently, many breast cancers go undetected at their treatable stage. Improved cancer detection and characterization for women with dense breast tissue is urgently needed. Our clinical study has shown that ultrasound tomography (UST) is an emerging technique that moves beyond B-mode imaging by its through transmission capabilities. Transmission ultrasound provides additional tissue parameters such as sound speed, attenuation, and through-transmission rendered tissue stiffness information. For women with dense breasts, these parameters can be used to assist in detecting malignant masses within glandular or fatty tissue and differentiating malignant and benign masses. This paper focuses on the use of waveform ultrasound sound speed imaging and tissue stiffness information generated using through-transmission data to characterize different breast tissues and breast masses. In-vivo examples will be given to assess its effectiveness.
KEYWORDS: Signal attenuation, Breast imaging, Breast, Ultrasonography, Image resolution, Tomography, Detection and tracking algorithms, Transducers, In vivo imaging, Ultrasound tomography, Tissues, Reconstruction algorithms, Data modeling
Ex vivo studies using our ultrasound waveform attenuation algorithm have shown promising results for detection and
characterization of lesions of different types. Our preliminary in vivo study shows that the waveform attenuation image
has much higher resolution and can better delineate breast lesions boundaries than the corresponding ray-based attenuation
image. In this study, we preprocessed our time domain waveforms acquired with a ring array and explored the directional
transducer beam pattern to better match calculated wave fields with respect to the acquired wave fields. We have applied
waveform attenuation to in vivo data and compared the resulting waveform attenuation images with the ray-based
counterparts to assess the resolution and accuracy of the waveform attenuation reconstruction.
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.
Waveform inversion methods can produce high-resolution reconstructed sound speed images for ultrasound computed tomography; however, they are very computational expensive. Source encoding methods can reduce this computational cost by formulating the image reconstruction problem as a stochastic optimization problem. Here, we solve this optimization problem by the regularized dual averaging method instead of the more commonly used stochastic gradient descent. This new optimization method allows use of non-smooth regularization functions and treats the stochastic data fidelity term in the objective function separately from the deterministic regularization function. This allows noise to be mitigated more effectively. The method further exhibits lower variance in the estimated sound speed distributions across iterations when line search methods are employed.
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: 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.
Ultrasound computed tomography (USCT) holds great promise for improving the detection and management of breast cancer. Because they are based on the acoustic wave equation, waveform inversion-based reconstruction methods can produce images that possess improved spatial resolution properties over those produced by ray-based methods. However, waveform inversion methods are computationally demanding and have not been applied widely in USCT breast imaging. In this work, source encoding concepts are employed to develop an accelerated USCT reconstruction method that circumvents the large computational burden of conventional waveform inversion methods. This method, referred to as the waveform inversion with source encoding (WISE) method, encodes the measurement data using a random encoding vector and determines an estimate of the speed-of-sound distribution by solving a stochastic optimization problem by use of a stochastic gradient descent algorithm. Computer-simulation studies are conducted to demonstrate the use of the WISE method. Using a single graphics processing unit card, each iteration can be completed within 25 seconds for a 128 × 128 mm2 reconstruction region. The results suggest that the WISE method maintains the high spatial resolution of waveform inversion methods while significantly reducing the computational burden.
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.
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.
Women with high breast density have an increased risk of developing breast cancer. Women treated with the selective estrogen receptor modulator tamoxifen for estrogen receptor positive breast cancer experience a 50% reduction in risk of contralateral breast cancer and overall reduction of similar magnitude has been identified among high-risk women receiving the drug for prevention. Tamoxifen has been shown to reduce mammographic density, and in the IBIS-1 chemoprevention trial, risk reduction and decline in density were significantly associated. Ultrasound tomography (UST) is an imaging modality that can create tomographic sound speed images of the breast. These sound speed images are useful because breast density is proportional to sound speed. The aim of this work is to examine the relationship between USTmeasured breast density and the use of tamoxifen. So far, preliminary results for a small number of patients have been observed and are promising. Correlations between the UST-measured density and
mammographic density are strong and positive, while relationships between UST density with some patient specific risk factors behave as expected. Initial results of UST examinations of tamoxifen treated patients show that approximately 45% of the patients have a decrease in density in the contralateral breast after only several months of treatment. The true effect of tamoxifen on UST-measured density cannot yet be fully determined until more data are collected. However, these promising results suggest that UST can be used to reliably assess quantitative changes in breast density over short intervals and therefore suggest that UST may enable rapid assessment of density changes associated with therapeutic and preventative interventions.
Previous studies concluded that the resolution limitation of travel-time tomography is the width of the first Fresnel
zone. However, we believe that the resolution of ray tomography cannot simply be limited to the first Fresnel zone
and is affected by many factors. In this study, we investigate a variety of factors that affect the resolving power of
travel time tomography. These factors include accuracy of picked travel time, ray coverage (data density) and data
signal-to-noise ratio (SNR). We also investigate to what extent that bent-ray travel-time tomography is capable of
resolving anomalous objects smaller than the first Fresnel zone based on numerical simulations. We have shown that
bent-ray travel-time tomography resolvability and detectability of small objects is better than the first Fresnel zone.
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.
KEYWORDS: Tomography, Breast, Signal attenuation, Ultrasonography, Data modeling, Inverse problems, Process modeling, Data acquisition, In vivo imaging, X-rays
A multi-grid tomographic inversion approach that uses variable grid sizes in both forward modeling and inverse
process is proposed and tested on breast phantom data and breast ultrasound data. In iterative tomographic inversion,
fine scale features are more sensitive to starting model than coarse scale features. The proposed multi-grid algorithm
starts from coarse grids for both forward modeling and inverse process and gradually proceeds to fine grids, which
can effectively suppress artifacts related to over iteration of fine scale features. Since the computational complexity
of inverse problems increases with number of grid points in both forward model and inverse model, the proposed
algorithm greatly reduces the computational cost in contrast to standard fixed-grid approaches. Both in vitro and in
vivo results indicate that the proposed multi-grid methods result in significant improvement in the inverted sound
speed and attenuation images compared to fixed-grid methods.
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.
It is known that breast cancer risk is greater in women with higher breast densities. Currently, breast
density is measured using mammographic percent density, defined as the ratio of fibroglandular to total
breast area on a two dimensional mammogram. Alternatively, systems that use ultrasound tomography
(UST) create tomographic sound speed images of the patient's breast. These volumetric images can be
useful as a diagnostic aid because it is also known that sound speed of tissue is proportional to the density
of the tissue. The purpose of this work is to expand on the comparisons of the two imaging modalities by
introducing new ultrasound tomography measurements that separate and quantify the fatty and dense tissue
distributions within the breast. A total of 249 patients were imaged using both imaging modalities. By
using k-means clustering, correlations beyond the volume averaged sound speed of the ultrasound images
and the mammographic percent density were investigated. Both the ultrasound and mammographic images
were separated into dense and fatty regions. Various associations between the global breast properties as
well as separate tissue components were found.
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.
Despite some shortcomings, mammography is currently the standard of care for breast cancer screening and
diagnosis. However, breast ultrasound tomography is a rapidly developing imaging modality that has the
potential to overcome the drawbacks of mammography. It is known that women with high breast densities
have a greater risk of developing breast cancer. Measuring breast density is accomplished through the use
of mammographic percent density, defined as the ratio of fibroglandular to total breast area. Using an
ultrasound tomography (UST) prototype, we created sound speed images of the patient's breast, motivated
by the fact that sound speed in a tissue is proportional to the density of the tissue. The purpose of this work
is to compare the acoustic performance of the UST system with the measurement of mammographic
percent density. A cohort of 251 patients was studied using both imaging modalities and the results suggest
that the volume averaged breast sound speed is significantly related to mammographic percent density.
The Spearman correlation coefficient was found to be 0.73 for the 175 film mammograms and 0.69 for the
76 digital mammograms obtained. Since sound speed measurements do not require ionizing radiation or
physical compression, they have the potential to form the basis of a safe, more accurate surrogate marker of
breast density.
The objective of this study is to present imaging parameters and display thresholds of an ultrasound tomography (UST)
prototype in order to demonstrate analogous visualization of overall breast anatomy and lesions relative to magnetic
resonance (MR). Thirty-six women were imaged with MR and our UST prototype. The UST scan generated sound
speed, attenuation, and reflection images and were subjected to variable thresholds then fused together into a single UST
image. Qualitative and quantitative comparisons of MR and UST images were utilized to identify anatomical similarities
and mass characteristics. Overall, UST demonstrated the ability to visualize and characterize breast tissues in a manner
comparable to MR without the use of IV contrast. For optimal visualization, fused images utilized thresholds of 1.46±0.1
km/s for sound speed to represent architectural features of the breast including parenchyma. An arithmetic combination
of images using the logical .AND. and .OR. operators, along with thresholds of 1.52±0.03 km/s for sound speed and
0.16±0.04 dB/cm for attenuation, allowed for mass detection and characterization similar to MR.
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.
Breast ultrasound tomography is a rapidly developing imaging modality that has the potential to impact breast
cancer screening and diagnosis. Double difference (DD) tomography utilizes more accurate differential time-of-flight
(ToF) data to reconstruct the sound speed structure of the breast. It can produce more precise and better
resolution sound speed images than standard tomography that uses absolute ToF data. We apply DD tomography to
phantom data and excised mouse mammary glands data. DD tomograms demonstrate sharper sound speed contrast
than the standard tomograms.
We report on the use of ultrasound tomography (UST) to characterize breast cancer and study the local and
distant tumor environments. We have imaged the tumor and its environment in 3 cases of breast cancer using
a UST prototype and its associated image reconstruction algorithms. After generating images of reflection,
sound speed and attenuation, the images were fused in combinations that allowed visualization and
characterization of the interior of the tumor as well as the tissue immediate to the tumor and beyond. The
reflection UST images demonstrated the presence of spiculation, and architectural distortion, indicators of
both local tumor invasion and distant involvement with surrounding tissues. Furthermore, the sound speed
images showed halos of elevated sound speed surrounding the tumors, indicating a local environment
characterized by stiff tissues. The combination of sound speed and attenuation images revealed that the
tumor interiors were the stiffest tissues in the region studied. These features and characteristics are
commensurate with the known biomechanical properties of cancer and may be manifestations of the
desmoplastic process that is associated with tumor invasion. We propose that UST imaging may prove to be a
valuable tool for characterizing cancers and studying the tumor invasion process.
Breast density descriptors were estimated from ultrasound tomography (UST) and digital mammogram (DM) images of
46 anthropomorphic software breast phantoms. Each phantom simulated a 450 ml or 700 ml breast with volumetric
percent density (PD) values between 10% and 50%. The UST based volumetric breast density (VBD) estimates were
calculated by thresholding the reconstructed UST images. Percent density (PD) values from DM images were estimated
interactively by a clinical breast radiologist using Cumulus software. Such obtained UST VBD and Cumulus PD
estimates were compared with the ground truth VBD values available from phantoms. The UST VBD values showed a
high correlation with the ground truth, as evidenced by the Pearson correlation coefficient of r=0.93. The Cumulus PD
values also showed a high correlation with the ground truth (r=0.84), as well as with the UST VBD values (r=0.78).
The consistency in measuring the UST VBD and Cumulus PD values was analyzed using the standard error of the
estimation by linear regression (σE). The σE value for Cumulus PD was 1.5 times higher compared to the UST VBD
(6.54 vs. 4.21). The σE calculated from two repeated Cumulus estimation sessions (σE=4.66) was comparable with the
UST. Potential sources of the observed errors in density measurement are the use of global thresholding and (for
Cumulus) the human observer variability. This preliminary study of simulated phantom UST images showed promise
for non-invasive estimation of breast density.
The purpose of this study was to investigate the performance of an ultrasound tomography (UST) prototype relative to
magnetic resonance (MR) for imaging overall breast anatomy and accentuating tumors relative to background tissue.
The study was HIPAA compliant, approved by the Institutional Review Board, and performed after obtaining the
requisite informed consent. Twenty-three patients were imaged with MR and the UST prototype. T1 weighted images
with fat saturation, with and without gadolinium enhancement, were used to examine anatomical structures and tumors,
while T2 weighted images were used to identify cysts. The UST scans generated sound speed, attenuation, and reflection
images. A qualitative visual comparison of the MRI and UST images was then used to identify anatomical similarities. A
more focused approach that involved a comparison of reported masses, lesion volumes, and breast density was used to
quantify the findings from the visual assessment. Our acoustic tomography prototype imaged distributions of fibrous
stroma, parenchyma, fatty tissues, and lesions in patterns similar to those seen in the MR images. The range of
thresholds required to establish tumor volume equivalency between MRI and UST suggested that a universal threshold for isolating masses relative to background tissue is feasible with UST. UST has demonstrated the ability to visualize and characterize breast tissues in a manner comparable to MRI. Thresholding techniques accentuate masses relative to background anatomy, which may prove clinically useful for early cancer detection.
The purpose of this study was to correlate changes in biomechanical properties of breast cancer lesions in response to
neoadjuvant chemotherapy. Nine patients were examined repeatedly throughout their treatment, using an experimental
prototype based on the principles of ultrasound tomography. The study was HIPAA compliant, approved by the
Institutional Review Board, and performed after obtaining the requisite informed consent. Images of reflection, sound
speed and attenuation, representing the entire volume of the breast, were reconstructed from the exam data and analyzed
for time-dependent changes during the treatment period. It was found that changes in tumor properties could be
measured in all cases. Furthermore, changes in sound speed were found to vary strongly from patient to patient. A
comparison of the sound speed response curves with pathological findings suggests that complete responders exhibit
distinctly different responses as measured by sound speed. These preliminary results were used to define a cut-point for
predicting response. Subsequently, a prospective prediction of the treatment response of a new patient was made
correctly. We hypothesize that changes in the biomechanical properties of breast cancers, as measured by sound speed,
can predict response. Future studies will focus on testing this hypothesis and defining and quantifying markers of response.
Our laboratory has focused on the development of ultrasound tomography (UST) for breast imaging. To that end we
have been developing and testing a clinical prototype in the Karmanos Cancer Institute's (KCI) breast center. The
development of our prototype has been guided by clinical feedback from data accumulated from over 300 patients
recruited over the last 4 years. Our techniques generate whole breast reflection images as well as images of the acoustic
parameters of sound speed and attenuation. The combination of these images reveals major breast anatomy, including
fat, parenchyma, fibrous stroma and masses. Fusion imaging, utilizing thresholding, is shown to visualize mass
characterization and facilitates separation of cancer from benign masses. These results indicate that operator-independent
whole-breast imaging and the detection and characterization of cancerous breast masses are feasible using acoustic
tomography techniques.
Analyses of the prototype images suggests that we can detect the variety of mass attributes noted by current ultrasound-BIRADS criteria, such as mass shape, acoustic mass properties and architecture of the tumor environment. These
attributes help quantify current BIRADS criteria (e.g. "shadowing" or high attenuation) and provide greater possibilities
for defining a unique signature of cancer. The potential for UST to detect and characterize breast masses was quantified
using UST measurements of 86 masses from the most recent cohort of patients imaged with the latest version of our prototype. Our preliminary results suggest that the development of a formal predictive model, in support of larger future trials, is warranted.
Since a 1976 study by Wolfe, high breast density has gained recognition as a factor strongly correlating with an
increased incidence of breast cancer. These observations have led to mammographic density being designated a "risk
factor" for breast cancer. Clinically, the exclusive reliance on mammography for breast density measurement has
forestalled the inclusion of breast density into statistical risk models. This exclusion has in large part been due to the
ionizing radiation associated with the method. Additionally, the use of mammography as valid tool for measuring a three
dimensional characteristic (breast density) has been criticized for its prima facie incongruity. These shortfalls have
prompted MRI studies of breast density as an alternative three-dimensional method of assessing breast density.
Although, MRI is safe and can be used to measure volumetric density, its cost has prohibited its use in screening. Here,
we report that sound speed measurements using a prototype ultrasound tomography device have potential for use as surrogates for breast density measurement. Accordingly, we report a strong positive linear correlation between volume-averaged sound speed of the breast and percent glandular tissue volume as assessed by MR.
Breast cancer is the most common type of cancer among women in Europe and North America. The established
screening method to detect breast cancer is X-ray mammography, although X-ray frequently provides poor contrast
for tumors located within glandular tissue. A new imaging approach is Ultrasound Tomography generating
three-dimensional speed of sound images. This paper describes a method to evaluate the clinical applicability of
three-dimensional speed of sound images by automatically registering the images with the corresponding X-ray
mammograms. The challenge is that X-ray mammograms show two-dimensional projections of a deformed breast
whereas speed of sound images render a three-dimensional undeformed breast in prone position. This conflict
requires estimating the relation between deformed and undeformed breast and applying the deformation to the
three-dimensional speed of sound image. The deformation is simulated based on a biomechanical model using
the finite element method. After simulation of the compression, the contours of the X-ray mammogram and
the projected speed of sound image overlap congruently. The quality of the matching process was evaluated
by measuring the overlap of a lesion marked in both modalities. Using four test datasets, the evaluation of
the registration resulted in an average tumor overlap of 97%. The developed registration provides a basis for
systematic evaluation of the new modality of three-dimensional speed of sound images, e.g. allows a greater
understanding of tumor depiction in these new images.
We report on a continuing assessment of the in-vivo performance of an operator independent breast imaging device
based on the principles of acoustic tomography. This study highlights the feasibility of mass characterization using
criteria derived from reflection, sound speed and attenuation imaging. The data were collected with a clinical prototype
at the Karmanos Cancer Institute in Detroit MI from patients recruited at our breast center. Tomographic sets of images
were constructed from the data and used to form 3-D image stacks corresponding to the volume of the breast. Masses
were identified independently by either ultrasound or biopsy and their locations determined from conventional
mammography and ultrasound exams. The nature of the mass and its location were used to assess the feasibility of our
prototype to detect and characterize masses in a case-following scenario.
Our techniques generated whole breast reflection images as well as images of the acoustic parameters of sound speed
and attenuation. The combination of these images reveals major breast anatomy, including fat, parenchyma, fibrous
stroma and masses. The three types of images are intrinsically co-registered because the reconstructions are performed
using a common data set acquired by the prototype. Fusion imaging, utilizing thresholding, is shown to visualize mass
characterization and facilitates separation of cancer from benign masses. These initial results indicate that operatorindependent
whole-breast imaging and the detection and a characterization of cancerous breast masses are feasible using
acoustic tomography techniques.
The objective of this study is to investigate a potential low-cost-alternative to MRI, based on acoustic tomography.
Using MRI as the gold standard, our goals are to assess the performance of acoustic tomography in (i) depicting normal
breast anatomy, (ii) imaging cancerous lesions and (iii) accentuating lesions relative to background tissue using
thresholding techniques. Fifteen patients were imaged with MRI and with an acoustic tomography prototype. A
qualitative visual comparison of the MRI and prototype images was used to verify anatomical similarities. These
similarities suggest that the prototype can image fibrous stroma, parenchyma and fatty tissues, with similar sensitivity to
MRI. The prototype was also shown to be able to image masses but equivalency in mass sensitivity with MRI could not
be established because of the small numbers of patients and the prototype's limited scanning range. The range of
thresholds required to establish tumor volume equivalency suggests that a universal threshold for isolating masses
relative to background tissue is possible with acoustic tomography. Thresholding techniques promise to accentuate
masses relative to background anatomy which may prove clinically useful in potential screening applications. Future
work will utilize larger trials to verify these preliminary conclusions.
As part of an ongoing assessment of the in-vivo performance of a operator independent breast imaging device, based on
acoustic tomography, we report on new results obtained with patients undergoing neoadjuvant chemotherapy. Five
patients were examined with the prototype on multiple occasions corresponding in time to their chemotherapy sessions.
Images of reflection, sound speed and attenuation, representing the entire volume of the breast, were reconstructed from
the exam data and analyzed for time-dependent changes during the treatment period. It was found that changes in
acoustic properties of the tumors could be measured directly from the images. The measured properties include
reflectivity, sound speed and attenuation, leading to measurable changes in the volume, shape and internal attributes of
the tumors. These measurements were used to monitor the response of the tumors to the therapy with the long term goal
of correlating results with pathological and clinical outcomes. Comparisons with tumor size changes based on traditional
US and MRI indicates potential for accurate, quantifiable tracking of tumor volume. Furthermore, our tentative results
also show declines in internal properties of the tumors, possibly relating to a reduction in tissue stiffness and/or density.
Future work will include an expansion of the study to a larger cohort of patients for determining the statistical
significance of our findings.
KEYWORDS: Breast, Ultrasonography, Ultrasound tomography, Tomography, Tissues, In vivo imaging, Inverse problems, Reconstruction algorithms, Cancer, Breast cancer
Breast ultrasound tomography is a rapidly developing imaging modality that that has the potential to impact breast
cancer screening and diagnosis. A new ultrasound breast imaging device (CURE) with a ring array of transducers has
been designed and built at Karmanos Cancer Institute, which acquires both reflection and transmission ultrasound
signals. To extract the sound-speed information from the breast data acquired by CURE, we have developed an iterative
sound-speed image reconstruction algorithm for breast ultrasound transmission tomography based on total-variation
(TV) minimization. We investigate applicability of the TV tomography algorithm using in vivo ultrasound breast data
from 61 patients, and compare the results with those obtained using the Tikhonov regularization method. We
demonstrate that, compared to the Tikhonov regularization scheme, the TV regularization method significantly improves
image quality, resulting in sound-speed tomography images with sharp (preserved) edges of abnormalities and few
artifacts.
We report and discuss clinical breast imaging results obtained with operator independent ultrasound tomography. A
series of breast exams are carried out using a recently upgraded clinical prototype designed and built on the principles of
ultrasound tomography. The in-vivo performance of the prototype is assessed by imaging patients at the Karmanos
Cancer Institute. Our techniques successfully demonstrate in-vivo tomographic imaging of breast architecture in both
reflection and transmission imaging modes. These initial results indicate that operator-independent whole-breast imaging
and the detection of cancerous breast masses are feasible using ultrasound tomography techniques. This approach has
the potential to provide a low cost, non-invasive, and non-ionizing means of evaluating breast masses. Future work will
concentrate on extending these results to larger trials.
Ultrasound attenuation parameters of breast masses are closely related to their types and pathological states, therefore, it
is essential to reliably estimate attenuation parameters for quantitative breast tissue characterization. We study the
applicability of three different attenuation tomography methods for ultrasound breast imaging using a ring transducer
array. The first method uses the amplitude decays of signals transmitted through the breast to reconstruct attenuation
coefficients. The second method employs the spectral ratios between the pulse propagating through the breast and that
through water to obtain attenuation parameters. The third method makes use of the complex energy ratios estimated
using the amplitude envelopes of transmitted signals. We use in vitro and in vivo breast data acquired with a clinical
ultrasound breast imaging system (CURE) to compare these tomography methods. Our results show that the amplitude
decay method yields attenuation coefficients with more artifacts than the other two methods. There is bias and
variability in the estimated attenuation using the spectral ratio due to its sensitivity to different temporal band-widths and
signal-to-noise-ratios of the data. The method based on the complex signal energy ratio is more robust than the other
two methods and yields images with fewer artifacts.
A novel clinical prototype, CURE (Computed Ultrasound Risk Evaluation), is used to collect breast tissue image data of
patients with either benign or malignant masses. Three types of images, reflection, sound speed and attenuation, are
generated from the raw data using tomographic reconstruction algorithms. Each type of image, usually presented as a
gray scale image, maps different characteristics of the breast tissue. This study is focused on fusing all three types of
images to create true color (RGB) images by assigning a different primary color to each type of image. The resulting
fused images display multiple tissue characteristics that can be viewed simultaneously. Preliminary results indicate that
it may be possible to characterize breast masses on the basis of viewing the superimposed information. Such a
methodology has the potential to dramatically reduce the time required to view all the acquired data and to make a
clinical assessment. Since the color scale can be quantified, it may also be possible to segment such images in order to
isolate the regions of interest and to ultimately allow automated methods for mass detection and characterization.
Ultrasound reflection imaging is a promising imaging modality for detecting small, early-stage breast cancers. Properly
accounting for ultrasound scattering from heterogeneities within the breast is essential for high-resolution and high-quality
ultrasound breast imaging. We develop a globally optimized Fourier finite-difference method for ultrasound reflectivity
image reconstruction. It utilizes an optimized solution of acoustic-wave equation and a heterogeneous sound-speed distribution
of the breast obtained from tomography to reconstruct ultrasound reflectivity images. The method contains a
finite-difference term in addition to the split-step Fourier implementation, and minimizes ultrasound phase errors during
wavefield inward continuation while maintaining the advantage of high computational efficiency. The accuracy analysis indicates
that the optimized method is much more accurate than the split-step Fourier method. The computational efficiency
of the optimized method is one to two orders of magnitude faster than time-reversal imaging using a finite-difference
time-domain wave-equation scheme. Our new optimized method can accurately handle ultrasound scattering from breast
heterogeneities during reflectivity image reconstruction. Our numerical imaging examples demonstrate that the optimized
method has the potential to produce high-quality and high-resolution ultrasound reflectivity images in combination with a
reliable ultrasound sound-speed tomography method.
To improve clinical breast imaging, a new ultrasound tomography imaging device (CURE) has been built at the
Karmanos Cancer Institute. The ring array of the CURE device records ultrasound transmitted and reflected ultrasound
signals simultaneously. We develop a bent-ray tomography algorithm for reconstructing the sound-speed distribution of
the breast using time-of-flights of transmitted signals. We study the capability of the algorithm using a breast phantom
dataset and over 190 patients' data. Examples are presented to demonstrate the sound-speed reconstructions for different
breast types from fatty to dense on the BI-RADS categories 1-4. Our reconstructions show that the mean sound-speed
value increases from fatty to dense breasts: 1440.8 m/ s (fatty), 1451.9 m/ s (scattered), 1473.2 m/ s(heterogeneous), and 1505.25 m/ s (dense). This is an important clinical implication of our reconstruction. The mean
sound speed can be used for breast density analysis. In addition, the sound-speed reconstruction, in combination with
attenuation and reflectivity images, has the potential to improve breast-cancer diagnostic imaging. The breast is not
compressed and does not move during the ultrasound scan using the CURE device, stacking 2D slices of ultrasound
sound-speed tomography images forms a 3D volumetric view of the whole breast. The 3D image can also be projected
into a 2-D "ultrasound mammogram" to visually mimic X-ray mammogram without breast compression and ionizing
radiation.
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