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Hyperthermia-enhanced chemo- and radiation therapies have been used in the treatment of various types of cancers such as breast, and soft-tissue sarcoma. Localized hyperthermia can increase the effectiveness of treatment and reduce the dosage requirements. Simultaneous temperature monitoring has generally required the use of additional modalities such as magnetic resonance imaging (MRI). Ultrasound (US) offers the potential for an all-in-one solution for heat induction and temperature monitoring through speed of sound (SOS) measurements. Such a system would ease the utility of hyperthermia-enhanced therapies and minimize the required hardware/costs, thereby presenting an attractive alternative. In this study, we present the results for 1) all-acoustic, in-silico, localized heating of a numerical breast phantom with embedded tumor, and 2) ex-vivo thermometry results, which look at monitoring the changes in water sound speed at 25, 35, and 45 °C in a heterogeneous lamb tissue phantom. The measurements from the thermometry experiment were then compared against the known values from the literature. The results from this study show successful all-acoustic induced localized heating and good agreement between the measured water sound speed values and their literature counterparts, which represent a significant step toward the development of a real-time US hyperthermia system.

Objective To evaluate the combination of tumor volume and sound speed as a potential imaging marker for assessing neoadjuvant chemotherapy (NAC) response. Methods This study was carried out under an IRB-approved protocol (written consent required). Fourteen patients undergoing NAC for invasive breast cancer were examined with ultrasound tomography (UST) throughout their treatment. The volume (V) and the volume-averaged sound speed (VASS) of the tumors and their changes were measured for each patient. Time-dependent response curves of V and VASS were constructed individually for each patient and then as averages for the complete versus partial response groups in order to characterize differences between the two groups. Differences in group means were assessed for statistical significance using t-tests. Differences in shapes of group curves were evaluated with Kolmogorov–Smirnoff tests. Results On average, tumor volume and sound speed in the partial response group showed a gradual decline in the first 60 days of treatment, while the complete response group showed a much steeper decline (P < 0.05). The shapes of the response curves of the two groups, corresponding to the entire treatment period, were also found to be significantly different (P < 0.05). Furthermore, large simultaneous drops in volume and sound speed in the first 3 weeks of treatment were characteristic only of the complete responders (P < 0.05). Conclusion This study demonstrates the feasibility of using UST to monitor NAC response, warranting future studies to better define the potential of UST for noninvasive, rapid identification of partial versus complete responders in women undergoing NAC.

Objectives Ultrasound tomography (UST) is an emerging whole-breast 3-dimensional imaging technique that obtains quantitative tomograms of speed of sound of the entire breast. The imaged parameter is the speed of sound which is used as a surrogate measure of density at each voxel and holds promise as a method to evaluate breast density without ionizing radiation. This study evaluated the technique of UST and compared whole-breast volume averaged speed of sound (VASS) with MR percent water content from noncontrast magnetic resonance imaging (MRI). Materials and Methods Forty-three healthy female volunteers (median age, 40 years; range, 29-59 years) underwent bilateral breast UST and MRI using a 2-point Dixon technique. Reproducibility of VASS was evaluated using Bland-Altman analysis. Volume averaged speed of sound and MR percent water were evaluated and compared using Pearson correlation coefficient. Results The mean standard deviation VASS measurement was 1463 +/- 29 m s(-1) (range, 1434-1542 m s(-1)). There was high similarity between right (1464 +/- 30 m s(-1)) and left (1462 +/- 28 m s(-1)) breasts (P = 0.113) (intraclass correlation coefficient, 0.98). Mean MR percent water content was 35.7% +/- 14.7% (range, 13.2%-75.3%), with small but significant differences between right and left breasts (36.3% +/- 14.9% and 35.1% +/- 14.7%, respectively; P = 0.004). There was a very strong correlation between VASS and MR percent water density (r(2) = 0.96, P < 0.0001). Conclusions Ultrasound tomography holds promise as a reliable and reproducible 3-dimensional technique to provide a surrogate measure of breast density and correlates strongly with MR percent water content.

PURPOSE. Ultrasound tomography (UST) using SoftVue (Delphinus Medical Technologies, Inc.) has the unique ability to provide quantitative whole breast tissue stiffness, including localized measurements on masses. Conversely, handheld ultrasound (HHUS) only provides localized diagnostic information of tissue stiffness, or elasticity. Screening requires global assessment of tissue properties for which HHUS is not suitable, while automated breast ultrasound does not measure stiffness. This study is the first to evaluate imaging of tissue stiffness by SoftVue for common breast masses. METHOD AND MATERIALS. Patients with findings on mammography during the time period of January 2017 to November 2018, were scanned with SoftVue. Patients were selected on the basis of having dense breasts and having either benign or malignant breast masses. All women received standard breast imaging evaluation prior to biopsy. Pathology and/or radiology reports were used as the ground truth for verifying lesion type, which included 195 masses RESULTS. SoftVue demonstrated the ability to measure tissue stiffness throughout the breast and to characterize mass stiffness in all 195 patients. Table 1 lists the average stiffness index for each type of mass. Cysts, fibroadenomas and cancers were found to have mean stiffness indices of (0.10; 95% CI: 0.05 to 0.30), (0.35; 0.25 to 0.77) and (0.60; 0.41 to 1.00) respectively (p DISCUSSION. Masses were characterized using mean stiffness and mean homogeneity of stiffness. Both measures were able to separate the populations of the three types of masses, but the homogeneity texture parameter showed less overlap between benign and malignant masses. Further radiomics analyses of texture features will assure inclusion in a future CAD tool for improved diagnostic performance. During dense breast screening by SoftVue, whole breast tissue stiffness improves cancer conspicuity throughout a breast volume for initial detection during screening, while mass characterization on the basis of stiffness may improve screening specificity, which is not possible with current ultrasound. CONCLUSION. Measuring tissue stiffness throughout the whole breast is not currently available clinically. The study demonstrates that stiffness characterization of lesions derived from whole breast stiffness imaging with UST SoftVue is feasible for future screening of women with dense breasts. Using SoftVue stiffness has the potential to reduce call backs and biopsies, in combination with other parameters, to improve specificity. Table 1Type of MassStiffness index valueStandard deviation95% CIMean HomogeneityStandard Deviation95% CICyst0.100.200.05-0.300.830.050.73 - 0.91FB0.350.240.25-0.770.770.060.65 - 0.85Ca0.610.190.41-1.000.660.090.52 - 0.79 Citation Format: Neb Duric, Peter J Littrup, Cuiping Li, Rachel Brem. Whole breast tissue stiffness and mass characterization by ultrasound tomography [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P1-02-08.

PURPOSE. Recent analyses of tumor location by breast magnetic resonance (MR) imaging have shown that breast cancers were significantly more likely to be located, at or near the fat-gland interface (FGI). However, these analyses did not include benign masses or coronal evaluations. Ultrasound tomography (UST) is a novel multi-sequence tomographic form of sonography with anatomic and physiologic information that can improve the sensitivity of breast cancer detection, particularly in women with dense breasts. The purpose of this study was to use the native coronal imaging plane of UST SoftVue (Delphinus Medical Technologies, Inc.) to map the locations of cancers, fibroadenomas and cysts, relative to the FGI, in order to facilitate the detection and characterization of breast masses in future UST screening. METHODS AND MATERIALS. Mass location in coronal UST images was determined by a MQSA certified radiologist with extensive UST imaging experience. The relationship of the lesion to the FGI was noted for a total of 427 breast masses (117 cancers, 135 fibroadenomas, 135 cysts and 40 other benign findings), confirmed by biopsy or by hand-held ultrasound for masses that fulfilled all criteria for a simple cyst. The FGI was defined as the circumferential interface between the peripheral fat and parenchyma as determined by examining sound speed (SS) images, which reliably differentiate the much lower SS of fat compared to that of dense tissue. Mass location was placed into three groups: (i) completely surrounded by dense fibroglandular tissue, (ii) completely surrounded by fat or (iii) partially surrounded by both (i.e., the FGI). Lesion locations relative to FGI were compared using the chi-squared test. RESULTS. Cancers were located at the FGI in 93.2% (109/117) of the cases and were surrounded by fat in 6.0% (7/117) or parenchyma in 0.9% (1/117) (p DISCUSSION. Coronal imaging by UST provides reliable circumferential evaluation of the FGI, which can be augmented by axial/sagittal reconstructions as needed for additional confirmation of anterior/posterior aspects of the FGI. Our results confirm the previously reported MRI findings that cancers have a very strong tendency to be located at the FGI and extend these findings by demonstrating that benign masses have a weaker tendency in that regard. With the introduction of UST, our finding that breast cancers occur more frequently at the fat-gland interface may facilitate the conspicuity, rapid search and localization of cancers during screening of women with dense breasts. Perhaps equally important for future specificity of screening women with dense breasts, fibroglandular tissue surrounded only 0.9% of cancers and was much more commonly associated with benign masses. CONCLUSIONS. The native coronal imaging plane by SoftVue UST facilitated detection and localization of cancers, which were much more likely to be found at the FGI (p Table 1Type of massAt FGIIn Dense tissueIn FatCancer109 (93%)1 (1%)7 (6%)Fibroadenoma85 (63%)42 (31%)8 (6%)Cyst39 (29%)93 (69%)3 (2%) Citation Format: Peter Littrup, Mark Sak, Neb Duric, Rachel Brem. Breast cancer development at the fat-gland interface (FGI): Importance of coronal imaging and ultrasound tomography [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P1-02-05.

Mammographic percent density (MPD) is an independent risk factor for developing breast cancer, but its inclusion in clinical risk models provides only modest improvements in individualized risk prediction, and MPD is not typically assessed in younger women because of ionizing radiation concerns. Previous studies have shown that tissue sound speed, derived from whole breast ultrasound tomography (UST), a non-ionizing modality, is a potential surrogate marker of breast density, but prior to this study, sound speed has not been directly linked to breast cancer risk. To that end, we explored the relation of sound speed and MPD with breast cancer risk in a case-control study, including 61 cases with recent breast cancer diagnoses and a comparison group of 165 women, frequency matched to cases on age, race, and menopausal status, and with a recent negative mammogram and no personal history of breast cancer. Multivariable odds ratios (ORs) and 95% confidence intervals (CIs) were estimated for the relation of quartiles of MPD and sound speed with breast cancer risk adjusted for matching factors. Elevated MPD was associated with increased breast cancer risk, although the trend did not reach statistical significance (OR per quartile = 1.27, 95% CI: 0.95, 1.70; ptrend = 0.10). In contrast, elevated sound speed was significantly associated with breast cancer risk in a dose−response fashion (OR per quartile = 1.83, 95% CI: 1.32, 2.54; ptrend = 0.0003). The OR trend for sound speed was statistically significantly different from that observed for MPD (p = 0.005). These findings suggest that whole breast sound speed may be more strongly associated with breast cancer risk than MPD and offer future opportunities for refining the magnitude and precision of risk associations in larger, population-based studies, including women younger than usual screening ages.

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.

Application of the frequency domain acoustic wave equation on data acquired from ultrasound tomography scans is shown to yield high resolution sound speed images on the order of the wavelength of the highest reconstructed frequency. Using a signal bandwidth of 0.4-1 MHz and an average sound speed of 1500 m s(-1), the resolution is approximately 1.5 mm. The quantitative sound speed values and morphology provided by these images have the potential to inform diagnosis and classification of breast disease. In this study, we present the formalism, practical application, and in vivo results of waveform tomography applied to breast data gathered by two different ultrasound tomography scanners that utilize ring transducers. The formalism includes a review of frequency domain modeling of the wave equation using finite difference operators as well as a review of the gradient descent method for the iterative reconstruction scheme. It is shown that the practical application of waveform tomography requires an accurate starting model, careful data processing, and a method to gradually incorporate higher frequency information into the sound speed reconstruction. Following these steps resulted in high resolution quantitative sound speed images of the breast. These images show marked improvement relative to commonly used ray tomography reconstruction methods. The robustness of the method is demonstrated by obtaining similar results from two different ultrasound tomography devices. We also compare our method to MRI to demonstrate concordant findings. The clinical data used in this work was obtained from a HIPAA compliant clinical study (IRB 040912M1F).

Ultrasound tomography (UST) is an emerging breast imaging modality that can be used to quantitatively measure breast density. However, the sound speed images that are used in this analysis must first be segmented in order to accurately parse any quantitative information. Previously, this segmentation has been done manually, but this is time consuming, especially when dealing with a large number of images that must be masked. An automated masking algorithm has been developed that applies thresholding and morphological operators to UST attenuation images to automatically create masks that separate the breast tissue from the water bath. An initial set of images was tested using this algorithm to fine tune settings and very good agreement was achieved. However, when the optimized settings were applied to a larger dataset of 286 images, the robustness of the algorithm was tested. The manual masks measured a larger volume (921 cm3) than the automated masks (713 cm3), but fortunately, the difference in mean sound speed was much smaller (1449 m/s versus 1448 m/s). A majority of the automated masks (72.7%) had a measured Dice similarity coefficient (DSC) of greater than 0.8 which indicates that there was good to great overlap in the volumes of tissue created by the automated method. This algorithm shows promise to be used as a tool to quickly and effectively measure breast density.

Ultrasound tomography (UST) image segmentation is fundamental in breast density estimation, medicine response analysis, and anatomical change quantification. Existing methods are time consuming and require massive manual interaction. To address these issues, an automatic algorithm based on GrabCut (AUGC) is proposed in this paper. The presented method designs automated GrabCut initialization for incomplete labeling and is sped up with multicore parallel programming. To verify performance, AUGC is applied to segment thirty-two in vivo UST volumetric images. The performance of AUGC is validated with breast overlapping metrics (Dice coefficient (D), Jaccard (J), and False positive (FP)) and time cost (TC). Furthermore, AUGC is compared to other methods, including Confidence Connected Region Growing (CCRG), watershed, and Active Contour based Curve Delineation (ACCD). Experimental results indicate that AUGC achieves the highest accuracy (D=0.9275 and J=0.8660 and FP=0.0077) and takes on average about 4 seconds to process a volumetric image. It was said that AUGC benefits large-scale studies by using UST images for breast cancer screening and pathological quantification.

Women with high breast density are at increased risk of developing breast cancer. Breast density has usually been defined using mammography as the ratio of fibroglandular tissue to total breast area. Ultrasound tomography (UST) is an emerging modality that can also be used to measure breast density. UST creates tomographic sound speed images of the patient’s breast which is useful as sound speed is directly proportional to tissue density. Furthermore, the volumetric and quantitative information contained in the sound speed images can be used to describe the distribution of breast density. The work presented here measures the UST sound speed density distributions of 165 women with negative screening mammography. Frequency distributions of the sound speed voxel information were examined for each patient. In a preliminary analysis, the UST sound speed distributions were averaged across patients and grouped by various patient and density-related factors (e.g., age, body mass index, menopausal status, average mammographic breast density). It was found that differences in the distribution of density could be easily visualized for different patient groupings. Furthermore, findings suggest that the shape of the distributions may be used to identify participants with varying amounts of dense and non-dense tissue.

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.

Previous ultrasound tomography work conducted by our group showed a direct correlation between measured sound speed and physical density in vitro, and increased in vivo sound speed with increasing mammographic density, a known risk factor for breast cancer. Building on these empirical results, the purpose of this work was to explore a metric to quantify breast density using our ultrasound tomography sound speed images in a manner analogous to computer-assisted mammogram segmentation for breast density analysis. Therefore, volumetric ultrasound percent density (USPD) is determined by segmenting high sound speed areas from each tomogram using a k-means clustering routine, integrating these results over the entire volume of the breast, and dividing by whole-breast volume. First, a breast phantom comprised of fat inclusions embedded in fibroglandular tissue was scanned four times with both our ultrasound tomography clinical prototype (with 4 mm spatial resolution) and CT. The coronal transmission tomograms and CT images were analyzed using semiautomatic segmentation routines, and the integrated areas of the phantom's fat inclusions were compared between the four repeated scans. The average variability for inclusion segmentation was approximately 7% and approximately2%, respectively, and a close correlation was observed in the integrated areas between the two modalities. Next, a cohort of 93 patients was imaged, yielding volumetric coverage of the breast (45-75 sound speed tomograms/patient). The association of USPD with mammographic percent density (MPD) was evaluated using two measures: (1) qualitative, as determined by a radiologist's visual assessment using BI-RADS Criteria and (2) quantitative, via digitization and semiautomatic segmentation of craniocaudal and mediolateral oblique mammograms. A strong positive association between BI-RADS category and USPD was demonstrated [Spearman rho = 0.69 (p < 0.001)], with significant differences between all BI-RADS categories as assessed by one-way ANOVA and Scheffe posthoc analysis. Furthermore, comparing USPD to calculated mammographic density yielded moderate to strong positive associations for CC and MLO views (r2 = 0.75 and 0.59, respectively). These results support the hypothesis that utilizing USPD as an analogue to mammographic breast density is feasible, providing a nonionizing, whole-breast analysis.

Women with elevated mammographic percent density, defined as the ratio of fibroglandular tissue area to total breast area on a mammogram are at an increased risk of de veloping breast cancer. Ultrasound tomography (UST) is an imaging modality that can create tomographic sound speed images of a patient’s breast, which can then be used to measure breast density. These sound speed images are useful because physical tissue density is directly proportional to sound speed. The work presented here updates previous results that compared mammographic breast density measurements with UST breast density measurements within an ongoing study. The current analysis has been expanded to include 158 women with negative digital mammographic screens who then underwent a breast UST scan. Breast density was measured for both imaging modalities and preliminary analysis demonstrated strong and positive correlations (Spearman correlation coefficient r s = 0.703). Additional mammographic and UST related imaging characteristics were also analyzed and used to compare the behavior of both imaging modalities. Results suggest that UST can be used among women with negative mammographic screens as a quantitative marker of breast density that may avert shortcomings of mammography. Keywords: Ultrasound tomography. Breast density. Breast cancer risk. Mammography. Sound speed. 1.

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.

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.

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 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.

Ultrasound tomography is a modality that can be used to image various characteristics of the breast, such assound speed, attenuation, and reectivity. In the considered setup, the breast is immersed in water and scannedalong the coronal axis from the chest wall to the nipple region. To improve image visualization, it is desirableto remove the water background. To this end, the 3D boundary of the breast must be accurately estimated. Wepresent an iterative algorithm based on active contours that automatically detects the boundary of a breast usinga 3D stack of attenuation images obtained from an ultrasound tomography scanner. We build upon an existingmethod to design an algorithm that is fast, fully automated, and reliable. We demonstrate the e ectiveness ofthe proposed technique using clinical data sets.Keywords: Active contours, breast boundary detection, image segmentation, ultrasound tomography 1. INTRODUCTION Ultrasound tomography (UST) is a technique that uses computed tomography methods to solve an inverseproblem involving ultrasound signals. In the scenario of interest, the breast to be imaged is immersed in a watertank, and is surrounded by an ultrasound transducer ring that moves from the chest wall to the nipple regionusing a motorized gantry. Each transducer element emits, in turn, an ultrasound pulse that propagates throughthe medium and gets recorded by all the elements of the ring aperture. Acoustic properties of the medium areinferred from the recorded ultrasound data using image reconstruction algorithms. A number of investigatorshave developed scanners based on UST principles. Examples include the work by Marmarelis et al.

Ultrasound tomography (UST) employs sound waves to produce three-dimensional images of breast tissue and precisely measures the sound speed of breast tissue composition. High breast density is a strong breast cancer risk factor and sound speed is directly proportional to breast density. UST provides a quantitative measure of breast density based on three-dimensional imaging without compression, thereby overcoming the shortcomings of many other imaging modalities. The quantitative nature of the UST breast density measures are tied to an external standard, so sound speed measurement in breast tissue should be independent of specific hardware. The work presented here compares breast sound speed measurement obtained with two different UST devices. The Computerized Ultrasound Risk Evaluation (CURE) system located at the Karmanos Cancer Institute in Detroit, Michigan was recently replaced with the SoftVue ultrasound tomographic device. Ongoing clinical trials have used images generated from both sets of hardware, so maintaining consistency in sound speed measurements is important. During an overlap period when both systems were in the same exam room, a total of 12 patients had one or both of their breasts imaged on both systems on the same day. There were 22 sound speed scans analyzed from each system and the average breast sound speeds were compared. Images were either reconstructed using saved raw data (for both CURE and SoftVue) or were created during the image acquisition (saved in DICOM format for SoftVue scans only). The sound speed measurements from each system were strongly and positively correlated with each other. The average difference in sound speed between the two sets of data was on the order of 1-2 m/s and this result was not statistically significant. The only sets of images that showed a statistical difference were the DICOM images created during the SoftVue scan compared to the SoftVue images reconstructed from the raw data. However, the discrepancy between the sound speed values could be easily handled by uniformly increasing the DICOM sound speed by approximately 0.5 m/s. These results suggest that there is no fundamental difference in sound speed measurement for the two systems and support combining data generated with these instruments in future studies.

The purpose of this paper is to describe the technical and clinical performance of SoftVue, a breast imaging device based on the principles of ultrasound tomography. We report on initial results from data acquired from 30 participants in a recently undertaken clinical study. Initial results suggest that SoftVue can accurately image the full range of breast anatomy, including both benign lesions and cancer. Ongoing research is focused on assessing SoftVue's ability to differentiate benign masses from cancer.

Ultrasound tomography (UST) is a breast imaging modality that is radiation free, operator independent, and does not involve breast compression. In the UST system under consideration, the breast is surrounded by a transducer ring that moves along the coronal axis from the chest wall to the nipple region. The deployment of UST in a clinical setting is technically challenging from three major standpoints: acquisition speed, storage capability, and computational requirements. Data acquisition must be fast to maximize patient throughput and minimize image registration artifacts. Unlike traditional ultrasound, hundreds of gigabytes of data must be acquired, buffered, and processed to image various characteristics of breast tissues such as sound speed, attenuation, and reflectivity. The tomographic image reconstruction methods are non-linear, iterative algorithms with significant computational complexity. Moreover, the scanner hosting the acquisition and reconstruction components must satisfy stringent cost, power, and size requirements. For decades, the above constraints have hindered the practicality of UST in a clinical scenario. We describe the design of a UST system that addresses the relevant clinical requirements as a means to demonstrate the feasability of UST deployment in a clinical setting.

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 UST-measured 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.

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.

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.

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.

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. T 1 weighted images with fat saturation, with and without gadolinium enhancement, were used to examine anatomical structures and tumors, while T 2 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.

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.

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.

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.

We propose a new method for imaging sound speed in breast tissue from measurements obtained by ultrasound tomography (UST) scan- ners. Given the measurements, our algorithm finds a sparse image representation in an overcomplete dictionary that is adapted to the properties of UST images. This dictionary is learned from high reso- lution MRI breast scans using an unsupervised maximum likelihood dictionary learning method. The proposed dictionary-based regular- ization method significantly improves the quality of reconstructed breast UST images. It outperforms the wavelet-based reconstruction and the least squares minimization with lowpass constraints, on both numerical and in vivo data. Our results demonstrate that the use of the learned dictionary improves the image accuracy for up to 4 dB with the exact measurement matrix and for 3.5 dB with the estimated measurement matrix over the wavelet-based reconstruction under the same conditions.

Ultrasound is commonly used as an adjunct to mammography for diagnostic evaluation of suspicions arising from breast cancer screening. As an alternative to conventional sonography that uses hand-held transducers, toroidal array probes that encircle the breast immersed in a water bath have been investigated for ultrasound tomography. In this paper, two sets of experiments performed with a prototype ultrasound scanner on a phantom and a human breast in vivo are used to investigate the effects of diffraction and coherence in ultrasound tomography. Reconstructions obtained with transmission diffraction tomography (TDT) are compared with conventional reflection imaging and computerized ultrasound tomography showing a substantial improvement. The in vivo tests demonstrate that TDT can image the complex boundary of a cancer mass and suggest that it can reveal the anatomy of milk ducts and Cooper's ligaments.

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.

Breast ultrasound tomography is a rapidly developing imaging modality 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.

Multiple tissue parameters are useful for early breast cancer detection and diagnosis. Ultrasound tomography is a new, important imaging modality for our computerized ultrasound risk evaluation (CURE) prototype, which employs a ring transducer array to scan the whole breast in a water tank. We use our bent-ray time-of-light ultrasound tomography to reconstruct sound speeds of breasts with different densities. In addition, we develop an ultrasound attenuation reconstruction method based on complex- signal energy ratios. We apply our reconstruction techniques to in vitro and in vivo breast data acquired using the CURE device. Our reconstruction results demonstrate that CURE has great potential to reliably measure multiple mass characteristics by combining sound-speed, attenuation and reflection images.

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 de vice 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. Keywords: Breast imaging, sound-speed reconstruction, ultrasound tomography.

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.

Women with high mammographic breast density are at 4- to 6-fold increased risk of developing breast cancer compared to women with fatty breasts. However, current breast density estimations rely on mammography, which cannot provide accurate volumetric breast representation. Therefore, we explored two techniques of breast density evaluation via ultrasound tomography. A sample of 93 patients was imaged with our clinical prototype; each dataset contained 45-75 tomograms ranging from near the chest wall through the nipple. Whole breast acoustic velocity was determined by creating image stacks and evaluating the sound speed frequency distribution. Ultrasound percent density (USPD) was determined by segmenting high sound speed areas from each tomogram using k-means clustering, integrating over the entire breast, and dividing by total breast area. Both techniques were independently evaluated using two mammographic density measures: (1) qualitative, determined by a radiologist's visual assessment using BI-RADS Categories, and (2) quantitative, via semi-automatic segmentation to calculate mammographic percent density (MPD) for craniocaudal and medio-lateral oblique mammograms. ~140 m/s difference in acoustic velocity was observed between fatty and dense BI-RADS Categories. Increased sound speed was found with increased BI-RADS Category and quantitative MPD. Furthermore, strong positive associations between USPD, BI-RADS Category, and calculated MPD were observed. These results confirm that utilizing sound speed, both for whole-breast evaluation and segmenting locally, can be implemented to evaluate breast density.

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.

This session focuses on recent developments in breast ultrasound imaging, covering clinical practice as well as clinical and pre-clinical research. Current status of ultrasound screening will be reviewed, followed by discussions of emerging technologies at various stages of regulatory and technical development. The session strives to provide the attendee with a view of a continuum of imaging advances starting with the present and spanning the near and long term future. Learning Objectives: 1. Understand current state of ultrasound screening for breast cancer 2. Learn about current availability of whole breast ultrasound 3. Appreciate the current barriers to stronger adoption of screening ultrasound 4. Learn about attempts to drive adoption of screening ultrasound (e.g. breast density laws) 5. Learn about ultrasound tomography as an emerging technique for breast imaging 6. Learn about the regulatory status of emerging techniques such as ultrasound tomography 7. Learn about the developmental status of combined 3-D ultrasound and Mammography systems 8. Learn about photo-acoustic imaging and its potential future role in breast imaging

We describe the technical design and performance of SoftVue, a breast imaging device based on the principles of ultrasound tomography. SoftVue's imaging sensor is a ring shaped transducer operating at 3 MHz and consisting of 2048 elements. Data acquisition is achieved through 512 receive channels. The transducer encircles the breast, which is immersed in warm water while the patient lies in a prone position. The transducer is translated vertically to acquire data from the entire breast. The acquired data are used to reconstruct images using tomographic inversions. The reconstruction engine is based around a blade-server design that houses multiple CPUs and GPUs. Separate algorithms are used to reconstruct reflection, sound speed, and attenuation images. A patient scan generates a stack of each type of image. The system was designed with the clinical goal of detecting and characterizing breast masses based on their biomechanical and morphological properties. Ongoing clinical studies are being used to assess the performance of the system under realistic clinical settings. Results of the clinical assessment are presented. [The authors acknowledge research support from the National Cancer Institute (5 R44 CA165320-03). Neb Duric and Peter Littrup also acknowledge that they have financial interests in the SoftVue technology.]

Purpose: To investigate the use of the whole-breast sound speed measurement as a marker of breast density (BD), a known risk factor for breast cancer. Methods: As part of an ongoing study of breast cancer detection, 249 patients were scanned with a clinical prototype that operates on the principles of ultrasound tomography. Typically, 40–100 sound speed tomograms were reconstructed from the scan data, corresponding to the entire volume of the breast of each patient. The data were used to estimate the volume averaged sound speed (VASS) of the breast for each patient. The corresponding mammograms were used to calculate mammographic percent density (MPD) using CUMULUS software. Film mammograms were available for 164 patients while 85 digital mammograms were available for the remaining patients. Standard statistical techniques were used to determine associations of breast sound speed with a variety of mammographic measures such as percent density, area of dense tissue, and area of nondense tissue. Furthermore, associations of breast sound speed with continuous variables such as age and weight and dichotomous variables such as parity and menopausal status were also assessed. Results: VASS was found to be significantly associated with MPD. The Spearman correlation coefficient (rs) between VASS and MPD was found to be 0.77 and 0.71 for film and digital mammography, respectively. VASS was positively correlated with dense areas by mammography, both digital (rs = 0.46) and film (rs = 0.56). VASS was negatively associated with nondense area by mammography, both digital (rs = −0.58) and film (rs = −0.63). BD by all methods was less in postmenopausal than in premenopausal women. The MPD was lower in the postmenopausal group (by 6.6%, p < 0.08, for the digital group and 7.73%, p < 0.007, for the film group). The VASS was also lower in the postmenopausal group (by 15 m/s, p < 0.001 for the digital group and 8 m/s, p < 0.08, for the film group). The association of MPD with age was characterized with rs = −0.06 (p < 0.6) for digital mammography and rs = −0.53 (p < 0.002) for film mammography. For weight, the MPD associations were characterized by rs = −0.53 (p < 0.0001) for digital mammography and −0.38 (p < 0.0001) for film mammography. The association of VASS with age was rs = −0.33 (p < 0.002) for the digital group and −0.17 (p < 0.03) for the film group. For weight, the relationship was characterized with rs = −0.45 (p < 0.001) for the digital group and −0.37 (p < 0.0001) for the film group. Conclusions: The association between VASS and MPD is strong for both film and digital mammography, suggesting that VASS is a viable measure of breast density. This result sets the stage for future work that will focus on directly testing the association of VASS with breast cancer risk.

Purpose: Previous ultrasoundtomography work conducted by our group showed a direct correlation between measuredsound speed and physical density in vitro, and increased in vivosound speed with increasing mammographic density, a known risk factor for breast cancer. Building on these empirical results, we investigated the use of volumetric ultrasound percent density (USPD) for breast density estimation. Method and Materials: A breast phantom comprised of fat inclusions embedded in fibroglandular tissue was scanned four times with both ultrasoundtomography and CT. The coronal transmission tomograms and corresponding CTimages were analyzed using a semi‐automatic segmentation routine. Next, a cohort of ∼100 patients was imaged encompassing the entire breast volume (50–75 tomograms/patient). USPD was determined by segmenting high sound speed areas from each slice using a k‐means clustering routine, integrating these results over the entire breast, and dividing by total breast area. USPD was evaluated using two mammographic density measures: (1) qualitative, as determined by a radiologist's visual assessment using BI‐RADS Criteria and (2) quantitative, via digitization and semi‐automatic segmentation of craniocaudal and medio‐lateral oblique mammograms.Results: The integrated areas of the phantom's fat inclusions were compared using both transmission ultrasound and CT for four repeated scans. The average variability for inclusion segmentation was ∼2% and ∼10%, respectively, and a close correlation was observed in the integrated areas between the two modalities. A strong positive association between BI‐RADS category and USPD was demonstrated. Furthermore, comparing USPD to calculated mammographic density yielded moderate to strong positive associations (Pearson r = 0.76–0.84) for MLO and CC views, respectively. Conclusion: These results support the hypothesis that utilizing USPD as an analogue to mammographic breast density is feasible. USPD has the potential to provide a non‐ionizing, whole‐breast analysis of breast density, which may better elucidate the relationship between breast density and breast cancer risk.

Purpose: Women with high mammographic breast density are at a 4‐ to 6‐fold increased risk of developing breast cancer compared to women with fatty breasts. The purpose of this investigation was to confirm preliminary acoustic velocity measurements for breast density assessment, and to evaluate them with the current standard of care. Method and Materials: A sample of ∼100 patients was imaged with our computed ultrasound tomography clinical prototype with each dataset comprised of 45–75 tomograms ranging from near the chest wall through the nipple region. Whole breast acoustic velocity was determined by creating image stacks and evaluating the sound speed frequency distribution. The acoustic measures of breast density were evaluated by comparing these results to two mammographic density measures: (1) qualitative, as determined by a certified radiologist using the BI‐RADS Categorical Assessment based on a 1 (fatty) to 4 (dense) scale, and (2) quantitative, via digitization and computerized analysis of archival mammograms. The former involved a radiologist's visual assessment of each mammogram, while the latter required digitizing cranio‐caudal (CC) and mediolateral oblique (MLO) mammograms and implementing semi‐automatic segmentation routines. Results: Approximately 140 m/s difference in acoustic velocity was found between the fatty and dense BI‐RADS Categories, with statistically significant differences in mean sound speed demonstrated between each category (ANOVA, α= 0.05). In addition, an increased sound speed was exhibited with increased BI‐RADS Category. Furthermore, moderately strong positive associations were demonstrated between mean acoustic velocity and quantitative measures of mammographic percent breast density for both MLO and CC views (r2 = 0.65–0.76), respectively. Conclusion: These results confirm the hypothesis that utilizing acoustical velocity can be used as an indicator of breast tissue density. Having an operator independent and non‐ionizing means of whole‐breast density evaluation has important clinical implications which include tracking temporal changes, identifying high‐risk populations, and evaluating treatment response.

Purpose: To improve resolution and reduce speckle in ultrasound breast images by accounting for ultrasound scattering from breast heterogeneities during reflectivityimage reconstruction.Method and Materials: X‐ray mammography often fails to detect cancers in dense breasts, while breast ultrasound has the potential to detect them. Breast heterogeneities, particularly in dense breasts, generate significant ultrasound scattering. Properly handling ultrasound scattering is critical for reliable cancer detection and diagnosis in dense breasts. Ultrasoundwave propagation in the breast is governed by the acoustic‐wave equation in heterogeneous media, which can be decomposed into two one‐way wave equations describing wave propagation in opposite directions. A split‐step Fourier solution of a one‐way wave equation is used for backpropagation of reflected ultrasoundwaves. The backpropagation consists of two steps: one phase‐shift step in the frequency‐wavenumber domain, and another phaseshift step in the frequency‐space domain. During the backpropagation of ultrasound wavefields, heterogeneous breast sound‐speed models obtained from transmission ultrasound tomography are used to approximately account for ultrasoundwavescattering. The reflectivityimaging method based on the split‐step Fourier propagator is applied to computer‐generated ultrasound data and in‐vivo ultrasound breast data acquired using a ring transducer array. The ultrasoundimages are compared with those obtained using a uniform sound‐speed model.Results: Comparison of ultrasoundreflectivityimages obtained using heterogeneous breast sound‐speed models with those obtained with a uniform model shows that ultrasound scattering of breast heterogeneities needs to be taken into account to obtain high‐resolution and high‐quality breast images.Conclusion: Using heterogeneous sound‐speed models for ultrasoundwave backpropagation during reflectivityimage reconstruction significantly improves image resolution and reduces speckle. The resolution and quality of ultrasoundreflectivityimages are further enhanced with increasing accuracy and resolution of transmission ultrasound tomography.