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PURPOSE. Studies have shown that a decrease in mammographic density (MD) or lowering of background parenchymal enhancement (BPE) on MRI after initiation of tamoxifen therapy predicts a favorable response in the preventive or adjuvant settings. However, performing serial mammograms poses radiation concerns, while serial MRIs carry high cost as well as risk of multiple Gadolinium doses. Previous studies have shown that tissue sound speed, derived from whole breast ultrasound tomography measurements, is a surrogate biomarker of MD. Ultrasound is ideal for performing serial measurements because it is fast and poses almost no risks. The purpose of this study was to evaluate repeated measures of the sound speed biomarker at 3, 6 and 12-months following tamoxifen initiation. METHOD AND MATERIALS. We performed a case-control comparison involving 74 participants referred by a health professional to undergo tamoxifen therapy (cases) and 150 matched participants with no history of breast cancer (controls). The cases were scanned with ultrasound tomography at baseline (i.e. before start of tamoxifen therapy), and then at 3, 6 and 12 months after tamoxifen initiation. Controls were scanned at baseline and 12 months. In the case group, sound speed was measured pre-treatment in the contralateral breast to avoid potential influences of tumor-related changes on density. In the control group, a single randomized breast was scanned. A pairwise t-test was used to assess differences in sound speed over time and between cases and controls. RESULTS. There was a steady decline in sound speed over the 12-month period for women undergoing tamoxifen therapy (mean(SD): -3.0(8.2) m/s; P=0.001). Furthermore, significant sound speed reductions were observed as early as 4-6 months after tamoxifen initiation (mean(SD): -2.1(6.8) m/s; P=0.008). In contrast, the controls demonstrated no significant change in sound speed over a 12-month period, and the difference between case-control groups was statistically significant (P=0.0009). DISCUSSION. Breast sound speed decreases rapidly after tamoxifen initiation while it remains steady for the control group. These results suggest that sound speed may be a biomarker of response to tamoxifen. Further studies are needed to assess whether this observation can predict clinical response. CONCLUSION. Ultrasound tomography may have utility in monitoring breast sound speed change as a potential biomarker of clinical tamoxifen response. Citation Format: Neb Duric, Mark Sak, Mark Sherman, Ruth Pfeiffer, Sharon Fan, Michael Simon, David Gorski, Teri Albrecht, Haythem Ali, Peter Littrup, Rachel Brem, Gretchen Gierach. Tissue sound speed: A novel imaging biomarker for measuring tamoxifen response [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 P2-11-11.

PURPOSE. Increased mammographic percent density (MPD) is a strong independent risk factor for developing breast cancer. Previous studies have shown that tissue sound speed, derived from ultrasound tomography, is a surrogate biomarker of MPD. We examined associations of sound speed and MPD with breast cancer risk in a case-control study. METHOD AND MATERIALS. We evaluated breast cancer risk associated with sound speed and MPD in a case-control study involving 59 participants with recent breast cancer diagnoses (cases, aged 30-70 years) and 150 participants with no history of breast cancer (controls), who were matched to cases on age, race, and menopausal status. The cases and controls were imaged with both ultrasound tomography (UST) and mammography. In cases, breast density was measured pre-treatment in the contralateral breast to avoid potential influences of tumor-related changes on MPD or sound speed. In controls, a randomly selected breast was imaged. The ultrasound tomography images were used to estimate the volume averaged sound speed of the breast, and the Cumulus software package was applied to mammograms to determine MPD. Odds Ratios (ORs) and 95% Confidence Intervals (CIs), adjusted for matching factors, were calculated for the relation of quartiles of MPD and sound speed with breast cancer risk. OR differences were tested using a bootstrap approach. RESULTS. MPD was associated with elevated breast cancer risk compared to controls, consistent with previous studies, although the trend did not reach statistical significance (OR per quartile=1.28, 95%CI: 0.95, 1.73; ptrend=0.10). In contrast, elevated sound speed was significantly associated with increased breast cancer risk in a dose-response fashion (OR per quartile=1.79, 95%CI: 1.30, 2.48; ptrend=0.0004). The OR-trend for sound speed was statistically significantly different from that observed for MPD (p=0.01). DISCUSSION. Our case-control study showed that increasing quartiles of whole breast sound speed were consistently and more strongly associated with increasing breast cancer risk than quartiles of MPD. These results show promise for UST’s role in breast cancer risk stratification. CONCLUSION. Elevated breast density strongly increases breast cancer risk. UST has the potential to provide a more accurate, non-ionizing method for assessing breast density and its associated breast cancer risk. Citation Format: Mark Sak, Neb Duric, Ruth Pfeiffer, Mark Sherman, Peter Littrup, Michael Simon, David Gorski, Teri Albrecht, Haythem Ali, Rachel Brem, Rachel Brem, Sharon Fan, Gretchen Gierach. Tissue sound speed is more strongly associated with breast cancer risk than mammographic percent density: A comparative case-control study [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 P3-08-28.

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.

ObjectiveTo assess the feasibility of using tissue sound speed as a quantitative marker of breast density.MethodsThis study was carried out under an Institutional Review Board–approved protocol (written consent required). Imaging data were selected retrospectively based on the availability of US tomography (UST) exams, screening mammograms with volumetric breast density data, patient age of 18 to 80 years, and weight less than 300 lbs. Sound speed images from the UST exams were used to measure the volume of dense tissue, the volume averaged sound speed (VASS), and the percent of high sound speed tissue (PHSST). The mammographic breast density and volume of dense tissue were estimated with three-dimensional (3D) software. Differences in volumes were assessed with paired t-tests. Spearman correlation coefficients were calculated to determine the strength of the correlations between the mammographic and UST assessments of breast density.ResultsA total of 100 UST and 3D mammographic data sets met the selection criteria. The resulting measurements showed that UST measured a more than 2-fold larger volume of dense tissue compared to mammography. The differences were statistically significant (P < 0.001). A strong correlation of rS = 0.85 (95% CI: 0.79–0.90) between 3D mammographic breast density (BD) and the VASS was noted. This correlation is significantly stronger than those reported in previous two-dimensional studies (rS = 0.85 vs rS = 0.71). A similar correlation was found for PHSST and mammographic BD with rS = 0.86 (95% CI: 0.80–0.90).ConclusionThe strong correlations between UST parameters and 3D mammographic BD suggest that breast sound speed should be further studied as a potential new marker for inclusion in clinical risk models.

Objectives Some US states have mandated that women be informed when they have dense breasts; however, little is known about how general knowledge about breast density (BD) affects related health decision-making. We examined the effects of BD information and imaging technology information on 138 African–American (AA) and European–American (EA) women's intentions to discuss breast cancer screening with their physicians. Methods Women were randomly assigned to receive BD information and/or imaging technology information via 2 by 2 factorial design, and completed planned behavior measures (e.g., attitudes, intentions) related to BC screening. Results Attitudes mediated the effects of BD information, and the mediation was stronger for AA women compared to EA women. Effects were more robust for BD information compared to imaging technology information. Results of moderator analyses revealed suppressor effects of injunctive norms that were moderated by imaging technology information. Conclusion Information about BD favorably influences women's intentions to engage in relevant breast health behaviors. Stronger attitude mediated-effects for AA women suggest greater scrutiny of BD information. Practice implications Since BD information may influence women's intentions to discuss BC screening, strategies to effectively present BD information to AA women should be investigated given the likelihood of their increased scrutiny of BD information.

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.

Breast density is one of the strongest predictors of breast cancer risk. Women with the densest breasts are four- to six-times more likely to develop cancer compared with those with the lowest densities. Breast density is generally assessed using mammographic imaging; however, this approach has limitations. Magnetic resonance imaging and ultrasound tomography are some alternative imaging modalities that can aid mammography in patient screening and the measurement of breast density. As breast density becomes more commonly discussed, knowledge of the advantages and limitations of breast density as a marker of risk will become more critical. This review article discusses the relationship between breast density and breast cancer risk, lists the benefits and drawbacks of using multiple different imaging modalities to measure density and briefly discusses how breast density will be applied to aid in breast cancer prevention and treatment.

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 Computer Tomography (USCT) is a promising breast imaging modality under development. Comparison to a standard method like mammography is essential for further development. Due to significant differences in image dimensionality and compression state of the breast, correlating USCT images and X-ray mammograms is challenging. In this paper we present a 2D/3D registration method to improve the spatial correspondence and allow direct comparison of the images. It is based on biomechanical modeling of the breast and simulation of the mammographic compression. We investigate the effect of including patient-specific material parameters estimated automatically from USCT images. The method was systematically evaluated using numerical phantoms and in-vivo data. The average registration accuracy using the automated registration was 11.9mm. Based on the registered images a method for analysis of the diagnostic value of the USCT images was developed and initially applied to analyze sound speed and attenuation images based on X-ray mammograms as ground truth. Combining sound speed and attenuation allows differentiating lesions from surrounding tissue. Overlaying this information on mammograms, combines quantitative and morphological information for multimodal diagnosis.

Clinical diagnostic imaging modalities of breast cancer are still having certain limitations such as low sensitivity in dense breast in mammography and low specificity of the B-mode ultrasound [1, 2]. Photoacoustic (PA) imaging has been introduced as an enabling tool to acquire important functional information of the pathologic tissues as well as molecular imaging of cancer when it is augmented with nano-sized contrast agents [3]. US tomography (UST) has shown superior utility imaging of the breast and is growing as reliable tool for characterizing breast lesions [4, 5]. In this study, we demonstrate the development of an US and PA tomography (USPAT) system, consists of a full-ring US acquisition and an all-reflective, aberration-independent, and easy to implement light delivery to achieve an omni-directional co-planar ring illumination.

Ultrasound computed tomography (USCT) holds great promise for breast cancer screening. Waveform inversion-based image reconstruction methods account for higher order diffraction effects and can produce high-resolution USCT images, but are computationally demanding. Recently, a source encoding technique was combined with stochastic gradient descent to greatly reduce image reconstruction times. However, this method bundles the stochastic data fidelity term with the deterministic regularization term. This limitation can be overcome by replacing stochastic gradient descent (SGD) with a structured optimization method, such as the regularized dual averaging (RDA) method, that exploits knowledge of the composition of the cost function. In this work, the dual averaging method is combined with source encoding techniques to improve the effectiveness of regularization while maintaining the reduced reconstruction times afforded by source encoding. It is demonstrated that each iteration can be decomposed into a gradient descent step based on the data fidelity term and a proximal update step corresponding to the regularization term. Furthermore, the regularization term is never explicitly differentiated, allowing non-smooth regularization penalties to be naturally incorporated. The wave equation is solved by use of a time-domain method. The effectiveness of this approach is demonstrated through computer-simulation and experimental studies. The results suggest that the dual averaging method can produce images with less noise and comparable resolution to those obtained by use of stochastic gradient descent.

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.

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.

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.

Hyperthermia is a promising method to enhance chemo- or radiation therapy of breast cancer and the time-temperature profile in the target and surrounding areas is the primary monitoring method. Unlike with thermal ablation of lesions, in hyperthermia there are not good alternative treatment monitoring quantities. However, there is less problem with non-monotonic thermal coefficients of speed of sound used with ultrasonic imaging of temperature. This paper tests a long discussed but little investigated method of imaging temperature using speed of sound and proposes methods of reducing edge enhancement artifacts in the temperature image. Normally, when directly using the speed of sound to reconstruct the temperature image around the tumor, there will be an abnormal bipolar edge enhancement along the boundary between two materials with different speeds of sound at a given temperature. This due to partial volume effects and can be diminished by regularized, weighted deconvolution. An initial, manual deconvolu...

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.

A population of 165 women with negative mammographic screens also received an ultrasound tomography (UST) exam at the Karmanos Cancer Institute (KCI) in Detroit, MI. Standard statistical techniques were employed to measure the associations between the various mammographic and UST related density measures and various participant characteristics such as age, weight and height. The Mammographic percent density (MPD) was found to have similar strength associations with UST mean sound speed (Spearman coefficient, rs = 0.722, p < 0.001) and UST median sound speed (rs = 0.737, p < 0.001). Both were stronger than the associations between MPD with two separate measures of UST percent density, a k-means (rs = 0.568, p < 0.001) or a threshold (rs = 0.715, p < 0.001) measure. Segmentation of the UST sound speed images into dense and non-dense volumes showed weak to moderate associations with the mammographically equivalent measures. Relationships were found to be inversely and weakly associated between age and the UST mean sound speed (rs = −0.239, p = 0.002), UST median sound speed (rs = −0.226, p= 0.004) and MPD (rs = −0.204, p= 0.008). Relationships were found to be inversely and moderately associated between BMI and the UST mean sound speed (rs = −0.429, p < 0.001), UST median sound speed (rs = −0.447, p < 0.001) and MPD (rs = −0.489, p < 0.001). The results confirm and strengthen findings presented in previous work indicating that UST sound speed imaging yields viable markers of breast density in a manner consistent with mammography, the current clinical standard. These results lay the groundwork for further studies to assess the role of sound speed imaging in risk prediction.

Ultrasound computed tomography (USCT) is a promising medical imaging modality that offers several novel tissue contrasts and holds great potential for breast cancer screening. Waveform inversion-based image reconstruction methods account for higher order diffraction effects and can produce high-resolution USCT images, but are computationally demanding. Recently, a source encoding technique was combined with stochastic gradient descent (SGD) to greatly reduce image reconstruction times. However, this method bundles the stochastic data fidelity term with the deterministic regularization term. This non-optimal approach can be overcome by replacing stochastic gradient descent with a structured optimization method, such as the regularized dual averaging (RDA) method, that exploits knowledge of the composition of the cost function. In this work, the dual averaging method is combined with source encoding techniques to improve the effectiveness of regularization while maintaining the reduced reconstruction times afforded by source encoding. It is demonstrated that, for a particular choice of regularization function, each iteration can be decomposed into a gradient descent step based on the data fidelity term and a proximal update step corresponding to the regularization term. Furthermore, the regularization term is never explicitly differentiated, allowing non-smooth regularization penalties to be naturally incorporated. The wave equation is solved by use of a time-domain k-space pseudo-spectral method, implemented on general-purpose graphics processing units. The effectiveness of this approach is demonstrated through computer simulation and experimental studies. The results suggest that the dual averaging method can produce images with less noise and comparable resolution to those obtained by use of stochastic gradient descent.

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 dierent 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 briey 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.

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 mammographic percent density >50% have a approximately three-fold increased risk of developing breast cancer, potentially making them screening candidates for breast MRI scanning. The purpose of this work is to introduce a new method to quantify mammographic percent density (MPD), and to compare the results with the current standard of care for breast density assessment. Craniocaudal (CC) and mediolateral oblique (MLO) mammograms for 104 patients were digitized and analyzed using an interactive computer-assisted segmentation routine implemented for two purposes: (1) to segment the breast area from background and radiographic markers, and (2) to segment dense from fatty portions of the breast. Our technique was evaluated by comparing the results to qualitative estimates determined by a certified breast radiologist using the BI-RADS Categorical Assessment (1 (fatty) to 4 (dense) scale). Statistically significant correlations (two-tailed, p < 0.01) were observed between calculated MPD and BI-RADS for both CC (Spearman rho = 0.67) and MLO views (Spearman rho = 0.71). For the CC view, statistically significant differences were revealed between the mean MPD for each BI-RADS category except between fatty (BI-RADS 1) and scattered (BI-RADS 2). Finally, for the MLO views, statistically significant differences in the mean MPD between all BI-RADS categories were observed. Comparing the CC and MLO views revealed a strong positive correlation (Pearson r = 0.8) in calculated MPD. In addition, an evaluation of the reproducibility of our segmentation demonstrated the average standard deviation of MPD for a subsample of eight patients, measured five times, was 1.9% (range: 0.03%-9.9%). Eliminating one misassignment reduced the average standard deviation to 0.75% (range: 0.03%-3.16%). Further analysis of approximately 10% of the patient sample revealed strong agreement (ICC = 0.80-0.85) in the reliability of MPD estimates for both mammographic views. Overall, these results demonstrate the feasibility of utilizing our approach for quantitative breast density segmentation, which may be useful for detecting small changes in MPD introduced through chemoprevention, diet, or other interventions.

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 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.

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 sound speed distribution by solving a stochastic optimization problem by use of a stochastic gradient descent algorithm. Both computer-simulation and experimental phantom studies are conducted to demonstrate the use of the WISE method. The results suggest that the WISE method maintains the high spatial resolution of waveform inversion methods while significantly reducing the computational burden.