Breast Glandular and Ductal Volume Changes during the Menstrual Cycle: A Study in 48 Breasts Using Ultralow-Frequency Transmitted Ultrasound Tomography/Volography.

The aim of this study was to show for the first time that low-frequency 3D-transmitted ultrasound tomography (3D UT, volography) can differentiate breast tissue types using tissue properties, accurately measure glandular and ductal volumes in vivo, and measure variation over time. Data were collected for 400 QT breast scans on 24 women (ages 18-71), including four (4) postmenopausal subjects, 6-10 times over 2+ months of observation. The date of onset of menopause was noted, and the cases were further subdivided into three (3) classes: pre-, post-, and peri-menopausal. The ducts and glands were segmented using breast speed of sound, attenuation, and reflectivity images and followed over several menstrual cycles. The coefficient of variation (CoV) for glandular tissue in premenopausal women was significantly larger than for postmenopausal women, whereas this is not true for the ductal CoV. The glandular standard deviation (SD) is significantly larger in premenopausal women vs. postmenopausal women, whereas this is not true for ductal tissue. We conclude that ducts do not appreciably change over the menstrual cycle in either pre- or post-menopausal subjects, whereas glands change significantly over the cycle in pre-menopausal women, and 3D UT can differentiate ducts from glands in vivo.

Spectral-based Quantitative Ultrasound Imaging Processing Techniques: Comparisons of RF Versus IQ Approaches.

Quantitative ultrasound (QUS) is an imaging technique which includes spectral-based parameterization. Typical spectral-based parameters include the backscatter coefficient (BSC) and attenuation coefficient slope (ACS). Traditionally, spectral-based QUS relies on the radio frequency (RF) signal to calculate the spectral-based parameters. Many clinical and research scanners only provide the in-phase and quadrature (IQ) signal. To acquire the RF data, the common approach is to convert IQ signal back into RF signal via mixing with a carrier frequency. In this study, we hypothesize that the performance, that is, accuracy and precision, of spectral-based parameters calculated directly from IQ data is as good as or better than using converted RF data. To test this hypothesis, estimation of the BSC and ACS using RF and IQ data from software, physical phantoms and in vivo rabbit data were analyzed and compared. The results indicated that there were only small differences in estimates of the BSC between when using the original RF, the IQ derived from the original RF and the RF reconverted from the IQ, that is, root mean square errors (RMSEs) were less than 0.04. Furthermore, the structural similarity index measure (SSIM) was calculated for ACS maps with a value greater than 0.96 for maps created using the original RF, IQ data and reconverted RF. On the other hand, the processing time using the IQ data compared to RF data were substantially less, that is, reduced by more than a factor of two. Therefore, this study confirms two things: (1) there is no need to convert IQ data back to RF data for conducting spectral-based QUS analysis, because the conversion from IQ back into RF data can introduce artifacts. (2) For the implementation of real-time QUS, there is an advantage to convert the original RF data into IQ data to conduct spectral-based QUS analysis because IQ data-based QUS can improve processing speed.

Full Wave Inversion and Inverse Scattering in Ultrasound Tomography/Volography.

Ultrasound breast tomography has been around for more than 40 years. Early approaches to reconstruction focused on simple algebraic reconstructions and bent ray techniques. These approaches were not able to provide high-quality and high spatial-resolution images. The advent of inverse scattering approaches resulted in a shift in image reconstruction approaches for breast tomography and a subsequent improvement in image quality. Full wave inverse solvers were developed to improve the reconstruction times without sacrificing image quality. The development of GPUs has markedly decreased the time for reconstruction using inverse scatting approaches. The development of fully 3D image solvers and hardware capable of capturing out of plane scattering have resulted in further improvement in breast tomography. This chapter discusses the state-of-the-art in ultrasound breast tomography, its history, the theory behind inverse scattering, approximations that are included to improve convergence, 3D image reconstruction, and hardware implementation of the constructions.

Low frequency 3D transmission ultrasound tomography: technical details and clinical implications.

A novel 3D ultrasound tomographic (3D UT) method (called volography) that creates a speed of sound (SOS) map and a reflection modality that is co-registered are reviewed and shown to be artifact free even in the presence of high contrast and thus shown to be applicable for breast, orthopedic and pediatric clinical use cases. The 3D UT images are almost isotropic with mm resolution and the reflection image is compounded over 360 degrees to create sub-mm resolution in plane. METHODS: The physics of ultrasound scattering requires 3D modeling and the concomitant high computational cost is ameliorated with a bespoke algorithm (paraxial approximation - discussed here) and Nvidia GPUs. The resulting reconstruction times are tabulated for clinical relevance. The resulting SOS map is used to create a refraction corrected reflection image at ∼3.6 MHz center frequency. The transmission data are highly redundant, collected over 360 degrees and at 2 mm levels by true matrix receiver arrays yielding 3D data. The high resolution SOS and attenuation maps and reflection images are used in a segmentation algorithm that optimally utilizes this information to segment out glandular, ductal, connective tissue, fat and skin. These volumes are used to estimate breast density, an important correlate to cancer. RESULTS: Multiple SOS images of breast, knee and segmentations of breast glandular and ductal tissue are shown. Spearman rho is calculated between our volumetric breast density estimates and Volpara™ from mammograms, as 0.9332. Multiple timing results are shown and indicate the variability of the reconstruction times with breast size and type but are ∼30 minutes for average size breast. The timing results with the 3D algorithm indicate ∼60 minute reconstruction times for pediatrics with two Nvidia GPUs. Characteristic variations of the glandular and ductal volumes over time are shown. The SOS from QT images are compared with literature values. The results of a multi-reader multi-case (MRMC) study are shown that compares the 3D UT with full field digital mammography and resulted in an average increase in ROC AUC of 10%. Orthopedic (knee) 3D UT images compared with MRI indicate regions of zero signal in the MRI are clearly displayed in the QT image. Explicit representation of the acoustic field is shown, indicating its 3D nature. An image of in vivo breast with the chest muscle is shown and speed of sound agreement with literature values are tabulated. Reference is made to a recently published paper validating pediatric imaging. CONCLUSIONS: The high Spearman rho indicates a monotonic (not necessarily linear) relation between our method and industry gold standard Volpara™ density. The acoustic field verifies the need for 3D modeling. The MRMC study, the orthopedic images, breast density study, and references, all indicate the clinical utility of the SOS and reflection images. The QT image of the knee shows its ability to monitor tissue the MRI cannot. The included references and images herein indicate the proof of concept for 3D UT as a viable and valuable clinical adjunct in pediatric and orthopedic situations in addition to the breast imaging.

Whole-Body Imaging Using Low Frequency Transmission Ultrasound.

RATIONALE AND OBJECTIVES: To indicate that 3D low-frequency ultrasound tomography with 3D data acquisition (volography) is a safe, low-cost, high-resolution, whole-body meso-scale medical imaging modality that gives high-resolution quantitatively accurate clinically relevant images. MATERIALS AND METHODS: We compare the speed of sound accuracy in various organs in situ. We validate our 3D ultrasound tomography images using MRI and gross section anatomy as ground truth in 10-day old piglets. Data acquisition is accomplished with the QT Scanner at ∼1 MHz center frequency, and array transceivers for reflection data @3.6 MHz. Images are generated with unique model-based 3D ultrasound tomography algorithms. In reflection, we use 3D refraction-corrected ray tracing to allow 360° compounding with sub-mm resolution. Four 10-12 day old pigs were anesthetized and whole-body images were acquired via low-frequency transmitted ultrasound and 3T MRI. RESULTS: Tissue values were within an average of 1.07% (0.5%) of the literature values. We also show the detailed correlation of our images with MRI images in axial, coronal, and sagittal views. Volography images of a piglet show high resolution and quantitative accuracy, showing more contrast &resolution than 3T MRI, including the kidney showing medulla, cortex and fibrous cover, and small intestines with ileal lumen detail visible. CONCLUSION: We establish that 3D ultrasound tomography (volography), yields high-resolution quantitatively accurate images whole-body images in presence of bone and air which are potentially clinically useful but have not appeared in the literature.

Full wave 3D inverse scattering transmission ultrasound tomography in the presence of high contrast.

We present here a quantitative ultrasound tomographic method yielding a sub-mm resolution, quantitative 3D representation of tissue characteristics in the presence of high contrast media. This result is a generalization of previous work where high impedance contrast was not present and may provide a clinically and laboratory relevant, relatively inexpensive, high resolution imaging method for imaging in the presence of bone. This allows tumor, muscle, tendon, ligament or cartilage disease monitoring for therapy and general laboratory or clinical settings. The method has proven useful in breast imaging and is generalized here to high-resolution quantitative imaging in the presence of bone. The laboratory data are acquired in ~ 12 min and the reconstruction in ~ 24 min-approximately 200 times faster than previously reported simulations in the literature. Such fast reconstructions with real data require careful calibration, adequate data redundancy from a 2D array of 2048 elements and a paraxial approximation. The imaging results show that tissue surrounding the high impedance region is artifact free and has correct speed of sound at sub-mm resolution.

Quantitative Assessment of Breast Density: Transmission Ultrasound is Comparable to Mammography with Tomosynthesis.

Elevated breast density is among the strongest independent predictors of breast cancer. Breast density scores are critical inputs in models used to calculate a patient's lifetime risk of developing breast cancer. Today, the only FDA-cleared technology for assessing breast density uses mammography. An alternative modality for breast density quantification is 3D transmission ultrasound (TU). In this retrospective study, we compared automated breast density calculations derived from TU using quantitative breast density (QBD) and mammography with tomosynthesis using VolparaDensity 3.1 for 225 breasts. Pearson correlation coefficients (r) and intraclass correlation coefficients were compared. Subset analyses of extremely dense breasts, premenopausal, and postmenopausal breasts were also performed. Comparative analysis between radiologist-derived density assessment and objective automated scores was performed. Calculations from TU and mammography with tomosynthesis for breast density, total breast volume (TBV), and fibroglandular volume (FGV) were strongly correlated (r = 0.91, 0.92, and 0.67, respectively). We observed moderate absolute agreement for FGV and breast density, and strong absolute agreement for TBV. A subset of 56 extremely dense breasts showed similar trends, however with lower breast density agreement in the subset than in the full study. No significant difference existed in density correlation between premenopausal and postmenopausal breasts across modalities. QBD calculations from TU were strongly correlated with breast density scores from VolparaDensity. TU systematically measured higher FGV and breast density compared with mammography, and the difference increased with breast density. IMPACT: TU of the breast can accurately quantify breast density comparable with mammography with tomosynthesis.

Quantitative assessment of breast density using transmission ultrasound tomography.

PURPOSE: Breast density is important in the evaluation of breast cancer risk. At present, breast density is evaluated using two-dimensional projections from mammography with or without tomosynthesis using either (a) subjective assessment or (b) a computer-aided approach. The purpose of this work is twofold: (a) to establish an algorithm for quantitative assessment of breast density using quantitative three-dimensional transmission ultrasound imaging; and (b) to determine how these quantitative assessments compare with both subjective and objective mammographic assessments of breast density. METHODS: We described and verified a threshold-based segmentation algorithm to give a quantitative breast density (QBD) on ultrasound tomography images of phantoms of known geometric forms. We also used the algorithm and transmission ultrasound tomography to quantitatively determine breast density by separating fibroglandular tissue from fat and skin, based on imaged, quantitative tissue characteristics, and compared the quantitative tomography segmentation results with subjective and objective mammographic assessments. RESULTS: Quantitative breast density (QBD) measured in phantoms demonstrates high quantitative accuracy with respect to geometric volumes with average difference of less than 0.1% of the total phantom volumes. There is a strong correlation between QBD and both subjective mammographic assessments of Breast Imaging - Reporting and Data System (BI-RADS) breast composition categories and Volpara density scores - the Spearman correlation coefficients for the two comparisons were calculated to be 0.90 (95% CI: 0.71-0.96) and 0.96 (95% CI: 0.92-0.98), respectively. CONCLUSIONS: The calculation of breast density using ultrasound tomography and the described segmentation algorithm is quantitatively accurate in phantoms and highly correlated with both subjective and Food and Drug Administration (FDA)-cleared objective assessments of breast density.

Quantitative transmission ultrasound tomography: Imaging and performance characteristics.

PURPOSE: Quantitative Transmission (QT) ultrasound has shown promise as a breast imaging modality. This study characterizes the performance of the latest generation of QT ultrasound scanners: QT Scanner 2000. METHODS: The scanner consists of a 2048-element ultrasound receiver array for transmission imaging and three transceivers for reflection imaging. Custom fabricated phantoms were used to quantify the imaging performance parameters. The specific performance parameters that have been characterized are spatial resolution (as point spread function), linear measurement accuracy, contrast to noise ratio, and image uniformity, in both transmission and reflection imaging modalities. RESULTS: The intrinsic in-plane resolution was measured to be better than 1.5 mm and 1.0 mm for transmission and reflection modalities respectively. The linear measurement accuracy was measured to be, on average, approximately 1% for both the modalities. Speed of sound image uniformity and measurement accuracy were calculated to be 99.5% and <0.2% respectively. Contrast to noise ratio (CNR) measurements vary as a function of object size. CONCLUSIONS: The results show an improvement in the imaging performance of the system in comparison to earlier ultrasound tomography systems, which are applicable to clinical applications of the system, such as breast imaging.

Objective breast tissue image classification using Quantitative Transmission ultrasound tomography.

Quantitative Transmission Ultrasound (QT) is a powerful and emerging imaging paradigm which has the potential to perform true three-dimensional image reconstruction of biological tissue. Breast imaging is an important application of QT and allows non-invasive, non-ionizing imaging of whole breasts in vivo. Here, we report the first demonstration of breast tissue image classification in QT imaging. We systematically assess the ability of the QT images' features to differentiate between normal breast tissue types. The three QT features were used in Support Vector Machines (SVM) classifiers, and classification of breast tissue as either skin, fat, glands, ducts or connective tissue was demonstrated with an overall accuracy of greater than 90%. Finally, the classifier was validated on whole breast image volumes to provide a color-coded breast tissue volume. This study serves as a first step towards a computer-aided detection/diagnosis platform for QT.

Anatomy-Correlated Breast Imaging and Visual Grading Analysis Using Quantitative Transmission Ultrasound™.

Objectives. This study presents correlations between cross-sectional anatomy of human female breasts and Quantitative Transmission (QT) Ultrasound, does discriminate classifier analysis to validate the speed of sound correlations, and does a visual grading analysis comparing QT Ultrasound with mammography. Materials and Methods. Human cadaver breasts were imaged using QT Ultrasound, sectioned, and photographed. Biopsies confirmed microanatomy and areas were correlated with QT Ultrasound images. Measurements were taken in live subjects from QT Ultrasound images and values of speed of sound for each identified anatomical structure were plotted. Finally, a visual grading analysis was performed on images to determine whether radiologists' confidence in identifying breast structures with mammography (XRM) is comparable to QT Ultrasound. Results. QT Ultrasound identified all major anatomical features of the breast, and speed of sound calculations showed specific values for different breast tissues. Using linear discriminant analysis overall accuracy is 91.4%. Using visual grading analysis readers scored the image quality on QT Ultrasound as better than on XRM in 69%-90% of breasts for specific tissues. Conclusions. QT Ultrasound provides accurate anatomic information and high tissue specificity using speed of sound information. Quantitative Transmission Ultrasound can distinguish different types of breast tissue with high resolution and accuracy.

Imaging Performance of Quantitative Transmission Ultrasound.

Quantitative Transmission Ultrasound (QTUS) is a tomographic transmission ultrasound modality that is capable of generating 3D speed-of-sound maps of objects in the field of view. It performs this measurement by propagating a plane wave through the medium from a transmitter on one side of a water tank to a high resolution receiver on the opposite side. This information is then used via inverse scattering to compute a speed map. In addition, the presence of reflection transducers allows the creation of a high resolution, spatially compounded reflection map that is natively coregistered to the speed map. A prototype QTUS system was evaluated for measurement and geometric accuracy as well as for the ability to correctly determine speed of sound.

Quantitative volumetric breast imaging with 3D inverse scatter computed tomography.

A method was developed to map tissue properties of the entire breast including sound speed and attenuation using fully 3D nonlinear inverse-scattering tomography. Clinical measurements suggest that in breast tissue benign and cancerous lesions may be identified in part by these inherent acoustic parameters. Sound speed accuracy and linearity are very high over a wide range (1325-1700 m/sec) with ~1.5 mm resolution at 2 MHz in transmission mode. Attenuation tomograms provide image contrast over a wide range (0-4 dB/cm/MHz) and assist classification of masses. High resolution 0.6 mm volumetric reflection tomograms are acquired with bandwidth 2-8 MHz, are refraction-corrected with the transmission tissue data and are precisely registered in 3D with the transmission volumes. USCT promises an automated whole-breast scan providing a global view of the entire breast in 3D, facilitating comparison to prior exams in a reproducible geometry. Scanner design, automated operation and results of our trial with over 125 subjects with confirmed breast masses will be presented with detailed comparison to conventional sonography and MRI.