We describe a novel 3-D ultrasound technology, the quantitative transmission ultrasound system and algorithm to image a pendent breast in a water bath. Quantitative accuracy is verified using phantoms. Morphological accuracy is verified using cadaveric breast and in vivo images, and spatial resolution is estimated. This paper generalizes an earlier 2-D algorithm to a full 3-D inversion algorithm and shows the importance of such a 3-D algorithm for artifact suppression as compared with the 2-D algorithm. The resultant high-resolution ultrasound images, along with quantitative information regarding tissue speed of sound/stiffness, provide a more accurate depiction of the breast anatomy and lesions, contributing to improved breast care.

Purpose: Quantitative Transmission (QT) ultrasound has shown promise as a breast imaging modality. This study characterizes the performance of the latest generation ofQTultrasound scanners:QTScanner 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.

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.

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. 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. 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. 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.

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. 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. 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. 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.