BackgroundIn addition to breast imaging, ultrasound offers the potential for characterizing and distinguishing between benign and malignant breast tissues due to their different microstructures and material properties. The aim of this study was to determine if high-frequency ultrasound (20-80 MHz) can provide pathology sensitive measurements for the ex vivo detection of cancer in margins during breast conservation surgery.MethodsUltrasonic tests were performed on resected margins and other tissues obtained from 17 patients, resulting in 34 specimens that were classified into 15 pathology categories. Pulse-echo and through-transmission measurements were acquired from a total of 57 sites on the specimens using two single-element 50-MHz transducers. Ultrasonic attenuation and sound speed were obtained from time-domain waveforms. The waveforms were further processed with fast Fourier transforms to provide ultrasonic spectra and cepstra. The ultrasonic measurements and pathology types were analyzed for correlations. The specimens were additionally re-classified into five pathology types to determine specificity and sensitivity values.ResultsThe density of peaks in the ultrasonic spectra, a measure of spectral structure, showed significantly higher values for carcinomas and precancerous pathologies such as atypical ductal hyperplasia than for normal tissue. The slopes of the cepstra for non-malignant pathologies displayed significantly greater values that differentiated them from the normal and malignant tissues. The attenuation coefficients were sensitive to fat necrosis, fibroadenoma, and invasive lobular carcinoma. Specificities and sensitivities for differentiating pathologies from normal tissue were 100% and 86% for lobular carcinomas, 100% and 74% for ductal carcinomas, 80% and 82% for benign pathologies, and 80% and 100% for fat necrosis and adenomas. Specificities and sensitivities were also determined for differentiating each pathology type from the other four using a multivariate analysis. The results yielded specificities and sensitivities of 85% and 86% for lobular carcinomas, 85% and 74% for ductal carcinomas, 100% and 61% for benign pathologies, 84% and 100% for fat necrosis and adenomas, and 98% and 80% for normal tissue.ConclusionsResults from high-frequency ultrasonic measurements of human breast tissue specimens indicate that characteristics in the ultrasonic attenuation, spectra, and cepstra can be used to differentiate between normal, benign, and malignant breast pathologies.

This research presents the first application of tomographic techniques for investigating gravity wave structures in polar mesospheric clouds (PMCs) imaged by the Cloud Imaging and Particle Size instrument on the NASA AIM satellite. Albedo data comprising consecutive PMC scenes were used to tomographically reconstruct a 3‐D layer using the Partially Constrained Algebraic Reconstruction Technique algorithm and a previously developed “fanning” technique. For this pilot study, a large region (760 × 148 km) of the PMC layer (altitude ~83 km) was sampled with a ~2 km horizontal resolution, and an intensity weighted centroid technique was developed to create novel 2‐D surface maps, characterizing the individual gravity waves as well as their altitude variability. Spectral analysis of seven selected wave events observed during the Northern Hemisphere 2007 PMC season exhibited dominant horizontal wavelengths of ~60–90 km, consistent with previous studies. These tomographic analyses have enabled a broad range of new investigations. For example, a clear spatial anticorrelation was observed between the PMC albedo and wave‐induced altitude changes, with higher‐albedo structures aligning well with wave troughs, while low‐intensity regions aligned with wave crests. This result appears to be consistent with current theories of PMC development in the mesopause region. This new tomographic imaging technique also provides valuable wave amplitude information enabling further mesospheric gravity wave investigations, including quantitative analysis of their hemispheric and interannual characteristics and variations.

A new methodology is presented to create two-dimensional (2D) and three-dimensional (3D) tomographic reconstructions of mesospheric airglow layer structure using two-station all-sky image measurements. A fanning technique is presented that produces a series of cross-sectional 2D reconstructions, which are combined to create a 3D mapping of the airglow volume. The imaging configuration is discussed and the inherent challenges of using limited-angle data in tomographic reconstructions have been analyzed using artificially generated imaging objects. An iterative reconstruction method, the partially constrained algebraic reconstruction technique (PCART), was used in conjunction with a priori information of the airglow emission profile to constrain the height of the imaged region, thereby reducing the indeterminacy of the inverse problem. Synthetic projection data were acquired from the imaging objects and the forward problem to validate the tomographic method and to demonstrate the ability of this technique to accurately reconstruct information using only two ground-based sites. Reconstructions of the OH airglow layer were created using data recorded by all-sky CCD cameras located at Bear Lake Observatory, Utah, and at Star Valley, Wyoming, with an optimal site separation of ∼100 km. The ability to extend powerful 2D and 3D tomographic methods to two-station ground-based measurements offers obvious practical advantages for new measurement programs. The importance and applications of mesospheric tomographic reconstructions in airglow studies, as well as the need for future measurements and continued development of techniques of this type, are discussed.

Ultrasound-induced cavitation in vegetable oils can be used to control the crystallization and resulting texture of food products such as shortenings. Cavitation in oils has not been explored as extensively as in aqueous systems, however. To more fully understand cavitation in vegetable oils, high-intensity ultrasound (HIU) and broadband 1.0-MHz transducers were used to generate and measure cavitation in soybean oil experimentally. To interpret the results, multipole-based models were used to simulate ultrasonic scattering from the cavitation bubbles in the 0.4–4.0 MHz range. Ultrasonic reflection spectra, transmission spectra, and velocities were simulated for spherical bubble clouds centered between two transducers. The size, concentration, and random configuration of the bubbles in the clouds were varied to find diagnostic features to correlate with experimental data. The models indicated that the configuration of the bubbles have unexpectedly large effects on the ultrasonic spectra even at dilute concentrations (0.2–5.0%). The simulated spectra additionally showed low-frequency (<2 MHz) and high-frequency (>2 MHz) features that correlated with bubble concentration and bubble size, respectively. The experimental results included spectral features that may be associated with turbulence in the oil and the persistence of low-frequency backscatter after stopping the HIU, indicating a slow decay in bubble concentration.

A Monte Carlo method was derived from the optical scattering properties of spheroidal particles and used for modeling diffuse photon migration in biological tissue. The spheroidal scattering solution used a separation of variables approach and numerical calculation of the light intensity as a function of the scattering angle. A Monte Carlo algorithm was then developed which utilized the scattering solution to determine successive photon trajectories in a three-dimensional simulation of optical diffusion and resultant scattering intensities in virtual tissue. Monte Carlo simulations using isotropic randomization, Henyey-Greenstein phase functions, and spherical Mie scattering were additionally developed and used for comparison to the spheroidal method. Intensity profiles extracted from diffusion simulations showed that the four models differed significantly. The depth of scattering extinction varied widely among the four models, with the isotropic, spherical, spheroidal, and phase function models displaying total extinction at depths of 3.62, 2.83, 3.28, and 1.95 cm, respectively. The results suggest that advanced scattering simulations could be used as a diagnostic tool by distinguishing specific cellular structures in the diffused signal. For example, simulations could be used to detect large concentrations of deformed cell nuclei indicative of early stage cancer. The presented technique is proposed to be a more physical description of photon migration than existing phase function methods. This is attributed to the spheroidal structure of highly scattering mitochondria and elongation of the cell nucleus, which occurs in the initial phases of certain cancers. The potential applications of the model and its importance to diffusive imaging techniques are discussed.