Simulation of diffuse photon migration in tissue by a Monte Carlo method derived from the optical scattering of spheroids.

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.

Three-dimensional tomographic reconstruction of mesospheric airglow structures using two-station ground-based image measurements.

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.

High-frequency ultrasound for intraoperative margin assessments in breast conservation surgery: a feasibility study.

BACKGROUND: In 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. METHODS: Ultrasonic 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. RESULTS: The 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. CONCLUSIONS: Results 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.

Ultrasonic differentiation of normal versus malignant breast epithelial cells in monolayer cultures.

Normal and malignant mammary epithelial cells were studied using laboratory measurements, wavelet analysis, and numerical simulations of monolayer cell cultures to determine whether microscopic breast cancer can be detected in vitro with high-frequency ultrasound. Pulse-echo waveforms were acquired by immersing a broadband, unfocused 50-MHz transducer in the growth media of cell culture well plates and collecting the first reflection from the well bottoms. The simulations included a multilayer pulse-reflection model and a model of two-dimensional arrays of spherical cells and nuclei. The results show that normal and malignant cells produce time-domain signals and spectral features that are significantly different.

Simulation of elastic wave scattering in cells and tissues at the microscopic level.

The scattering of longitudinal and shear waves from spherical, nucleated cells and three-dimensional tissues with simple and hierarchical microstructures was numerically modeled at the microscopic level using an iterative multipole approach. The cells were modeled with a concentric core-shell (nucleus-cytoplasm) structure embedded in an extracellular matrix. Using vector multipole expansions and boundary conditions, scattering solutions were derived for single cells with either solid or fluid properties for each of the cell components. Tissues were modeled as structured packings of cells. Multiple scattering between cells was simulated using addition theorems to translate the multipole fields from cell to cell in an iterative process. Backscattering simulations of single cells indicated that changes in the shear properties and nuclear diameter had the greatest effect on the frequency spectra. Simulated wave field images and high-frequency spectra (15-75 MHz) from tissues containing 1211-2137 cells exhibited up to 20% enhancement of the field amplitudes at the plasma membrane, significant changes in spectral features due to neoplastic and other microstructural alterations, and a detection threshold of approximately 8.5% infiltration of tumor cells into normal tissue. These findings suggest that histology-based simulations may provide insight into fundamental ultrasound-tissue interactions and help in the development of new medical technologies.

Histology-based simulations for the ultrasonic detection of microscopic cancer in vivo.

Ultrasonic spectroscopy may offer an alternative to imaging methods for the in vivo detection of microscopic cancer. To investigate this potential, a numerical model that incorporates multiple scattering, wave-mode conversion, and hierarchical microstructures was developed to simulate ultrasonic interactions in biological tissue at the microscopic level. Simulated high-frequency (20-75 MHz) spectra of up to 2137 cells displayed significant correlations to nucleus diameter and malignant cell infiltration, and indicated as few as 300 malignant cells may be detectable in normal tissue. The results suggest that ultrasonic spectroscopy combined with simulation-based interpretive models may provide real-time histopathology during surgeries, biopsies, and endoscopies.