Jennifer Kehlet Barton

We examine signal degradation effects in fiber arrays from fiber-to-fiber coupling and from cross talk attributable to backscatter from the sample medium originating from adjacent fibers in the array. An analysis of coupling and cross talk for single-mode fibers (SMFs) operating at 1310 nm with different core diameters, interaction lengths, core center spacing, and numerical apertures (NAs) is evaluated. The coupling was evaluated using beam propagation algorithms and cross talk was analyzed by using Monte Carlo methods. Several multimode fiber types that are currently used in fiber image guides were also evaluated for comparative purposes. The analysis shows that an optimum NA and core diameter can be found for a specific fiber center separation that maximizes the directly backscattered signal relative to the cross talk. The coupling between fibers can be kept less than -35 dB for interaction lengths less than 5 mm. The calculations were compared to an experimentally fabricated SMF array with 15 microm center spacing and showed good agreement. The experimental fiber array without a lens was also used in a coherent detection configuration to measure the position of a mirror. Accurate depth ranging up to a distance of 250 microm from the tip of the fiber was achieved, which was five times the Rayleigh range of the beam emitted from the fiber.

We explored plasmon resonant nanorods of gold as a contrast agent for optical coherence tomography (OCT). Nanorod suspensions were generated through wet chemical synthesis and characterized with spectrophotometry, transmission electron microscopy, and OCT. Polyacrylamide-based phantoms were generated with appropriate scattering and anisotropy coefficients (30 cm(-1) and 0.89, respectively) to image distribution of the contrast agent in an environment similar to that of tissue. The observed signal was dependent on whether the plasmon resonance peak overlapped the source bandwidth of the OCT, confirming the resonant character of enhancement. Gold nanorods with plasmon resonance wavelengths overlapping the OCT source yielded a signal-to-background ratio of 4.5 dB, relative to the tissue phantom. Strategies for OCT imaging with nanorods are discussed.

Optical coherence tomography (OCT) is an imaging modality capable of acquiring cross-sectional images of tissue using back-reflected light. Conventional OCT images have a resolution of 10-15 microm, and are thus best suited for visualizing tissue layers and structures. OCT images of collagen (with and without endothelial cells) have no resolvable features and may appear to simply show an exponential decrease in intensity with depth. However, examination of these images reveals that they display a characteristic repetitive structure due to speckle. The purpose of this study is to evaluate the application of statistical and spectral texture analysis techniques for differentiating living and non-living tissue phantoms containing various sizes and distributions of scatterers based on speckle content in OCT images. Statistically significant differences between texture parameters and excellent classification rates were obtained when comparing various endothelial cell concentrations ranging from 0 cells/ml to 25 million cells/ml. Statistically significant results and excellent classification rates were also obtained using various sizes of microspheres with concentrations ranging from 0 microspheres/ml to 500 million microspheres/ml. This study has shown that texture analysis of OCT images may be capable of differentiating tissue phantoms containing various sizes and distributions of scatterers.

Optical coherence tomography (OCT) acquires cross-sectional images of tissue by measuring back-reflected light. Images from in vivo OCT systems typically have a resolution of 10 to 15 mm, and are thus best suited for visualizing structures in the range of tens to hundreds of microns, such as tissue layers or glands. Many normal and abnormal tissues lack visible structures in this size range, so it may appear that OCT is unsuitable for identification of these tissues. However, examination of structure-poor OCT images reveals that they frequently display a characteristic texture that is due to speckle. We evaluated the application of statistical and spectral texture analysis techniques for differentiating tissue types based on the structural and speckle content in OCT images. Excellent correct classification rates were obtained when images had slight visual differences (mouse skin and fat, correct classification rates of 98.5 and 97.3%, respectively), and reasonable rates were obtained with nearly identical-appearing images (normal versus abnormal mouse lung, correct classification rates of 64.0 and 88.6%, respectively). This study shows that texture analysis of OCT images may be capable of differentiating tissue types without reliance on visible structures.