Fiber optic probes are a key element for biomedical spectroscopic sensing. We review the use of fiber optic probes for optical spectroscopy, focusing on applications in turbid media, such as tissue. The design of probes for reflectance, polarized reflectance, fluorescence, and Raman spectroscopy is illustrated. We cover universal design principles as well as technologies for beam deflecting and reshaping.

Monte Carlo techniques provide an important means to investigate the combined contributions of multiple fluorophores to measured emission spectra. The approach will prove increasingly valuable as a more sophisticated understanding of in vivo optical properties is developed.

This study evaluates the potential of near-infrared Raman spectroscopy for in vivo detection of squamous dysplasia, a precursor to cervical cancer. A pilot clinical trial was carried out at three clinical sites. Raman spectra were measured from one colposcopically normal and one abnormal area of the cervix. These sites were then biopsied and submitted for routine histologic analysis. Twentyfour evaluable measurements were made in vivo in 13 patients. Cervical tissue Raman spectra contain peaks in the vicinity of 1070, 1180, 1195, 1210, 1245, 1330, 1400, 1454, 1505, 1555, 1656, and 1760 cm−1. The ratio of intensities at 1454 to 1656 cm−1 is greater for squamous dysplasia than all other tissue types, while the ratio of intensities at 1330 to 1454 cm−1 is lower for samples with squamous dysplasia than all other tissue types. A simple algorithm based on these two intensity ratios separates high-grade squamous dysplasia from all others, misclassifying only one sample. Spectra measured in vivo resemble those measured in vitro. Cervical epithelial cells may contribute to tissue spectra at 1330 cm−1, a region associated with DNA. In contrast, epithelial cells probably do not contribute to tissue spectra at 1454 cm−1, a region associated with collagen and phospholipids.

In this study, we investigate the potential of near-infrared Raman spectroscopy to differentiate cervical precancers from normal tissues, inflammation and metaplasia and to differentially diagnose low-grade and high-grade precancers. Near infrared Raman spectra were measured from 36 biopsies from 18 patients in vitro. Detection algorithms were developed and evaluated relative to histopathologic examination. Algorithms based on empirically selected peak intensities, ratios of peak intensities and a combination of principal component analysis for data reduction and Fisher discriminant analysis for classification were investigated. Spectral peaks were tentatively identified from measured spectra of potential chromophores. Empirically selected normalized intensities can differentiate precancers from other tissues with an average sensitivity and specificity of 88 +/- 4% and 92 +/- 4%. Ratios of unnormalized intensities can differentiate precancers from other tissues with a sensitivity and specificity of 82% and 88% and high-grade from low-grade lesions with a sensitivity and specificity of 100%. Using multivariate methods, intensities at eight frequencies can be used to differentiate precancers from all other tissues with a sensitivity and specificity of 82% and 92% in an unbiased test. Raman algorithms can potentially separate benign abnormalities such as inflammation and metaplasia from precancers. Comparison of tissue spectra to published and measured chromophore spectra indicate that the most likely primary contributors to the tissue spectra are collagen, nucleic acids, phospholipids and glucose 1-phosphate. These results suggest that near-infrared Raman spectroscopy can be used for cervical precancer diagnosis and may be able to accurately separate samples with inflammation and metaplasia from precancer.

While it is known that the aorta stiffens with location and age, little is known about the underlying mechanisms that govern these alterations. The purpose of this study was to investigate the relationship between the anisotropic biomechanical behavior and extracellular matrix microstructure of the human aorta and quantify how each changes with location and age. A total of 207 specimens were harvested from 5 locations (ascending n = 33, arch n = 38, descending n = 54, suprarenal n = 52, and abdominal n = 30) of 31 autopsy donor aortas (aged 3 days to 93 years). Each specimen underwent planar biaxial testing in order to derive quantitative biomechanical endpoints of anisotropic stiffness and compliance. Quantitative measures of fiber alignment and degree of fiber alignment were also generated on the same samples using a small-angle light scattering (SALS) technique. Circumferential and axial stiffening occurred with age and increased from the proximal to distal aorta, and the abdominal region was found to be more stiff than all others (p ≤ 0.006). Specimens from donors aged 61 and above were drastically more stiff than younger specimens (p < 0.001) and demonstrated greater circumferential compliance and axial stiffening (p < 0.001). Fiber direction for all ages and locations was predominantly circumferential (p < 0.001), and the degree of fiber alignment was found to increase with age (p < 0.001). Our results demonstrate that the aorta becomes more biomechanically and structurally anisotropic after age 60; with significant changes occurring preferentially in the abdominal aorta, these changes may play an important role in the predisposition of disease formation (e.g., aneurysm) in this region with age.

Purpose: Among gynecologic cancers, ovarian cancer is the second most common and has the highest mortality. Currently, there is no accurate early diagnostic technique for ovarian cancer. Furthermore, little is understood regarding the early progression of this disease. We have imaged multiphoton interactions of endogenous tissue constituents from normal and abnormal ovarian biopsies that were kept viable during transport from the operating room and microscopy. Experimental Design: The ovarian surface and underlying stroma were assessed with two-photon excited fluorescence (2PEF) and second harmonic generation (SHG). High-resolution, optically sectioned images were analyzed for epithelial morphology based on 2PEF and collagen density and structural integrity based on SHG. Additionally, multiwavelength 2PEF provided an estimation of the cellular redox ratio of epithelial cells.

In this study, we investigate the potential of near-infrared Raman spectroscopy to differentiate cervical precancers from normal tissues, inflammation and metaplasia and to differentially diagnose low-grade and high-grade precancers. Near infrared Raman spectra were measured from 36 biopsies from 18 patients in vitro. Detection algorithms were developed and evaluated relative to histopathologic examination. Algorithms based on empirically selected peak intensities, ratios of peak intensities and a combination of principal component analysis for data reduction and Fisher discriminant analysis for classification were investigated. Spectral peaks were tentatively identified from measured spectra of potential chromophores. Empirically selected normalized intensities can differentiate precancers from other tissues with an average sensitivity and specificity of 88 +/- 4% and 92 +/- 4%. Ratios of unnormalized intensities can differentiate precancers from other tissues with a sensitivity and specificity of 82% and 88% and high-grade from low-grade lesions with a sensitivity and specificity of 100%. Using multivariate methods, intensities at eight frequencies can be used to differentiate precancers from all other tissues with a sensitivity and specificity of 82% and 92% in an unbiased test. Raman algorithms can potentially separate benign abnormalities such as inflammation and metaplasia from precancers. Comparison of tissue spectra to published and measured chromophore spectra indicate that the most likely primary contributors to the tissue spectra are collagen, nucleic acids, phospholipids and glucose 1-phosphate. These results suggest that near-infrared Raman spectroscopy can be used for cervical precancer diagnosis and may be able to accurately separate samples with inflammation and metaplasia from precancer.

To better understand interstitial matrix remodeling during angiogenesis, we probed endogenous optical signatures of collagen fibrils and cells with multiphoton microscopy to noninvasively visualize, in real-time, changes to fibril organization around angiogenic sprouts and growing neovessels. From analyses of the second-harmonic generation signal from fibrillar collagen and two-photon excited fluorescence, as well as coherent transmitted light from vascular cells, we found that microvessel fragments interacting with the collagen matrix exhibited two key features: a strong association of fibrillar collagen around the parent vessel fragment during vessel construct reconstitution and a substantial collagen fibril reorganization by sprout and neovessel tips. Results indicate that angiogenic sprouts and growing neovessels actively and differentially remodel existing collagen fibrils. This imaging approach to assess local changes in matrix organization may have a broader impact on tissue biology and mechanics during angiogenesis and allow for new insights in cardiovascular, diabetes, and cancer research.