Glicemical analysis of human blood serum using FT-Raman: a new approach.

BACKGROUND DATA: Fourier transform Raman spectroscopy (FT-Raman) is a noninvasive diagnostic tool largely applied to the analysis of biological fluids and tissues. METHODS: We examined the variation of carbohydrate concentration in human blood during 180 min relative to 29 spectra of patients split into four categories: hypoglycemic, healthy, threshold, and diabetic. The main bands monitored were placed in 960, 1030, 1091, 1128, and 1205 cm(-1). These bands were respectively attributed to C-O, C-C (stretching), C-O-H and C-O-C of carbohydrates. In this study, the Raman scattering signal of the all the blood samples was collected during 360 sec. The calculated correlation coefficient (R) between the concentration of carbohydrates and the Raman intensity was 0.923. CONCLUSIONS: The obtained results are reasonable according to classical biochemical analysis. Our proposed FT-Raman-based method was shown to be suitable for the monitoring of carbohydrate concentration in human blood, and presented some advantages over classical biochemical methods, such as real-time analysis, required small sample volume, and was nondestructive, and the samples did not need any previous treatment.

Fluorescence and reflectance spectroscopy for identification of atherosclerosis in human carotid arteries using principal components analysis.

OBJECTIVES: The aim of this work was to verify the differentiation between normal and pathological human carotid artery tissues by using fluorescence and reflectance spectroscopy in the 400- to 700-nm range and the spectral characterization by means of principal components analysis. BACKGROUND DATA: Atherosclerosis is the most common and serious pathology of the cardiovascular system. Principal components represent the main spectral characteristics that occur within the spectral data and could be used for tissue classification. MATERIALS AND METHODS: Sixty postmortem carotid artery fragments (26 non-atherosclerotic and 34 atherosclerotic with non-calcified plaques) were studied. The excitation radiation consisted of a 488-nm argon laser. Two 600-microm core optical fibers were used, one for excitation and one to collect the fluorescence radiation from the samples. The reflectance system was composed of a halogen lamp coupled to an excitation fiber positioned in one of the ports of an integrating sphere that delivered 5 mW to the sample. The photo-reflectance signal was coupled to a (1/4)-m spectrograph via an optical fiber. Euclidean distance was then used to classify each principal component score into one of two classes, normal and atherosclerotic tissue, for both fluorescence and reflectance. RESULTS: The principal components analysis allowed classification of the samples with 81% sensitivity and 88% specificity for fluorescence, and 81% sensitivity and 91% specificity for reflectance. CONCLUSIONS: Our results showed that principal components analysis could be applied to differentiate between normal and atherosclerotic tissue with high sensitivity and specificity.