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Back-illuminated charged-coupled device (BI-CCD) arrays increase quantum efficiency but also amplify etaloning, a multiplicative, wavelength-dependent fixed-pattern effect. When spectral data from hundreds of BI-CCD rows are combined, the averaged spectrum will generally appear etalon-free. This can mask substantial etaloning at the row level, even if the BI-CCD has been treated to suppress the effect. This paper compares two methods of etalon correction, one with simple averaging and one with row-by-row calibration using a fluorescence standard. Two BI-CCD arrays, both roughened by the supplier to reduce etaloning, were used to acquire Raman spectra of murine bone specimens. For one array, etaloning was the dominant source of noise under the exposure conditions chosen, even for the averaged spectrum across all rows; near-infrared-excited Raman peaks were noticeably affected. In this case, row-by-row calibration improved the spectral quality of the average spectrum. The other CCD’s performance was shot-noise limited and therefore received no benefit from the extra calibration. The different results highlight the importance of checking for and correcting row-level fixed pattern when measuring weak Raman signals in the presence of a large fluorescence background.

In near-infrared spectroscopy (NIRS) of human cerebral hemodynamics, detection of stimulus-related responses is confounded by the presence of unrelated trends in both the brain and the overlying scalp. A proposed strategy for reducing hemodynamic noise has been to record “scalp only” trends simultaneously via a second shorter-separation detector (~5 mm rather than ~30 mm) and perform a subtraction (C-NIRS, for “corrected near-infrared spectroscopy”). To compare the single- and dual-detector strategies, a 21-volunteer study of visual stimulation responses (6 stimulation blocks and 8 recording channels per measurement run) has been conducted. Activation-flagged channels were defined based upon (a) the significance (p-value) of the average rise in oxyhemoglobin concentration and (b) the average signal-to-noise over 6 stimulation epochs. At reasonable thresholds (p 1), the C-NIRS method increased the number of activation-flagged channels from 47 to 66, an increase of 40%, adding 24 channels and eliminating only 5. Of the 71 channels that were activation-flagged by at least one modality, the C-NIRS time series exhibited more significant oxyhemoglobin rise in 80% of such channels, and better signal-to-noise in 73%. In addition, single-subject C-NIRS stimulus responses were more consistent than NIRS over the six stimulation epochs, with significantly lower coefficients of variation in both amplitude and latency (i.e. time between stimulus onset and maximum hemoglobin rise). These results demonstrate that two-detector C-NIRS provides a straightforward way of (a) removing hemodynamic interference from NIRS data, (b) increasing the detection rate of cerebrally-unique responses, and (c) improving the quality of those recorded responses. Parallel insights regarding deoxyhemoglobin trends could not be drawn from this data set but should be attainable in future studies with higher signal to noise ratios.

A key design parameter in spatially offset Raman spectroscopy (SORS) is the choice of offset distance between the illumination and collection areas. To investigate this choice, we performed SORS measurements on a simple two-layer chemical phantom. We show that while the SORS ratio, or the ratio of signal from the bottom layer to the top layer, monotonically increases with spatial offset, the signal-to-noise ratio (SNR) does not. Specifically, we show that there exists a specific spatial offset that yields the best SNR for signal originating in the bottom layer of a two-layer sample. We also show that this SNR-optimal offset depends upon the strength of the particular Raman band. This work presents the considerations that should be taken into account when designing optical probes for use in SORS.

Raman scattering from aqueous liquids can be collected with high efficiency by enclosing the liquid within a suitable waveguide, as several groups have reported. Here, we present a quantitative model that predicts the relative strength of signals collected from (a) a tubular waveguide and (b) a flat-walled cuvette. Experimental measurements of Raman scattering from aqueous ethanol are made using two geometries, a Teflon®-AF waveguide and a standard quartz cuvette. The model correctly predicts the enhancements in several ethanol Raman bands provided by the waveguide geometry. This model should be useful in aligning and characterizing liquid core waveguides, whose manufacture is still undergoing refinements. In particular, the model shows that absorption and scattering losses affect the enhancement factor in different ways.

We present an analytical formula that estimates the uncertainty in concentrations predicted by linear multivariate calibration, particularly partial least-squares (PLS). We emphasize the analysis of spectroscopic data. The derivation addresses the important limit in which calibration error is negligible in comparison to noise in the prediction spectra. The formula is expressed in terms of standard PLS calibration parameters and the amplitude of spectral noise; it is therefore straightforward to evaluate. To test the formula, we performed PLS analysis upon simulated spectra and upon experimental Raman spectra of dissolved biological analytes in water. In each instance, the root-mean-squared error of prediction was compared to the estimate from the formula. Accurate uncertainty estimates were obtained in cases where calibration noise was lower than prediction noise, and surprisingly good estimates were obtained even when the noise levels were equal. By comparing measured and estimated uncertainties, we assessed the robustness of each PLS calibration model. The scaling of prediction uncertainty with the spectral signal-to-noise ratio is also discussed.

The observation of surface-enhanced Raman scatterings (SERS) from CO2 molecules dissolved in aqueous solutions of silver and gold colloids measured with 850 nm near-IR excitation is reported. Different types of surface enhancement and surface-enhanced Raman spectra were observed. The SERS spectrum of CO2 on colloidal gold is in good agreement with the spectrum of CO2 dissolved in water. Two different types of SERS spectra were found for CO2 on colloidal silver. They can be assigned to physisorbed and/or weakly chemisorbed CO2 molecules and to strongly bonded CO2 - negatively charged surface radicals, respectively. The enhancement factor for the stretching mode of carbon dioxide is estimated to be of the order of 102−104, depending on the kinds of metal and types of adsorption, which demonstrates that SERS on colloidal silver or gold particles in solution offers possibilities for detecting CO2 dissolved in liquids at low concentrations.

Near-infrared Raman spectra of several gases dissolved in an aqueous medium have been acquired and analyzed for the first time. Spectra of dissolved and gaseous CO2, SO2, N2O, dimethyl ether, and O2 are presented and compared. Raman-forbidden bands in the spectrum of gaseous dimethyl ether are observed in the dissolved spectrum; this result can be explained by relaxed selection rules due to lowered symmetry. Raman scattering enhancements in the dissolved phase are measured and shown to compare well with a theoretical prediction accounting for internal field enhancements in water. Dissolved CO2 is measured quantitatively at concentrations from 0 to 250 Torr with the use of the method of partial least-squares, with an average prediction error of 12 Torr.

Near-infrared spectroscopy (NIRS) sensing of cerebral hemodynamics can be made more brain-specific by regressing against superficially-sensitive channels. Different distances and single channels versus global averages are discussed.

Near-infrared spectroscopy is a non-invasive diffuse optical-imaging technique for estimating the metabolic demand in local (1 cm) regions of cortex. Activations in visual cortex of human adults and infants are consistent with known projections from the two hemi-fields.

We describe a compound parabolic concentrator (CPC)-based probe for enhanced signal collection in the spectroscopy of biological tissues. Theoretical considerations governing signal enhancement compared with conventional collection methods are given. A ray-tracing program was used to analyze the throughput of CPC's with shape deviations and surface imperfections. A modified CPC shape with 99% throughput was discovered. A 4.4-mm-long CPC was manufactured and incorporated into an optical fiber-based near-infrared Raman spectrometer system. For human tissue samples, light collection was enhanced by a factor of 7 compared with collection with 0.29-NA optical fibers.

Accurate concentration measurements of glucose, lactic acid, and creatinine in saline solution have been achieved with near-IR Raman spectroscopy and a partial least-squares analysis. The Raman spectra were acquired remotely through optical fibers. A root-mean-squared prediction error of 1.2 mM for glucose concentration was achieved in 100 s. Concentrations of other analytes were predicted with similar accuracy.

A technique for measuring broadband near-infrared absorption spectra of turbid media that uses a combination of frequency-domain (FD) and steady-state (SS) reflectance methods is presented. Most of the wavelength coverage is provided by a white-light SS measurement, whereas the FD data are acquired at a few selected wavelengths. Coefficients of absorption (μa) and reduced scattering (μ‘s) derived from the FD data are used to calibrate the intensity of the SS measurements and to estimate μ‘s at all wavelengths in the spectral window of interest. After these steps are performed, one can determine ma by comparing the SS reflectance values with the predictions of diffusion theory, wavelength by wavelength. Absorption spectra of a turbid phantom and of human breast tissue in vivo, derived with the combined SSFD technique, agree well with expected reference values. All measurements can be performed at a single source-detector separation distance, reducing the variations in sampling volume that exist in multidistance methods. The technique uses relatively inexpensive light sources and detectors and is easily implemented on an existing multiwavelength FD system. © 2000 Optical Society of America.

Raman spectroscopy studies a target chemically, while angularly-resolved elastic light scattering probes morphology. We have combined these modalities on a microscopic platform. The optical system and data from beads and immune cells are discussed.

Near-infrared Raman spectroscopy has been used for species identification of pure microbial specimens for more than a decade. More recently, this optical method has been extended to the analysis of specimens containing multiple species. In this report, we demonstrate rapid, reagent-free quantitative analysis of a simplified model of oral plaque containing three oral bacteria species, S. mutans, S. sanguis, and S. gordonii, using near-infrared Raman spectroscopy. Raman spectra were acquired from bacterial mixtures in 200 seconds. A prediction model was calibrated by the partial least squares method and validated by additional samples. On a scale from 0 to 1, relative fractions of each species could be predicted with a root mean square error of 0.07. These results suggest that near-infrared Raman spectroscopy is potentially useful in quantification of microbial mixtures in general and oral plaques in particular.

Raman spectra were obtained from single mouse tumor cells before and after treatment with photodynamic therapy. We are presently investigating pure chemicals to illuminate differences observed in the spectra of treated and untreated cells.

This PDF file contains the editorial “Infrared and Raman Spectroscopy” for JBO Vol. 10 Issue 03

We propose a method to isolate absorption trends confined to the lower layer of a two-layer turbid medium, as is desired in near-infrared spectroscopy (NIRS) of cerebral hemodynamics. Several two-layer Monte Carlo simulations of NIRS time series were generated using a physiologically relevant range of optical properties and varying the absorption coefficients due to bottom-layer, top-layer, and/or global fluctuations. Initial results showed that by measuring absorption trends at two source-detector separations and performing a least-squares fit of one to the other, processed signals strongly resemble the simulated bottom-layer absorption properties. Through this approach, it was demonstrated that fitting coefficients can be estimated within less than +/- 2% of the ideal value without any a priori knowledge of the optical properties present in the model. An analytical approximation for the least-squares coefficient provides physical insight into the nature of errors and suggests ways to reduce them.

In biomedical optics, the specimens usually have a "Goldilocks" quality: some structures are much larger than an optical wavelength, some are much smaller, and some are just about the same size. Consequently, biological absorption, emission, and scattering properties can have strong wavelength and angular dependences. This tutorial will explain the nature of the dependences and survey some of the ways they are exploited for biomedical purposes.Full-text article is not available.

Spectroscopic methods of urinalysis offer several advantages over chemical methods, including less sample contact and higher information content. In particular, urine creatinine has been the subject of several spectroscopic studies. We report the first use of Raman spectroscopy to measure creatinine concentrations in unaltered urine samples from a multipatient population. Using near-infrared excitation and a hybrid linear analysis calibration method, a root mean squared error of cross-validation (RMSECV) of 4.9 mg/dL was obtained. The error in the reference chemical method was 1.1 mg/dL. This result shows that the Raman spectroscopy can measure creatinine at clinical levels even in the presence of patient-to-patient variations. Because most assays in urine require creatinine concentration in order to correct for fluctuations in water content, measurement of creatinine is the first step towards more extensive Raman-based urinalysis.

Raman spectroscopy has been employed to measure the varying concentrations of two oral bacteria in simple mixtures. Evaporated droplets of centrifuged mixtures of Streptococcus sanguis and Streptococcus mutans were analyzed via Raman microspectroscopy. The concentration of s. sanguis was determined based upon the measured Raman spectrum, using partial least squares cross-validation, with an r2 value of 0.98.

Near-infrared (NIR) diffuse optical spectroscopy and imaging may enhance existing technologies for breast cancer screening, diagnosis, and treatment. NIR techniques are based on quantitative measurements of functional contrast between healthy and diseased tissue. In this study we measured the spectral dependence of tissue absorption (μa) and reduced scattering (μ's) in the breasts of 30 healthy women and one woman with a fibroadenoma using a seven-wavelength frequency-domain photon migration probe. Subjects included pre- and postmenopausal women between the ages of 18 and 64. Multi-spectral measurements were used along with a four-component fit to determine the concentrations of de-oxy and oxyhemoglobin, water and lipids in breast. The scattering spectral shape was also quantified. Our measurements demonstrate that the measured concentrations of NIR analytes correlate well with known breast physiology. Although the tissue scattering at a single wavelength was found to have little value as a functional parameter, the dependence of the scattering on wavelength provided key insights into breast composition and physiology. Lipids and scattering spectra in the breast were found to increase and decrease, respectively, with increasing body mass index. Simple calculations are also provided to demonstrate potential penalties from ignoring the contributions of water and lipids in breast measurements. Finally, water is shown to be a possible indicator for detecting a fibroadenoma, whereas the hemoglobin saturation was found to be a poor indicator. Multi-spectral measurements, compared to measurements restricted to one or two wavelengths, provide additional information that may be useful in managing breast disease. © 2002 Society of Photo-Optical Instrumentation Engineers.

In functional near-infrared spectroscopy (fNIRS) of human cerebral hemodynamics, dedicated surface-sensitive recording channels are useful for regressing out background hemodynamics and isolating activation-specific responses. A wide variety of source-detector separations have been utilized for this purpose. Here, we report a direct comparison of regression performance between two extremes of the reported range, 13 and 6 mm. Measurements of visual stimulation response (flickering radial checkerboard) were obtained from nine adults using a standard commercial source-detector grid with 13-mm diagonals, into which three extra detector fibers were placed to provide 6-mm channels at certain locations. When the NIRS recordings (17 total trials) were processed, the contrast-to-noise ratio was significantly higher with 6-mm regression channels than with 13 mm. The advantage could be due in part to the undesired sensing of brain activity by the 13-mm channels. We suggest that shorter distances be considered for optimal removal of superficial hemodynamics in NIRS signals from the adult brain.

Raman spectroscopy has advantages over infrared absorption spectroscopy. Combined with a novel multivariate technique, hybrid linear analysis (HLA), low prediction error is expected.A near-infrared (NIR) light source excited Raman signals, and a charge coupled device (CCD) camera was used to collect the signal. Samples were collected from 69 individuals for 7 weeks. The standard multivariate calibration technique, partial least squares (PLS) and HLA were both used to analyze the collected spectra. A Clarke error grid was used to evaluate the usefulness of the glucose measurement in serum.The root mean squared error of prediction (RMSEP) for glucose in serum obtained with PLS is 21 mg/dL, and the RMSEP obtained with HLA is 17 mg/dL. In whole blood, the PLS RMSEP for glucose was 79 mg/dL, and HLA predictions had an RMSEP of 63 mg/dL.The measurement technique was robust over the 7-week period. HLA was shown to generate a lower prediction error than PLS. The predictions by both PLS and HLA were clinically acceptable. The result with whole blood requires further improvement.

A technique for measuring broadband near-infrared absorption spectra of turbid media is presented using a combination of frequency-domain (FD) and steady-state (SS) reflectance methods. Most of the wavelength coverage is provided by a white-light SS measurement, while the FD data are acquired at a few selected wavelengths. Coefficients of absorption ((mu) a) and reduced scattering ((mu) s') derived from the FD data are used to intensity-calibrate the SS measurements and to estimate (mu) s' at all wavelengths in the spectral window of interest. After these steps are performed, (mu) a can be determined by comparing the SS reflectance values to the predictions of diffusion theory, wavelength by wavelength. We present an application of this method to breast tumor characterization. A case study of a fibroadenoma is shown, where different absorption spectra were found between the normal and the tumor sides.© (2001) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Near infrared diffuse optical spectroscopy and imaging may enhance existing technologies for breast cancer screening, diagnosis, and treatment. NIR spectroscopy yields quantitative functional information that cannot be obtained with other non-invasive radiological techniques. In this study we focused upon the origins of this contrast in healthy breast, especially from water and lipids.

Rationale and Objectives Near-infrared (NIR) diffuse optical spectroscopy and imaging may enhance existing technologies for breast cancer screening, diagnosis, and treatment. NIR techniques are based on sensitive, quantitative measurements of functional contrast between healthy and diseased tissue. In this study, the authors quantified the origins of this contrast in healthy breasts. Materials and Methods A seven-wavelength frequency-domain photon migration probe was used to perform noninvasive NIR measurements in the breasts of 28 healthy women, both pre- and postmenopausal, aged 18–64 years. A diffusive model of light transport quantified oxygenated and deoxygenated hemoglobin, water, and lipid by their absorption signatures. Changes in the measured light-scattering spectra were quantified by means of a “scatter power” parameter. Results Substantial quantitative differences were observed in both absorption and scattering spectra of breast as a function of subject age. These physiologic changes were consistent with long-term hormone-dependent transformations that occur in breast. Instrument response was not adversely affected by subject age or menopausal status. Conclusion These measurements provide new insight into endogenous optical absorption and scattering contrast mechanisms and have important implications for the development of optical mammography. NIR spectroscopy yields quantitative functional information that cannot be obtained with other noninvasive radiologic techniques.

A method was described for using steady-state and frequency-domain reflectance measurements to obtain broad wavelength quantitative data with deep tissue penetration. Fundamental information on tissue biochemistry and structure was provided using the wavelength-dependence of absorption and scattering parameters. Results showed that total hemoglobin content, water and lipid percentage can be measured using this technique.

We report the determinations of glucose concentrations in human whole blood samples made using near-infrared Raman spectroscopy. Raman spectra of blood samples with above-physiological levels of glucose were acquired for 5 min through the wall of a cuvette via fiber optics. Partial least squares analysis was used to predict glucose concentrations in the samples. A root mean squared prediction error of 3.6 mM glucose was achieved with a correlation coefficient of 0.99 between reference and predicted values. This result is the first step in evaluating the potential of near-infrared Raman spectroscopy to perform blood glucose measurement with clinical accuracy. The technique is capable of measuring the concentration of other Raman-active blood constituents; as an example, bicarbonate was also measured. The method could eventually be useful for direct measurement of tissue analytes.

The use of Raman spectroscopy for biomedical applications requires overcoming the obstacle of the broad background that is also generated by biological samples. This background, which is often largely attributed to fluorescence, is frequently orders of magnitude greater than the Raman signal and needs to be removed in order to use Raman spectra in sample analysis. Several methods have been proposed for removing fluorescent signal, both instrumental and computational. Of the computational methods, polynomial fitting has become increasingly popular. Typically, a polynomial of approximately fifth order is used in the fitting. This method alone is not always capable of fitting some more tightly featured spectra that may be present in data, potentially coming from a contaminant in the sample itself or from the experimental design. If this signal is present in varying amounts, the polynomial background removal method can leave the residual spectra with non-uniform artifacts that hinder classification results. If a reference spectrum can be obtained for this interfering signal, however, it can be incorporated into the polynomial fit and removed separately. An automated method for the removal of broad and/or moderately featured background signal is described. In addition to simulations, the method has been applied to spectra from biofilms of Streptococcus mutans.

We report measurements of chemical concentrations in clinical blood serum and urine samples using liquid-core optical fiber (LCOF) Raman spectroscopy to increase the collected signal strength. Both Raman and absorption spectra were acquired in the near-infrared region using the LCOF geometry. Spectra of 71 blood serum and 61 urine samples were regressed via partial least squares against reference analyzer values. Significant correlation was found between predicted and reference concentrations for 13 chemicals. Using absorption data to normalize the LCOF enhancement made the results more accurate. The experimental geometry is well suited for high-volume and automated chemical analysis of clear biofluids.

The enhancement of a dissolved chemical's Raman scattering by a liquid-core optical fiber (LCOF) geometry is absorption dependent. This dependence leads to a disruption of the usual linear correlation between chemical concentration and Raman peak area. To recover the linearity, we augmented a standard LCOF Raman spectroscopy system with spectrophotometric capabilities, permitting sequential measurements of Raman and absorption spectra within the LCOF. Measurements of samples with identical Raman-scatterer concentrations but different absorption coefficients are described. Using the absorption values, we reduced variations in the measured Raman intensities from 60% to less than 1%. This correction method should be important for LCOF-based Raman spectroscopy of sample sets with variable absorption coefficients, such as urine and blood serum from multiple patients.