Noninvasive Glucose Sensing In Vivo

Blood glucose monitoring is an essential aspect of disease management for individuals with diabetes. Unfortunately, traditional methods require collecting a blood sample and thus are invasive and inconvenient. Recent developments in minimally invasive continuous glucose monitors have provided a more convenient alternative for people with diabetes to track their glucose levels 24/7. Despite this progress, many challenges remain to establish a noninvasive monitoring technique that works accurately and reliably in the wild. This review encompasses the current advancements in noninvasive glucose sensing technology in vivo, delves into the common challenges faced by these systems, and offers an insightful outlook on existing and future solutions.

Spectral Methods for Response Enhancement of Microwave Resonant Sensors in Continuous Non-Invasive Blood Glucose Monitoring

In this paper, the performance of three recent algorithms for the frequency-response enhancement of microwave resonant sensors are compared. The first one, a single-step algorithm, is based on a couple of direct-inverse Fourier transforms, giving a densely sampled response as a result. The second algorithm exploits an iterative procedure to progressively restricts the frequency response. The final one is based on the super-resolution MUSIC algorithm. The comparison is carried out through a Monte Carlo analysis. In particular, synthetic signals are firstly exploited to mimic the frequency response of a resonant microwave sensor. Then, experimental data collected from water-glucose solutions are adopted as validation test for potential applications in noninvasive blood-glucose monitoring.

Noninvasive Blood Glucose Concentration Measurement Based on Conservation of Energy Metabolism and Machine Learning

Blood glucose (BG) concentration monitoring is essential for controlling complications arising from diabetes, as well as digital management of the disease. At present, finger-prick glucometers are widely used to measure BG concentrations. In consideration of the challenges of invasive BG concentration measurements involving pain, risk of infection, expense, and inconvenience, we propose a noninvasive BG concentration detection method based on the conservation of energy metabolism. In this study, a multisensor integrated detection probe was designed and manufactured by 3D-printing technology to be worn on the wrist. Two machine-learning algorithms were also applied to establish the regression model for predicting BG concentrations. The results showed that the back-propagation neural network model produced better performance than the multivariate polynomial regression model, with a mean absolute relative difference and correlation coefficient of 5.453% and 0.936, respectively. Here, about 98.413% of the predicted values were within zone A of the Clarke error grid. The above results proved the potential of our method and device for noninvasive glucose concentration detection from the human wrist.

Enhancing the Accuracy of Non-Invasive Glucose Sensing in Aqueous Solutions Using Combined Millimeter Wave and Near Infrared Transmission

We reported measurement results relating to non-invasive glucose sensing using a novel multiwavelength approach that combines radio frequency and near infrared signals in transmission through aqueous glucose-loaded solutions. Data were collected simultaneously in the 37–39 GHz and 900–1800 nm electromagnetic bands. We successfully detected changes in the glucose solutions with varying glucose concentrations between 80 and 5000 mg/dl. The measurements showed for the first time that, compared to single modality systems, greater accuracy on glucose level prediction can be achieved when combining transmission data from these distinct electromagnetic bands, boosted by machine learning algorithms.

Rapid and simultaneous analysis of direct and indirect bilirubin indicators in serum through reagent-free visible-near-infrared spectroscopy combined with chemometrics

Indirect (IBil), direct (DBil) and total (TBil) bilirubin are important clinical indicators of hepatobiliary diseases, which require rapid detection in diagnosis and treatment. IBil and DBil have a structural relationship with several macromolecules in hepatobiliary metabolism. Here, the rapid analysis models for bilirubin indicators using serum visible-near-infrared (Vis-NIR) spectroscopy were established. Norris derivative filter with optimisation was used for spectral pretreatment; the optimal parameters (derivative order, number of smoothing points, number of differential gaps) were (2, 15, 9) for IBil; (2, 13, 9) for DBil, respectively. Equidistant combination-partial least squares (EC-PLS) was used for large-scale wavelength screening. Wavelength step-by-step phase-out PLS (WSP-PLS) was used for secondary wavelength optimisation. The wavelength models of the optimal EC-WSP-PLS for IBil and DBil included 11 and 18 wavelengths, respectively. In independent validation, the root-mean-square errors and correlation coefficient for prediction (SEP, R_P), and ratio of performance-to-deviation (RPD) were 0.90 μmol L^-1, 0.975, and 4.4 for IBil; 0.71 μmol L^-1, 0.955, and 3.3 for DBil, respectively. TBil was subjected to spectral analysis, and the summation of the prediction values of IBil and DBil was compared. The latter was obviously better, and SEP, R_P, RPD were 0.82 μmol L^-1, 0.990, 7.1, respectively. The results for IBil, DBil and TBil indicated high correlation, low error and good overall prediction ability and confirmed the feasibility of the simultaneous analysis of bilirubin indicators through reagent-free serum Vis-NIR spectroscopy. The proposed method is crucial for the rapid screening of large populations and the treatment of hepatobiliary diseases.

Spectral noise-to-signal ratio priority method with application for visible and near-infrared analysis of whole blood viscosity

Whole blood viscosity (WBV) is a group of important clinical indicators of cardio-cerebral vascular diseases. Existing detection methods for WBV are complex, making them inconvenient for large population screening. Blood viscosity is closely related to the deformability and aggregation of erythrocytes, which are associated with haemoglobin. Haemoglobin has obvious near-infrared (NIR) spectral absorption. Scattering occurs when NIR light enters a viscous blood sample, and its scattering degree is correlated with blood viscosity. Based on repeated spectral measurements and spectral similarity, spectral noise-to-signal ratio (NSR) was proposed to quantify the spectral scattering effect in the blood sample. A novel selection method of piecewise-continuous wavelengths, named NSR priority-partial least squares (NSRP-PLS), was proposed and applied for visible-NIR quantitative analysis of WBV with high, medium and low shear rates [WBV(H), WBV(M), WBV(L)]. Modelling was separately performed by gender to allow for systematic gender differences in blood viscosity. For the NIR-predicted and clinically measured values of the three WBV indicators in independent validation, the root mean square errors for prediction (SEP) were 0.498, 0.222 and 0.193 (mPa·s), respectively. And the correlation coefficients (R_P) were 0.927, 0.934 and 0.927, respectively. Compared with the three current well-performing methods (MW-PLS, CARS-PLS and SPA-PLS), the proposed NSRP-PLS method achieved better predictive accuracy. Results indicated that visible-NIR spectroscopy combined with the NSRP-PLS method can be used for the quantitative analysis of WBV. The proposed analytical method is rapid, reagent-free and is scientific and meaningful for cardio-cerebral vascular diseases screening in large populations.

CHEMOMETRIC ANALYSIS OF DIFFUSE REFLECTANCE SPECTRAL DATA USING SINGULAR VALUE DECOMPOSITION FOR BLOOD GLUCOSE DETECTION

Diabetes mellitus is a metabolic disorder that affects the production or usage of insulin by the body. Diabetes prevails in the body as a long-term condition which causes several other disorders if left unnoticed. Proper control of Diabetes needs continuous monitoring. The current measurement technique is invasive in nature and requires the withdrawal of blood from the body. Periodic quantification of blood glucose leads to pain and discomfort for the subject. This paper presents a non-invasive glucose measuring system using near-infrared diffuse reflectance spectroscopy (DRS). This work attempts to determine the blood glucose value from the diffuse reflected spectra in the NIR region. The study is executed with the spectral signatures of 33 diabetic subjects collected non-invasively using diffuse reflectance spectrometer from a diabetic centre. Blood glucose level of the same subjects are also recorded using the clinical method. The spectral information is subjected to standard normal variate (SNV) preprocessing method to remove baseline drift and then dimension reduction using singular value decomposition (SVD) is applied to the preprocessed data. The extracted singular values when compared with the clinically measured blood glucose is found to have a proportional relationship. The proposed study using singular value decomposition paves us the way for estimating the blood glucose value non-invasively with the obtained set of clinical blood glucose and the corresponding singular value table as a standard reference set.

Glucose sensing in oral mucosa simulating phantom using differential absorption based frequency domain low-coherence interferometry

The superluminescent diode based differential absorption frequency domain low-coherence interferometry (FD-DALCI) technique is proposed and demonstrated for sensing physiological concentrations of glucose (0-250 mg/dl) in oral mucosa simulating phantoms (intralipid of concentrations 0.25-0.50%) with wavelengths at 1589 and 1310 nm. The proposed technique allows simultaneous measurements of refractive index based spectral shift and estimation of physiological concentration of glucose in intralipid with scattering characteristics using the differential absorption approach. The sensitivity of the glucose concentration obtained by spectral shift measurement was ≈0.016  nm/(mg/dl), irrespective of the intralipid concentration. The resolution of the glucose level was estimated to be ≈15  mg/dl in 0.25% intralipid and ≈19  mg/dl in 0.5% intralipid using the FD-DALCI technique.

Mid-Infrared Photoacoustic Detection of Glucose in Human Skin: Towards Non-Invasive Diagnostics

Diabetes mellitus is a widespread metabolic disease without cure. Great efforts are being made to develop a non-invasive monitoring of the blood glucose level. Various attempts have been made, including a number of non-optical approaches as well as optical techniques involving visible, near- and mid-infrared light. However, no true breakthrough has been achieved so far, i.e., there is no fully non-invasive monitoring device available. Here we present a new study based on mid-infrared spectroscopy and photoacoustic detection. We employ two setups, one with a fiber-coupled photoacoustic (PA) cell and a tunable quantum cascade laser (QCL), and a second setup with two QCLs at different wavelengths combined with PA detection. In both cases, the PA cells are in direct skin contact. The performance is tested with an oral glucose tolerance test. While the first setup often gives reasonable qualitative agreement with ordinary invasive blood glucose measurements, the dual-wavelength approach yields a considerably improved stability and an uncertainty of only ±30 mg/dL of the blood glucose concentration level at a confidence level of 90%. This result is achieved without advanced data treatment such as principal component analysis involving extended wavelength ranges.

Near-infrared spectroscopy for medical applications: Current status and future perspectives

The near-infrared radiation (NIR) window, also known as the "optical window" or "therapeutic window", is the range of wavelengths that has the maximum depth of penetration in tissue. Indeed, because NIR is minimally absorbed by water and hemoglobin, spectra readings can be easily collected from the body surface. Recent reports have shown the potential of NIR spectroscopy in various medical applications, including functional analysis of the brain and other tissues, as well as an analytical tool for diagnosing diseases. The broad applicability of NIR spectroscopy facilitates the diagnosis and therapy of diseases as well as elucidating their pathophysiology. This review introduces recent advances and describes new studies in NIR to demonstrate potential clinical applications of NIR spectroscopy.

Hollow optical-fiber based infrared spectroscopy for measurement of blood glucose level by using multi-reflection prism

A mid-infrared attenuated total reflection (ATR) spectroscopy system employing hollow optical fibers and a trapezoidal multi-reflection ATR prism has been developed to measure blood glucose levels. Using a multi-reflection prism brought about higher sensitivity, and the flat and wide contact surface of the prism resulted in higher measurement reproducibility. An analysis of in vivo measurements of human inner lip mucosa revealed clear signatures of glucose in the difference spectra between ones taken during the fasting state and ones taken after ingestion of glucose solutions. A calibration plot based on the absorption peak at 1155 cm(-1) that originates from the pyranose ring structure of glucose gave measurement errors less than 20%.

Near-Infrared (NIR) Spectroscopy of Synthetic Hydroxyapatites and Human Dental Tissues

Near-infrared spectroscopy (NIR) was used to analyze synthetic hydroxyapatite calcined at various temperatures, synthetic carbonated hydroxyapatite, and human hard dental tissues (enamel and dentin). The NIR bands of those materials in the combination, first-overtone, and second-overtone spectral regions were assigned and evaluated for structural characterization. They were attributed to adsorbed and structural water, structural hydroxyl (OH) groups and surface P-OH groups. The NIR spectral features were quantitatively discussed in view of proton solid-state magic-angle spinning nuclear magnetic resonance ((1)H MAS NMR) results. We conclude that the NIR spectra of apatites are useful in the structural characterization of synthetic and biogenic apatites.

Design and characterization of protein films for modeling near-infrared spectra of human tissue

Films of keratin and collagen proteins are fabricated for use in implementing a laboratory simulation of noninvasive glucose measurements based on transmission near-infrared spectroscopy of human tissue.

First step toward near-infrared continuous glucose monitoring: in vivo evaluation of antibody coupled biomaterials

Continuous glucose monitoring (CGM) is crucial in diabetic care. Long-term CGM systems however require an accurate sensor as well as a suitable measuring environment. Since large intravenous sensors are not feasible, measuring inside the interstitial fluid is considered the best alternative. This option, unfortunately, has the drawback of a lag time with blood glucose values. A good strategy to circumvent this is to enhance tissue integration and enrich the peri-implant vasculature. Implants of different optically transparent biomaterials (poly(methyl-methacrylate) [PMMA] and poly(dimethylsiloxane) [PDMS]) - enabling glucose monitoring in the near-infrared (NIR) spectrum - were surface-treated and subsequently implanted in goats at various implantation sites for up to 3 months. The overall in vivo biocompatibility, tissue integration, and vascularization at close proximity of the surfaces of these materials were assessed. Histological screening showed similar tissue reactions independent of the implantation site. No significant inflammation reaction was observed. Tissue integration and vascularization correlated, to some extent, with the biomaterial composition. A modification strategy, in which a vascular endothelial-cadherin antibody was coupled to the biomaterials surface through a dopamine layer, showed significantly enhanced vascularization 3 months after subcutaneous implantation. Our results suggest that the developed strategy enables the creation of tissue interactive NIR transparent packaging materials, opening the possibility of continuous glucose monitoring.

Effects of optical clearing agents on noninvasive blood glucose monitoring with optical coherence tomography: a pilot study

Recently, the capability of optical coherence tomography (OCT) has been demonstrated for noninvasive blood glucose monitoring. In this work, we investigate the administration of chemical agents onto human skin tissue to increase the transparency of the surface of the skin, as a means of improving the capability of OCT imaging for clinically relevant applications. Eight groups of experiments were proposed, in which different optical clearing agents (OCA) were used. The results indicate that, when properly used, some OCAs perform well in promoting the capability of OCT for noninvasive blood glucose monitoring. Among the four kinds of OCA we used, 50%  v/v glycerol solute turns out to be the best enhancer. Compared with the results of the experiments in which no OCA was used, when 50% glycerol was applied onto the human skin topically, the correlation coefficient between the OCT signal slope (OCTSS) and blood glucose concentration (BGC) was improved by 7.1% on average, and the lag time between changes in the OCTSS and BGC was cut by 8 min on average. The results of 10  w/v mannitol were also good, but not as pronounced.

Glucose sensing in human epidermis using mid-infrared photoacoustic detection

No reliable non-invasive glucose monitoring devices are currently available. We implemented a mid-infrared (MIR) photoacoustic (PA) setup to track glucose in vitro in deep epidermal layers, which represents a significant step towards non-invasive in vivo glucose measurements using MIR light. An external-cavity quantum-cascade laser (1010-1095 cm(-1)) and a PA cell of only 78 mm(3) volume were employed to monitor glucose in epidermal skin. Skin samples are characterized by a high water content. Such samples investigated with an open-ended PA cell lead to varying conditions in the PA chamber (i.e., change of light absorption or relative humidity) and cause unstable signals. To circumvent variations in relative humidity and possible water condensation, the PA chamber was constantly ventilated by a 10 sccm N(2) flow. By bringing the epidermal skin samples in contact with aqueous glucose solutions with different concentrations (i.e., 0.1-10 g/dl), the glucose concentration in the skin sample was varied through passive diffusion. The achieved detection limit for glucose in epidermal skin is 100 mg/dl (SNR=1). Although this lies within the human physiological range (30-500 mg/dl) further improvements are necessary to non-invasively monitor glucose levels of diabetes patients. Furthermore spectra of epidermal tissue with and without glucose content have been recorded with the tunable quantum-cascade laser, indicating that epidermal constituents do not impair glucose detection.

Instrument for near infrared emission spectroscopic probing of human fingertips in vivo

We present instrumentation for probing of volar side fingertip capillary beds with free space coupled near infrared light while collecting Raman, Rayleigh, and Mie scattered light as well as fluorescence. Fingertip skin capillary beds are highly vascularized relative to other tissues and present a desirable target for noninvasive probing of blood. But human hands and fingers in particular are also highly idiosyncratic body parts requiring specific apparatus to allow careful and methodical spectroscopic probing. The apparatus includes means for precise and reproducible placement of the tissues relative to the optical aperture. Appropriate means are provided for applying and maintaining pressure to keep surface tissues immobile during experiments while obtaining the desired blood content and flow. Soft matter, e.g., skin, extrudes into the aperture in response to any applied pressure, e.g., to keep the tissue in registration with the optical system, so the position, contact area, pressure, and force are continuously measured and recorded to produce feedback for an actuator applying force and to discern the compliance of the test subject. The compliance strongly affects the reliability of the measurement and human factors must be adequately managed in the case of in vivo probing. The apparatus produces reproducible observations and measurements that allow consistent probing of the tissues of a wide range of skin types.

Microneedle-based automated therapy for diabetes mellitus

This article discusses the use of microneedles in automated diabetes therapy systems. Advanced bioengineered systems have the potential to close the loop between diagnostic and therapeutic elements of diabetes treatment, thus constituting a "smart" system. Prevalent insulin therapies, and most glucose sensing techniques, involve the transfer of physical entities through the skin. Micromachined needles (microneedles) can achieve this in a noninvasive or minimally invasive manner while contributing various other technological merits. The dynamics of autonomous diabetes therapy systems include highly complex interdependencies between the various physical and biological entities involved, thus warranting multidisciplinary research initiatives. The iterative development of a noninvasive, bioengineered interface such as microneedles necessitates a better understanding of the human skin, its molecular architecture as a polymer film, and its role as a functional biological unit. This review addresses application-specific requirements of a microneedle-based interface system specifically for autonomous diabetes therapy. Key design issues and related parametric interdependencies specific to this application are discussed.

Progress toward an in vivo surface-enhanced Raman spectroscopy glucose sensor

BACKGROUND

In this report, we detail our current work towards developing a surface-enhanced Raman spectroscopy (SERS) based sensor for in vivo glucose detection. Despite years of innovations in the development of blood glucose monitors, there remains a need for accurate continuous glucose sensors to provide care to rising numbers of diagnosed diabetes patients and mitigate secondary health complications associated with this metabolic disorder.

METHODS

SERS is a highly specific and sensitive optical technique suitable for direct detection of glucose. The SERS effect is highly distance dependent, thus the glucose molecules need to be within a few nanometers or adsorbed to an SERS-active surface. In our sensor, this is achieved with a self-assembled monolayer (SAM) that facilitates reversible interactions between glucose molecules and the surface. The amount of glucose near the surface is proportional to its concentration in the surrounding environment.

RESULTS

We determined that the SAM-functionalized surface is stable for at least 10 days and provides rapid, reversible partitioning. In vitro experiments in bovine plasma as well as in vivo experiments in rats demonstrated quantitative detection.

CONCLUSIONS

We show successful use of the SERS glucose sensor in rats, making it the first in vivo SERS sensor. Furthermore, we demonstrate free space transdermal detection of a SERS signal through the rat's skin as an initial step toward developing a transcutaneous sensor.

Current development in non-invasive glucose monitoring

Painless control of blood glycemic levels could improve life quality of diabetes patients, enabling a better regulation of hyper- and hypoglycaemia episodes and thereby avoiding physiological complications. Although research groups have been trying for decades to separate non-invasive glucose information from interference compounds, none of the available commercial devices offers enough precision to replace lancet approaches. Many reviews have already been published on this topic, but the great amount of information available and the fast development of technologies require a continuous update in the research status. Besides the description of current in-vivo methods and the analysis of devices available commercially, one also explains treatment algorithms useful for multivariate analysis.

Comparison of performance of partial least squares regression, secured principal component regression, and modified secured principal component regression for determination of human serum albumin, gamma-globulin and glucose in buffer solutions and in vivo blood glucose quantification by near-infrared spectroscopy

The performances of three multivariate analysis methods--partial least squares (PLS) regression, secured principal component regression (sPCR) and modified secured principal component regression (msPCR)--are compared and tested for the determination of human serum albumin (HSA), gamma-globulin, and glucose in phosphate buffer solutions and blood glucose quantification by near-infrared (NIR) spectroscopy. Results from the application of PLS, sPCR and msPCR are presented, showing that the three methods can determine the concentrations of HSA, gamma-globulin and glucose in phosphate buffer solutions almost equally well provided that the prediction samples contain the same spectral information as the calibration samples. On the other hand, when some potential spectral features appear in new measurements, sPCR and msPCR outperform PLS significantly. The reason for this is that such spectral features are not included during calibration, which leads to a degradation in PLS prediction performance, while sPCR and msPCR can improve their predictions for the concentrations of the analytes by removing the uncalibrated features from the original spectra. This point is demonstrated by successfully applying sPCR and msPCR to in vivo blood glucose measurements. This work therefore shows that sPCR and msPCR may provide possible alternatives to PLS in cases where some uncalibrated spectral features are present in measurements used for concentration prediction.

Comparison between transmittance and reflectance measurements in glucose determination using near infrared spectroscopy

Glucose determination based on near-IR spectroscopy is investigated for reflectance and transmittance measurement. A wavelength range is 1100 to 2500 nm, which includes both the combination and overtone bands of glucose absorption. Intralipid solutions are used as samples, where glucose concentrations vary between 0 and 1000 mg/dl. Sample thickness for reflectance is 10 cm and 1- and 2-mm-thick samples are used for transmission. Partial least-squares regression (PLSR) analyses are performed to predict glucose concentrations. The standard errors of calibration are comparable between reflectance and 2-mm-thick transmittance. The reflectance method is inferior to the transmittance method in terms of the standard errors of prediction. Loading vector analysis for reflectance does not show glucose absorption features. Reflected light may not have enough information of glucose since a major portion of detected light has a short optical path length. In addition, prediction becomes more dependent on medium scattering rather than glucose, compared with transmission measurement. Loading vectors obtained from a PLSR transmittance analysis have glucose absorption profiles. The 1-mm-thick samples give better results than the 2-mm-thick samples for both calibration and prediction models. The transmittance setup is recommended for noninvasive glucose monitoring.

Noninvasive glucose sensing

The ability to measure glucose noninvasively in human subjects is a major objective for many research groups. Success will revolutionize the treatment of diabetes by providing a means to improve glycemic control, thereby delaying the onset of the medical complications associated with this disease. This article focuses on the current state of the art and attempts to identify the principal areas of research necessary to advance the field. Two fundamentally different approaches are identified for the development of noninvasive glucose sensing technology. The indirect approach attempts to measure glucose on the basis of its effect on a secondary process. The direct approach is based on the unique chemical structure of the glucose molecule. Advances for each approach are limited by issues of selectivity. Several critical parameters are discussed for the direct approach, including issues related to the optical path length, wavelength range, dimensionality of the multivariate calibration model, net analyte signal, spectral variance, and assessment of the chemical basis of measurement selectivity. A set of publication standards is recommended as a means to enhance progress toward a successful noninvasive monitor.

Noninvasive and minimally invasive methods for transdermal glucose monitoring

Noninvasive and minimally invasive techniques for monitoring glucose via the skin are reviewed. These approaches rely either on the interaction of electromagnetic radiation with the tissue or on the extraction of fluid across the barrier. The structure and physiology of the skin make the technical realization of transdermal glucose monitoring a difficult challenge. The techniques involving transdermal fluid extraction circumvent and/or compromise the barrier function of skin's outermost and least permeable layer, the stratum corneum, by the application of physical energy. While sonophoresis and microporation methods, for example, are in relatively early-stage development, a device using reverse iontophoresis [the GlucoWatch Biographer (Cygnus, Inc., Redwood City, CA)] is already commercially available. Optical techniques to monitor glucose are truly noninvasive. The tissue is irradiated, the absorbed or scattered radiation is analyzed, and the information is processed, to provide a measure proportional to the concentration of glucose in the dermal tissue. These techniques include near-infrared and Raman spectroscopy, polarimetry, light scattering, and photoacoustic spectroscopy. By contrast, impedance spectroscopy measures changes in the dielectric properties of the tissue induced by blood glucose variation. Large-scale studies in support of efficacy of these methodologies are as yet unavailable. At present, therefore, transdermal fluid extraction technologies are offering greater promise in terms of practical and realizable devices for patient use. The truly noninvasive allure of the optical approach assures continued and intense research activity--for the moment, however, an affordable, efficient, and portable system is not on the immediate horizon.

Improvement of the Partial Least Squares Model Performance for Oral Glucose Intake Experiments by Inside Mean Centering and Inside Multiplicative Signal Correction

Near infrared (NIR) spectroscopy has become a promising technique for the in vivo monitoring of glucose. Several capillary-rich locations in the body, such as the tongue, forearm, and finger, have been used to collect the in vivo spectra of blood glucose. For such an in vivo determination of blood glucose, collected NIR spectra often show some dependence on the measurement conditions and human body features at the location on which a probe touches. If NIR spectra collected for different oral glucose intake experiments, in which the skin of different patients and the measurement conditions may be quite different, are directly used, partial least squares (PLS) models built by using them would often show a large prediction error because of the differences in the skin of patients and the measurement conditions. In the present study, the NIR spectra in the range of 1300-1900 nm were measured by conveniently touching an optical fiber probe on the forearm skin with a system that was developed for in vivo measurements in our previous work. The spectra were calibrated to resolve the problem derived from the difference of patient skin and the measurement conditions by two proposed methods, inside mean centering and inside multiplicative signal correction (MSC). These two methods are different from the normal mean centering and normal multiplicative signal correction (MSC) that are usually performed to spectra in the calibration set, while inside mean centering and inside MSC are performed to the spectra in every oral glucose intake experiment. With this procedure, spectral variations resulted from the measurement conditions, and human body features will be reduced significantly. More than 3000 NIR spectra were collected during 68 oral glucose intake experiments, and calibrated. The development of PLS calibration models using the spectra show that the prediction errors can be greatly reduced. This is a potential chemometric technique with simplicity, rapidity and efficiency in the pretreatment of NIR spectra collected during oral glucose intake experiments.

Non-invasive glucose measurement technologies: an update from 1999 to the dawn of the new millennium

There are three main issues in non-invasive (NI) glucose measurements: namely, specificity, compartmentalization of glucose values, and calibration. There has been progress in the use of near-infrared and mid-infrared spectroscopy. Recently new glucose measurement methods have been developed, exploiting the effect of glucose on erythrocyte scattering, new photoacoustic phenomenon, optical coherence tomography, thermo-optical studies on human skin, Raman spectroscopy studies, fluorescence measurements, and use of photonic crystals. In addition to optical methods, in vivo electrical impedance results have been reported. Some of these methods measure intrinsic properties of glucose; others deal with its effect on tissue or blood properties. Recent studies on skin from individuals with diabetes and its response to stimuli, skin thermo-optical response, peripheral blood flow, and red blood cell rheology in diabetes shed new light on physical and physiological changes resulting from the disease that can affect NI glucose measurements. There have been advances in understanding compartmentalization of glucose values by targeting certain regions of human tissue. Calibration of NI measurements and devices is still an open question. More studies are needed to understand the specific glucose signals and signals that are due to the effect of glucose on blood and tissue properties. These studies should be performed under normal physiological conditions and in the presence of other co-morbidities.

Automated insulin infusion trials in the intensive care unit

The objective is to demonstrate the effectiveness of a simple automated insulin infusion for controlling the rise and duration of blood glucose excursion following a glucose challenge in critically ill patients with impaired glucose tolerance. A two-compartment model of the glucose regulatory system was developed for intravenous infusion control design. On two subsequent days a critically ill patient with impaired glucose tolerance was given a 75 g oral glucose tolerance test (OGTT), and the glucose level was measured every 15 min. The first day's data were used to design a heavy-derivative insulin infusion controller for the second day. Ethics approval was granted for this test. Five patients were studied. In four patients, the magnitude and duration of blood glucose excursion were reduced over 50%. Fasting level was reduced 15%, from an average of 7.2 mmol/L to 6.1 mmol/L. The fifth patient's results showed a diminished response due to the antagonistic effects of hydrocortisone on insulin, a data point not provided prior to testing. Modeling to account for this effect yielded better correlation with the test. The automated algorithm provided rapid, effective control of the blood glucose rise in response to an OGTT input. These results highlight the effectiveness of automated infusions for regulating blood glucose rise and excursions, and the potential of this approach for non-hospitalized individuals.

Removal of Interference Signals Due to Water from in vivo Near-Infrared (NIR) Spectra of Blood Glucose by Region Orthogonal Signal Correction (ROSC)

A novel chemometric method, region orthogonal signal correction (ROSC), is proposed and applied to pretreat near-infrared (NIR) spectra of blood glucose measured in vivo. Water is the most serious interference component in such kinds of noninvasive measurements, because it shows very high absorbance in the spectra. In the present study, the spectra of blood glucose in the range of 1212 - 1889 nm are used, in which the absorption of water around 1440 nm is very high. ROSC aims at removing the interference signal due to water from the spectra by selecting a set of spectra with a special region of 1404 - 1454 nm that mainly contain information about the variation of the interference component, water, and calculating the orthogonal components to the concentrations of glucose that will be removed. The difference between ROSC and orthogonal signal correction (OSC) is that ROSC uses a special region of spectra for the estimation of scores and loading weights of orthogonal components to pretreat the spectra in other regions, while OSC only uses one fixed region of spectra to calculate loadings, scores and weights of OSC components and removes the OSC components in the same region. A clear advantage of ROSC is that it is more interpretable than OSC, because one can select a spectral region to remove the variation of a special component such as water. Another chemometric method, moving window partial least squares (MWPLSR), is also used to select informative regions of glucose from the NIR spectra of blood glucose measured in vivo, leading to improved PLS models. Results of the application of ROSC demonstrate that ROSC-pretreated spectra including the whole spectral region of 1212 - 1889 nm or an informative region of 1600- 1730 nm selected by MWPLSR provide very good performance of the PLS models. Especially, the later region yields a model with RMSECV of 15.8911 mg/dL for four PLS components. ROSC is a potential chemometric technique in the pretreatment of various spectra.

Monitoring blood glucose changes in cutaneous tissue by temperature-modulated localized reflectance measurements

BACKGROUND

Most proposed noninvasive methods for glucose measurements do not consider the physiologic response of the body to changes in glucose concentration. Rather than consider the body as an inert matrix for the purpose of glucose measurement, we exploited the possibility that noninvasive measurements of glucose can be approached by investigating their effects on the skin's thermo-optical response.

METHODS

Glucose concentrations in humans were correlated with temperature-modulated localized reflectance signals at wavelengths between 590 and 935 nm, which do not correspond to any near-infrared glucose absorption wavelengths. Optical signal was collected while skin temperature was modulated between 22 and 38 degrees C over 2 h to generate a periodic set of cutaneous vasoconstricting and vasodilating events, as well as a periodic change in skin light scattering. The method was tested in a series of modified meal tolerance tests involving carbohydrate-rich meals and no-meal or high-protein/no-carbohydrate meals.

RESULTS

The optical data correlated with glucose values. Changes in glucose concentrations resulting from a carbohydrate-rich meal were predicted with a model based on a carbohydrate-meal calibration run. For diabetic individuals, glucose concentrations were predicted with a standard error of prediction <1.5 mmol/L and a prediction correlation coefficient 0.73 in 80% of the cases. There were run-to-run differences in predicted glucose concentrations. Non-carbohydrate meals showed a high degree of scatter when predicted by a carbohydrate meal calibration model.

CONCLUSIONS

Blood glucose concentrations alter thermally modulated optical signals, presumably through physiologic and physical effects. Temperature changes drive cutaneous vascular and refractive index responses in a way that mimics the effect of changes in glucose concentration. Run-to-run differences are attributable to site-to-site structural differences.

Simultaneous determination of human serum albumin, γ-globulin, and glucose in a phosphate buffer solution by near-infrared spectroscopy with moving window partial least-squares regression

Near-infrared (NIR) spectra in the 12,000-4,000 cm(-1) region were measured for phosphate buffer solutions containing human serum albumin (HSA), gamma-globulin, and glucose with various concentrations at 37 degrees C. Five levels of full factorial design were used to prepare a sample set consisting of 125 samples of three component mixtures. The concentration ranges of HSA, gamma-globulin and glucose were 0.00-6.00 g dl(-1), 0.00-4.00 g dl(-1) and 0.00-2.00 g dl(-1), respectively. The 125 sample data were split into two sets, the calibration set with 95 data and the prediction set with 30 data. The most informative spectral ranges of 4648-4323, 4647-4255 and 4912-4304 cm(-1) were selected by moving window partial least-squares regression (MWPLSR) for HSA, [gamma]-globulin, and glucose in the mixtures, respectively. For HSA, the correlation coefficient (R) of 0.9998 and the root mean square error of prediction (RMSEP) of 0.0289 g dl(-1) were obtained. For [gamma]-globulin, R of 0.9997 and RMSEP of 0.0252 g dl(-1) were obtained. The corresponding statistic values of glucose were 0.9997 and 0.0156 g dl(-1), respectively. These statistical values obtained by MWPLSR are highly significant and better than those calculated by using the regions reported in the literature. The results presented here show that MWPLSR can select the informative regions with a simple procedure and increase the power of NIR spectroscopy for simultaneous determination of the concentrations of HSA, [gamma]-globulin and glucose in the mixture systems.

Influence of temperature on water and aqueous glucose absorption spectra in the near- and mid-infrared regions at physiologically relevant temperatures

Near- and mid-infrared absorption spectra of pure water and aqueous 1.0 g/dL glucose solutions in the wavenumber range 8000-950 cm-1 were measured in the temperature range 30-42 degrees C in steps of 2 degrees C. Measurements were carried out with an FT-IR spectrometer and a variable pathlength transmission cell controlled within 0.02 degree C. Pathlengths of 50 microns and 0.4 mm were used in the mid- and near-infrared spectral region, respectively. Difference spectra were used to determine the effect of temperature on the water spectra quantitatively. These spectra were obtained by subtracting the 37 degrees C water spectrum from the spectra measured at other temperatures. The difference spectra reveal that the effect of temperature is highest in the vicinity of the strong absorption bands, with a number of isosbestic points with no temperature dependence and relatively flat plateaus in between. On the basis of these spectra, prospects for and limitations on data analysis for infrared diagnostic methods are discussed. As an example, the absorptive properties of glucose were studied in the same temperature range in order to determine the effect of temperature on the spectral shape of glucose. The change in water absorption associated with the addition of glucose has also been studied. An estimate of these effects is given and is related to the expected level of infrared signals from glucose in humans.

Rhenium bipyridine complexes for the recognition of glucose

Bipyridine ligands containing pendant methyl, amino, and amino-boronic acid groups were synthesized. Coordination complexes of these ligands with rhenium were prepared straightforwardly and in good yield. The fluorescence behavior of the Re complexes was studied as a function of pH and exposure to various concentrations of glucose. The methyl bipyridine complex showed no change in fluorescence with pH, the amino derivative showed a rapid decrease from low pH to neutral, and the amino-boronate derivative showed little change from pH 4 to 10. Fluorescence quenching was observed at high pH as expected on the basis of a photoinduced electron transfer (PET) signaling mechanism. This behavior can be explained on the basis of the first oxidation and reduction potentials of these complexes. Glucose testing showed a significant dependence on the solvent system used. In pure methanol, the rhenium boronate complex exhibited a 55% fluorescence intensity increase upon increasing glucose concentration from 0 to 400 mg/dL. However, in 50 vol % methanol/phosphate buffered saline, none of the complexes showed significant response in the glucose range of physiological interest.

Nondestructive near-infrared spectroscopic measurement of multiple analytes in undiluted samples of serum-based cell culture media

An adaptive calibration procedure is used to build selective multivariate calibration models for the measurement of glucose, lactate, glutamine, and ammonia in undiluted serum-based cell culture media. This adaptive procedure removes metabolism-induced covariance between these analytes in a series of calibration samples collected during the cultivation of PC-3 human prostate cancer cells. Partial least-squares calibration models are generated from single-beam near-infrared (NIR) spectra collected over the 4800- to 4200-cm(-1) combination spectral range. Calibration models were generated with both the full spectral range and optimized spectral ranges. In both cases, the number of model factors was optimized and model validity was determined by comparing analyte concentrations predicted from a series of independent and unaltered samples that were obtained during a subsequent cultivation of the PC-3 cells. Similar analytical performance was achieved with fewer model factors when the optimized spectral range was used. The lowest standard errors of prediction were 0.82, 0.94, 0.55, and 0.76 mM for glucose, lactate, glutamine, and ammonia, respectively. Different spectral ranges were optimal for each analyte and the optimized spectral range coincided with the distinguishing spectral features of the analyte. The results of this study demonstrate that NIR spectroscopy can be used effectively in the off-line measurement of important nutrients (glucose and glutamine) and byproducts (lactate and ammonia) in a serum-based animal cell culture medium.

Near-Infrared Spectroscopy for Measuring Urea in Hemodialysis Fluids

Background: Near-infrared spectroscopy is proposed as a method for providing real-time urea concentrations during hemodialysis treatments. The feasibility of such noninvasive urea measurements is evaluated in undiluted dialysate fluid.

Methods: Near-infrared spectra were collected from calibration solutions of urea prepared in dialysate fluid. Spectra were collected over three distinct spectral regions, and partial least-squares calibration models were optimized and compared for each. Selectivity for urea was demonstrated with two-component samples composed of urea and glucose in the dialysate matrix. The clinical significance of this approach was assessed by measuring urea in real hemodialysate samples.

Results: Urea absorptions within the combination and short-wavelength, near-infrared spectral regions provided sufficient spectral information for sound calibration models in the dialysate matrix. The combination spectral region had SEs of calibration (SEC) and prediction (SEP) of 0.38 mmol/L and 0.26 mmol/L, respectively, over the 4720–4600 cm−1 spectral range with 5 partial least-square factors. A second calibration model was established over the combination region from a series of solutions prepared with independently variable concentrations of urea and glucose. The best calibration model for urea in the presence of variable glucose concentrations had a SEC of 0.6 mmol/L and a SEP of 0.4 mmol/L for a 5-factor model over the 4600–4350 cm−1 spectral range. There was no significant decrease in SEP when the 4720–4600 cm−1 calibration model was used to measure urea in real samples collected during actual hemodialysis.

Conclusions: Urea can be determined with sufficient sensitivity and selectivity for clinical measurements within the matrix of the hemodialysis fluid.

Noninvasive and minimally-invasive optical monitoring technologies

With recent advancements in micro-fabrication and nano-fabrication techniques as well as advancements in the photonics industry, there is now the potential to develop less invasive portable sensors for monitoring micronutrients and other substances used to assess overall health. There have been many technology innovations in the central laboratory for these substances for overall health status but the primary motivation for the research and development of a portable field instrument has come from a diabetic patient and market-driven desire to minimally invasively or noninvasively monitor glucose concentrations in vivo. Such a sensor system has the potential to significantly improve the quality of life for the estimated 16 million diabetics in this country by making routine glucose measurements less painful and more convenient. In addition, there is a critical need for the development of less invasive portable technologies to assess micronutrient status (iron, vitamin A, iodine and folate), environmental hazards (lead) and for other disease-related substances, such as billirubin for infant jaundice. Currently, over 100 small companies and universities are working to develop improved monitoring devices, primarily for glucose, and optical methods are a big part of these efforts. In this article many of these potentially less invasive and portable optical sensing technologies, which are currently under investigation, will be reviewed including optical absorption spectroscopy, polarimetry, Raman spectroscopy and fluorescence.

Noninvasive glucose determination by oscillating thermal gradient spectrometry

BACKGROUND

Several noninvasive measurement approaches for the determination of blood glucose levels have been pursued over the past two decades. There is worldwide recognition that an unobtrusive and noninvasive measurement technique will better enable the patient with diabetes to obtain information for appropriate disease management. Many challenges have so far prevented any noninvasive technology from meeting the requirements.

METHOD

In this article, we describe a novel optical technology that when applied to the human body, provides both the sensitivity and the specificity required for acceptance. For human tissue, specific wavelength bands in the mid- infrared (IR) region offer predominantly single component absorbances and thus, provide the basis for the required specificity of an in vivo determination of glucose. It is highly desirable to utilize these bands for the development of a practical spectroscopic technique. The use of mid-IR absorbance bands requires a methodology that accommodates relatively short optical transmission pathlengths. Thermal gradient spectroscopy is one suitable methodology. We describe the utilization of optical phenomena, which arise during a thermal gradient, in the development of a practical instrument. The prototype apparatus is described and results obtained from aqueous samples and tissue phantom studies are presented. Furthermore, a mathematical derivation is presented in the Appendix, that defines the relationship between the optical signals produced and the properties of the tissue under analysis.

Noninvasive blood glucose measurements by near-infrared transmission spectroscopy across human tongues

Noninvasive blood glucose measurements are characterized in human subjects. A series of first overtone transmission spectra are collected across the tongues of five human subjects with type 1 diabetes. The noninvasive human spectra are collected by an experimental protocol that is designed to minimize chance correlations with blood glucose levels. In one treatment of the data, every fifth sample is used as a blind prediction point to validate model performance. In another rearrangement of the data, the spectra collected over the first 29 days are used to build calibration models that are then used to predict in vivo glycemia from spectra collected over the next 10 days. Of the five data sets (one for each subject), one demonstrates a complete inability to predict blood glucose levels and is deemed void of glucose-specific information. Glucose-specific information is evident in the remaining four data sets, albeit to varying degrees. For all data sets, the ability to measure glucose from spectra collected noninvasively from human subjects depends on spectral quality and reproducibility of the tongue-to-spectrometer interface. The standard error of prediction is 3.4 mM for the best calibration model. The significance of this magnitude of prediction error is discussed relative to the situations where: (1) the model is completely void of glucose-specific information and (2) glucose predictions are limited by spectral signal-to-noise and sample thickness. Overall, glucose-specific information is available from noninvasive first-overtone spectra collected across human tongues. Significant improvements are necessary, however, before clinically useful measurements are possible.