Ralf Marbach

Noninvasive Blood Glucose Assay by Near-Infrared Diffuse Reflectance Spectroscopy of the Human Inner Lip

Near-infrared (NIR) spectra of the human inner lip were obtained by using a special optimized accessory for diffuse reflectance measurements. The partial-least squares (PLS) multivariate calibration algorithm was applied for linear regression of the spectral data between 9000 and 5500 cm−1 (Λ = 1.1–1.8 μm) against blood glucose concentrations determined by a standard clinical enzymatic method. Calibration experiments with a single person were carried out under varying conditions, as well as with a population of 133 different patients, with capillary and venous blood glucose concentration values provided. A genuine correlation between the blood glucose concentrations and the NIR-spectra can be proven. A time lag of about 10 min for the glucose concentration in the spectroscopically probed tissue volume vs. the capillary concentration can be estimated. Mean-square prediction errors obtained by cross-validation were in the range of 45 to 55 mg/dL. An analysis of different variance factors showed that the major contribution to the average prediction uncertainty was due to the reduced measurement reproducibility, i.e., variations in lip position and contact pressure. The results demonstrate the feasibility of using diffuse reflectance NIR-spectroscopy for the noninvasive measurement of blood glucose.

Multicomponent Assay for Blood Substrates in Human Plasma by Mid-Infrared Spectroscopy and its Evaluation for Clinical Analysis

An analytical multicomponent method for the blood substrates total protein, glucose, total cholesterol, triglycerides, and urea in human EDTA plasma by FT-IR spectroscopy is described. The spectra were obtained with the use of the attenuated total reflection technique. Partial least-squares was applied for multivariate calibration over optimized spectral ranges. The mean-square prediction errors for the population of 126 plasma samples of different patients calculated by cross-validation are in the range of clinical acceptance. Within an error variance analysis, the contributions of the reference method and the spectrometric measurement to the average (root mean square) prediction error have been estimated for each substrate, giving evidence of the limitations of the spectrometric method. The problem of the biocompatibility of the plasma has been investigated, and the protein adsorption onto the ATR crystal can be reduced to a constant and tolerable level by appropriate cleaning and rinsing. The potential for further improvement is discussed.

Multivariate Determination of Glucose in Whole Blood Using Partial Least-Squares and Artificial Neural Networks Based on Mid-Infrared Spectroscopy

The infrared (IR) spectra of whole blood EDTA samples, in the range between 1500 and 750 cm−1, obtained from the patient population of a general hospital, were used to compare different multivariate calibration techniques for quantitative glucose determination. Ninety-six spectra of whole undiluted blood samples with glucose concentration ranging between 44 and 291 mg/dL were used to create calibration models based on a combination of partial least-squares (PLS) and artificial neural network (ANN) methods. The prediction capabilities of these calibration models were evaluated by comparing their standard errors of prediction (SEP) with those obtained with the use of PLS and principal component regression (PCR) calibration models in an independent prediction set consisting of 31 blood samples. The optimal model based on the combined PLS-ANN produced smaller SEP values (15.6 mg/dL) compared with those produced with the use of either PLS (21.5 mg/dL) or PCR (24.0 mg/dL) methods. Our results revealed that the combined PLS-ANN models can better approximate the deviations from linearity in the relationship between spectral data and concentration, compared with either PLS or PCR models.

Near-infrared reflectance spectroscopy for noninvasive monitoring of metabolites.

Abstract An important class of substances in clinical chemistry are metabolites in body fluids, which are accessible by near-infrared spectroscopy without sample treatment using reagentless, fast and readily automated in vitro assays. Furthermore, noninvasive sensing systems are under development for the determination of blood glucose, especially for diabetic patients or for monitoring in intensive care and surgery. Near-infrared diffuse reflectance spectrometry of skin was employed allowing a certain tissue volume to be integrally probed. For calibration, the partial least-squares (PLS) algorithm was used either based on wide spectral intervals or using special spectral variable selection. Capillary blood glucose reference concentrations were obtained by finger pricking and an automated laboratory method (hexokinase/G6P-DH). Clear evidence is provided for the physical effect, as manifested by the spectral glucose absorptivities, underlying the individual single-person calibration models, which still require improvements in the methodology in the normo- and hypoglycemic concentration range. In extending the potential of noninvasive blood assays by infrared spectroscopy, a novel technique is presented for probing the intravascular fluid space by using fast spectral near-infrared measurements of skin tissue. The pulsatile blood spectrum can be derived from reflectance spectra of oral mucosa by Fourier analysis (near-infrared plethysmography). Future applications and prospects for noninvasive blood assays are discussed.

Clinical chemistry and near infrared spectroscopy: multicomponent assay for human plasma and its evaluation for the determination of blood substrates

A multicomponent assay for the blood substrates of total protein, glucose, total cholesterol, triglycerides and urea in human EDTA-plasma by FT-IR spectroscopy is described. Transmission near infrared spectra of plasma were recorded using a 1 mm cell. Partial least-squares was applied for multivariate calibration taking into account optimising the spectral ranges of absorbance or logarithmised single beam spectra. The standard errors of prediction for the population of 124 plasma samples of different patients calculated by cross-validation are in the range of clinical acceptance for protein, cholesterol and triglycerides, whereas glucose assay performance is slightly above the recommended level. The relative standard error of prediction for urea is 12.7% based on the mean concentration of the population studied. Within an error variance analysis, the contributions of the reference method and the spectrometric measurement to the average (RMS) prediction error have been estimated for each substrate giving evidence of the spectrometric method limitations. The potential for further improvement is discussed.

Multivariate determination of blood substrates in human plasma by FT-NIR spectroscopy

A spectral analysis of human EDTA plasma from 124 different patients was undertaken using an FT-NIR spectrometer. Optimized intervals of the absorbance spectra were considered for the PLS-calibrations with reference concentrations from standard clinical methods determined in triplicate. The following relative prediction errors were achieved: total protein 1.4%, cholesterol 3.8%, triglycerides 8.6%, glucose 9.1%, and urea 18.6%.

Effect of data pretreatment on the noninvasive blood glucose measurement by diffuse reflectance NIR spectroscopy

Recent progress in spectroscopy and chemometrics have brought in-vitro blood glucose analysis into clinical reach. Parallel to these efforts noninvasive experiments by NIR- spectroscopy have also been proposed and carried out. A specially designed and optimized accessory for diffuse reflectance measurements in the spectral range of 9000 - 5000 cm-1 was used. The spectral data and reference concentration values were obtained using oral glucose tolerance tests. Calibration results are provided for log(1/R) and single beam spectra. In addition, the effects of smoothing and the use of derivative filtering were evaluated. The best results were achieved by multivariate PLS-modeling with raw data from single beam reflectance spectra.

Multivariate calibration of glucose in blood by PLS using spectral and fourier-domain data

Infrared attenuated total reflection spectra of 133 whole EDTA blood samples, from patients of a general hospital population, in the range from 1500 to 750 cm−1 were used for the calibration of glucose. Reference concentration values were provided by the enzymatic glucose dehydrogenase method. The partial-least squares (PLS) algorithm was used to solve the inverse regression problem. The prediction results from, calculations using spectral and Fourier-transformed data were compared, and in the latter case, the data reduction yielded no advantage. The spectral range optimization for calibration can be carried out more flexibly in the spectral domain which is more readily interpreted by the spectroscopist.

Novel design of an ellipsoidal diffuse-reflectance accessory with improved throughput

The value of diffuse reflectance spectroscopy for infrared analytical methods has some limitations caused by the low throughput efficiency of commercial accessories. We have redesigned a home-built diffuse reflectance accessory with an on-axis ellipsoidal collecting mirror which can also have benefits for the analysis of bulky samples. For illumination, use is made of the Circle cell optics which fits by adaption into the cone with a half angle of 30 degree(s) not considered for detection. Special features of the accessory are discussed, especially in view of our applications to the study of human tissue.