Biomedical subjects

H Michael Heise

Publications and source records attributed to H Michael Heise.

5 recordsLinked to original sources

PubMed2007

CH-overtone regions as diagnostic markers for near-infrared spectroscopic diagnosis of primary cancers in human pancreas and colorectal tissue.

We have investigated the application of near-infrared spectroscopy for detection of human primary pancreatic and colorectal cancers. Spectra from cancerous and normal tissue were collected from a total of 37 surgically resected pancreatic and colorectal patient tissue specimens using a fibre-optic probe. Major spectral differences were observed in the CH-stretching first (6,000-5,400 cm(-1)) and second overtone (9,000-7,900 cm(-1)) regions. By use of artificial neural networks, linear discriminant analysis, and cluster analysis as pattern-recognition methods the spectra were classified into cancerous and normal tissue groups with accuracy up to 89%. We also explored differences between the spectra obtained from colorectal and pancreatic tissue. Spectral data from cancerous and normal tissue were classified organ-specifically into four groups with accuracy between 80 and 83%. Our results indicate that CH-overtone regions, besides serving as diagnostic markers for NIR spectroscopic diagnosis of primary human pancreas and colorectal cancers, are also useful for elucidating differences between the spectra obtained from colorectal and pancreatic cancerous tissue.

Adult↗

PubMed2006

Infrared transmission spectrometry for the determination of urea in microliter sample volumes of blood plasma dialysates.

Application of mid-infrared spectroscopy for the determination of urea in blood plasma dialysates of microliter sample volumes using a transmission microcell was investigated. Infrared spectra of the dialysates of plasma samples collected from 75 different patients using CMA 60 microdialysis catheters were evaluated with multivariate partial least squares regression. Using the absorbance spectral data from 1520-1420 cm(-1) and 1220-1120 cm(-1), a minimum standard error of prediction (SEP) of 0.88 mg/dL (0.14 mM) was achieved with spectral variable selection. Our findings suggest the feasibility of developing a mid-infrared sensor in combination with micro-fluidics for on-line monitoring of urea in patients undergoing dialysis treatment.

Biomarkers↗

PubMed2005

Nanoliter serum sample analysis by mid-infrared spectroscopy for minimally invasive blood-glucose monitoring.

The aim of this study was to demonstrate that mid-infrared spectroscopy is able to quantify glucose in a serum matrix with sample volumes well below 1 muL. For this, we applied mid-infrared attenuated total reflectance (ATR) or transmission-based spectroscopic methods to glucose quantification in microsamples of dry-film sera, either undiluted or diluted 10 times in distilled water. The sample series spanned physiological glucose concentrations between 50 and 600 mg/dL and volumes of 80, 8, and 1 nL. Calibration was carried out using multivariate partial least-squares (PLS) modeling with spectral data between 1180 and 940 cm(-1). Best performance was achieved in the ATR experiments. For raw ATR spectra, the optimum standard error of prediction (SEP) of 13.3 mg/dL was obtained for the 8 nL sample series with subsequent 10-fold dilution. With respect to the coefficient of variation of the glucose assay, CV(pred), we obtained a value of 3% for the 80 nL volume samples with spectral preprocessing using matrix protein absorption bands as an internal standard, 4% for the 8 nL samples, and 6% for the 1 nL samples with raw data. Spectral standardization resulted in significant improvement, especially for the 80 nL volume sample series. By contrast, the accuracy of the glucose assay for the 1 nL sample volume series could not be improved either by internal standardization or by considering the dry film areas for normalization, which we attribute to varying topographies of the dry films.

Blood Chemical Analysis↗

PubMed2005

Spectral variable selection for partial least squares calibration applied to authentication and quantification of extra virgin olive oils using Fourier transform Raman spectroscopy.

The limits of quantitative multivariate assays for the analysis of extra virgin olive oil samples from various Greek sites adulterated by sunflower oil have been evaluated based on their Fourier transform (FT) Raman spectra. Different strategies for wavelength selection were tested for calculating optimal partial least squares (PLS) models. Compared to the full spectrum methods previously applied, the optimum standard error of prediction (SEP) for the sunflower oil concentrations in spiked olive oil samples could be significantly reduced. One efficient approach (PMMS, pair-wise minima and maxima selection) used a special variable selection strategy based on a pair-wise consideration of significant respective minima and maxima of PLS regression vectors, calculated for broad spectral intervals and a low number of PLS factors. PMMS provided robust calibration models with a small number of variables. On the other hand, the Tabu search strategy recently published (search process guided by restrictions leading to Tabu list) achieved lower SEP values but at the cost of extensive computing time when searching for a global minimum and less robust calibration models. Robustness was tested by using packages of ten and twenty randomly selected samples within cross-validation for calculating independent prediction values. The best SEP values for a one year's harvest with a total number of 66 Cretian samples were obtained by such spectral variable optimized PLS calibration models using leave-20-out cross-validation (values between 0.5 and 0.7% by weight). For the more complex population of olive oil samples from all over Greece (total number of 92 samples), results were between 0.7 and 0.9% by weight with a cross-validation sample package size of 20. Notably, the calibration method with Tabu variable selection has been shown to be a valid chemometric approach by which a single model can be applied with a low SEP of 1.4% for olive oil samples across three different harvest years.

Calibration↗

PubMed2004

Glucose quantification in dried-down nanoliter samples using mid-infrared attenuated total reflection spectroscopy.

The aim of this study was to determine the feasibility of minimally invasive glucose concentration measurement of a body fluid within the physiologically important range below 100 nL with a number of samples such as interstitial fluid, plasma, or whole blood using mid-infrared spectroscopy, but starting with preliminary measurements on samples of simple aqueous glucose solutions. The Fourier transform infrared spectrometer was equipped with a Golden Gate single reflection diamond attenuated total reflection (ATR) accessory and a room-temperature pyroelectric detector. As the necessary detection limits can be achieved only for dried samples within the spectrometric conditions realized by a commercial instrument, the work focused on the optimization of such ATR measurements. We achieved quantification of samples with volumes as low as 7 nL between 10 and 600 mg/dL. The standard error of prediction (SEP) for the concentration range 10-100 mg/dL is 3.2 mg/dL with full interval data between 1180 and 940 cm(-1). The performance of the prediction is given by a coefficient of variation of prediction (CV(pred) ) of 6.2%. When all samples within the whole concentration range are included, the SEP increases to 20.2 mg/dL, and hence the CV(pred) to 10.6% due to a nonlinear signal dependence on glucose concentration. A detection limit for glucose of 0.7 ng with a signal-to-noise ratio of 10 was obtained.

Glucose↗