Mid-infrared and Raman spectroscopy together with multivariate data analysis offers the potential to be applied to clinical laboratory analysis due to their reagent-free nature, the speed of analysis and the possibility of obtaining a variety of information from a single measurement. In what we believe to be among the largest studies on mid-infrared and Raman spectroscopy for the analysis of multiple analytes in serum, samples from 247 donors have been analyzed with the emphasis on reproducibility. In an independent validation, root-mean-square errors of prediction (RMSEP) ranged from 328 mg/dL for the quantification of protein (mean concentration: 7008 mg/dL) using mid-infrared spectroscopy to 1.1 mg/dL for uric acid (mean concentration: 5.3 mg/dL) in the case of Raman spectroscopy. Both techniques deliver similar performances. We also performed first steps towards determining system precision and accuracy. In a fivefold measurement of 5 randomly chosen samples from this study, precision and accuracy range from 4% to 16% and from 4% to 29%, respectively. However, when considering the physiological and pathological range of concentrations of analytes, vibrational spectroscopy might open the path towards less expensive and more rapid multiparameter analysis of small sample volumes in those cases, in which moderate accuracy is permissible.
Mid-infrared or Raman spectroscopy together with multivariate data analysis provides a novel approach to clinical laboratory analysis, offering benefits due to its reagent-free nature, the speed of the analysis and the possibility of obtaining a variety of information from one single measurement. We compared mid-infrared and Raman spectra of the sera obtained from 247 blood donors. Partial least squares analysis of the vibrational spectra allowed for the quantification of total protein, cholesterol, high and low density lipoproteins, triglycerides, glucose, urea and uric acid. Glucose (mean concentration: 154 mg/dl) is frequently used as a benchmark for spectroscopic analysis and we achieved a root mean square error of prediction of 14.7 and 17.1 mg/dl for mid-infrared and Raman spectroscopy, respectively. Using the same sample set, comparable sample throughput, and identical mathematical quantification procedures Raman and mid-infrared spectroscopy of serum deliver similar accuracies for the quantification of the analytes under investigation. In our experiments vibrational spectroscopy-based quantification appears to be limited to accuracies in the 0.1 mmol/l range.
Design and functionality of a reagent-free Raman-based fiber optic
sensor are described in the context of glucose monitoring.
Theoretical calculations of sensor performance are shown using
raytrace software. An optimized sensor design with an outer
diameter of 1.5 mm was carried out. First experiments in aqueous
glucose solutions showed a root mean square error of prediction of
10.5 mg/dl in an independent validation.