Reagentless Blood Analysis by Near-Infrared Raman Spectroscopy

Abstract

Background: Raman spectroscopy has advantages over infrared absorption spectroscopy. Combined with a novel multivariate technique, hybrid linear analysis (HLA), low prediction error is expected. Methods: 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. Results: 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. Conclusions: 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.