Label free hepatitis B detection based on serum derivative surface enhanced Raman spectroscopy combined with multivariate analysis.

Surface-enhanced Raman spectroscopy (SERS) was developed here for the noninvasive detection of the hepatitis B virus (HBV). Chronic hepatitis B virus (HBV) infection is a primary health problem in the world and may further develop into cirrhosis and hepatocellular carcinoma (HCC). SERS measurement was applied to two groups of serum samples. One group included 93 HBV patients and the other group included 94 healthy volunteers as control subjects. Tentative assignments of the Raman bands in the measured SERS spectra have shown the difference of the serum SERS spectra between HBV patients and healthy volunteers. The differences indicated an increase in the relative amounts of L-arginine, Saccharide band (overlaps with acyl band), phenylalanine and tyrosine, together with a decrease in the percentage of nucleic acid, valine and hypoxanthine in the serum of HBV patients compared with those of healthy volunteers. For better analysis of the spectral data, the first-order derivation was applied to the SERS data. Furthermore. principal components analysis (PCA), combined with linear discriminant analysis (LDA), were employed to distinguish HBV patients from healthy volunteers and to realize the diagnostic sensitivity of 78.5% and 91.4%, and specificity of 75% and 83% for SERS and the first order derivative SERS spectrum, respectively. These results suggest that derivative analysis could be an effective method to improve the classification of SERS spectra belonging to different groups. This exploratory work demonstrated that first-order derivative scrum SERS spectrum combined with PCA-LDA has great potential for improving the detection of HBV. (C) 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement