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

Abstract

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 Larginine, 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 serum SERS spectrum combined with PCA-LDA has great potential for improving the detection of HBV.

Enhancing Disease Diagnosis: Biomedical Applications of Surface-Enhanced Raman Scattering

“…Examples of where chemometrics has been applied to SERS and related techniques include detection of cancers using PC-LDA and SVM [68][69][70][71], microbial pathogens by various discriminant and cluster analysis [72][73][74] and drug and their metabolites by PLS and ANNs [75][76][77].…”

Optical diagnosis of hepatitis B virus infection in blood plasma using Raman spectroscopy and chemometric techniques

“…The enhanced performance of the developed PCA‐SVM models is revealed compared with other studies 25–27 . For instance, our model (Table 2) demonstrates higher diagnostic accuracy, sensitivity, and specificity of 98.82%, 98.89%, and 98.80%, respectively.…”

“…Each molecule has a unique scattering patron, which serves as a fingerprint and hence identification entity for a particular molecule or compound in a mixture. In recent years, Raman spectra of blood serum samples were used to diagnose many types of infectious diseases, including dengue virus infection, 14–16 hepatitis C, 17,18 typhoid and malaria fever, 19–21 HIV infection, 22 tuberculosis, 23 and HBV infection 24–27 . Therefore, in order to improve the diagnostic capability for infectious diseases, new, reliable, online, and economical methods are needed to be developed for diagnosis and for monitoring the progression of infection.…”

“…During recent years, four studies have been reported on the detection of HBV infection in blood sera using Raman spectroscopy 24–27 . Khan et al 24 used SVM algorithm on the Raman spectra of diseased and healthy samples and compared diagnostic accuracy for different polynomial kernel.…”

Surface‐enhanced Raman scattering of secretory proteins for the cytotoxicity analysis of low‐dose doxorubicin

“…PCA can reduce the high dimension of SERS spectra into a few PC scores which contain the most of diagnostic information for sample identification. Furthermore, LDA is a useful method for determining the discriminant function that maximizes the variance in the data between different sample groups while minimizing the variance between members of the same group [65]. Figure 3a,b shows that most of the clusters standing for secretory protein samples from control (without treatment) and from doxorubicin‐treated groups have been broadly separated into two parts except the overlap of a few samples.…”