Optical diagnostic of hepatitis B (HBV) and C (HCV) from human blood serum using Raman spectroscopy

Abstract

Hepatitis is the second most common disease worldwide with half of the cases arising in the developing world. The mortality associated with hepatitis B and C can be reduced if the disease is detected at the early stages of development. The aim of this study was to investigate the potential of Raman spectroscopy as a diagnostic tool to detect biochemical changes accompanying hepatitis progression. Raman spectra were acquired from 20 individuals with six hepatitis B infected patients, six hepatitis C infected patients and eight healthy patients in order to gain an insight into the determination of biochemical changes for early diagnostic. The human blood serum was examined at a 532 nm excitation laser source. Raman characteristic peaks were observed in normal sera at 1006, 1157 and 1513 cm −1 , while in the case of hepatitis B and C these peaks were found to be blue shifted with decreased intensity. New Raman peaks appeared in HBV and HCV infected sera at 1194, 1302, 844, 905, 1065 and 1303 cm −1 respectively. A Mat lab subroutine and frequency domain filter program is developed and applied to signal processing of Raman scattering data. The algorithms have been successfully applied to remove the signal noise found in experimental scattering signals.The results show that Raman spectroscopy displays a high sensitivity to biochemical changes in blood sera during disease progression resulting in exceptional prediction accuracy when discriminating between normal and malignant. Raman spectroscopy shows enormous clinical potential as a rapid non-invasive diagnostic tool for hepatitis and other infectious diseases.

Optical imaging spectroscopy for rapid, primary screening of SARS-CoV-2: a proof of concept

“…Optical spectroscopic methods have been developed to detect viruses in vegetal structures 21 – 23 and in human samples, mostly in blood. They involve polarimetric and fluorescence spectroscopy, and different implementations of Raman spectroscopy for identification of Dengue virus 24 , hepatitis B and C viruses 25 , and microfluidic devices to recognize avian influenza A and other respiratory infections 26 . Further approaches propose the use of nanomaterials targeted to specific viral antibodies to enhance the potentialities of optical spectroscopy to detect the human immunodeficiency virus 27 .…”

Wheat Leaf Rust Detection at an Early Stage with Atomic Force Microscopy (AFM)

“…Wheat leaf rust at the leaf scale was studied for two purposes, one is to estimate the reflectance spectra of various disease symptoms; and other is to introduce an index for precise determination of disease severity using the spectral reflectance of leaf [24]. In our previous study we have applied optical detection techniques to several viral infection monitoring using human blood in vivo and in vitro [25][26][27][28][29][30][31][32].…”

Analysis and Classification of Hepatitis Infections Using Raman Spectroscopy and Multiscale Convolutional Neural Networks

“…Benzoquinone [42] Lipids, fatty acids [42] Possible changes in polysaccharide structure are observed in this region [43] N(C-C) stretching (probably in amino acids) [43] This region allowed for a complete separation between HBV-and HCV-infected and normal blood serum spectra [43] This region allowed for a complete separation between HBV-and HCV-infected and normal blood serum spectra [43] C-120 protein in human blood serum [43] Amide-I bond [43] experimental results show underfi tting, and the accuracy is reduced by 2.43% compared to the two-layer scheme. With three extraction and fusion layers, the experimental results show overfi tting, and the accuracy is reduced by 3.22% compared to the two-layer scheme.…”