title: Correlation between METAVIR scores and Raman spectroscopy in liver lesions induced by hepatitis C virus: a preliminary study.
abstract: The viral hepatitis C is one of the most important causes of chronic hepatic illness worldwide, affecting around 3 % of the world population. Raman spectroscopy has been employed to distinguish normal from hepatic lesions through differences in the spectral features related to the METAVIR score system. This preliminary study evaluated 11 patients with diagnoses of chronic hepatitis C who underwent hepatic biopsies; the biopsies were submitted to near-infrared Raman spectroscopy using a dispersive spectrometer (830-nm wavelength, 300-mW laser power, and 20-s exposure time). The METAVIR was further scored, and the spectra were submitted to principal component analysis (PCA). The results show a good correlation between the Raman spectroscopy features and the stage of hepatic inflammation and fibrosis. PCA showed that samples with a higher degree of fibrosis presented a higher amount of protein features (collagen), whereas samples with a higher degree of inflammation presented higher features of hemoglobin, in accordance to the expected evolution of chronic hepatitis. Quinone was found to be an important biomarker in early hepatic lesions with a spectral feature at 1595 cm(-1). This study demonstrates that Raman spectroscopy may become an important tool for diagnosing liver disease.
authors: Biomedical Engineering Institute, Universidade Camilo Castelo Branco-UNICASTELO, Parque Tecnológico de São José dos Campos, Estr. Altino Bondesan, no 500, São José dos Campos, SP, 12247-015, Brazil.
authors: Marcio Cesar Reino
authors: MC
authors: Gaggini
authors: Ricardo Scarparo
authors: RS
authors: Navarro
authors: Aline Reis
authors: AR
authors: Stefanini
authors: Rubens Sato
authors: RS
authors: Sano
authors: Landulfo
authors: L
authors: Silveira
mesh_terms: D016174:Hepacivirus; D019698:Hepatitis C, Chronic / Q000175:diagnosis* / Q000821:virology; D006801:Humans; D025341:Principal Component Analysis; D012720:Severity of Illness Index; D019265:Spectroscopy, Near-Infrared; D013059:Spectrum Analysis, Raman