An "in vitro" study of Raman spectra from oral human tissues is reported in order to the develop a diagnostic method suitable for "in vivo" oral pathology follow-up. The investigated pathology is Pemphigus Vulgaris (PV) for which new techniques for guiding and monitoring therapy would be particularly useful. Raman spectra were obtained in the wavenumber regions from 1000 to 1800 cm(-1) and 2700 to 3200 cm(-1) from tissues from patients at different stages of pathology (active PV, under therapy and in PV remission stage) as confirmed by histopathological and immunofluorescence analysis. Differences in the spectra depending on tissue illness stage arise in 1150-1250 cm(-1) (amide III) and 1420-1450 cm(-1) (CH3 deformation) regions and around 1650 cm(-1) (amide I) and 2930 cm(-1) (CH3 symmetric stretch). A wavelet deconvolution procedure was applied to the spectra for better discriminating among the three different stages of illness and a linear regression analysis was used to fully exploit the content of information of Raman spectra.

Micro-Raman spectroscopy of tissue samples for oral pathology follow-up monitoring

PERNA, GIUSEPPE;CAPOZZI, VITO GIACOMO;
2010-01-01

Abstract

An "in vitro" study of Raman spectra from oral human tissues is reported in order to the develop a diagnostic method suitable for "in vivo" oral pathology follow-up. The investigated pathology is Pemphigus Vulgaris (PV) for which new techniques for guiding and monitoring therapy would be particularly useful. Raman spectra were obtained in the wavenumber regions from 1000 to 1800 cm(-1) and 2700 to 3200 cm(-1) from tissues from patients at different stages of pathology (active PV, under therapy and in PV remission stage) as confirmed by histopathological and immunofluorescence analysis. Differences in the spectra depending on tissue illness stage arise in 1150-1250 cm(-1) (amide III) and 1420-1450 cm(-1) (CH3 deformation) regions and around 1650 cm(-1) (amide I) and 2930 cm(-1) (CH3 symmetric stretch). A wavelet deconvolution procedure was applied to the spectra for better discriminating among the three different stages of illness and a linear regression analysis was used to fully exploit the content of information of Raman spectra.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11369/15925
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