Abstract
Micro-Raman spectroscopy is a very promising tool for medical applications, thanks to its sensitivity to subtle changes in the chemical and structural characteristics of biological specimens. To fully exploit these promises, building a method of data analysis properly suited for the case under study is crucial. Here, a linear or univariate approach using a R2 determination coefficient is proposed for discriminating Raman spectra even with small differences. The validity of the proposed approach has been tested using Raman spectra of high purity glucose solutions collected in the 600 to 1,600 cm−1 region and also from solutions with two known solutes at different concentrations. After this validation step, the proposed analysis has been applied to Raman spectra from oral human tissues affected by Pemphigus Vulgaris (PV), a rare life-threatening autoimmune disease, for monitoring disease follow-up. Raman spectra have been obtained in the wavenumber regions from 1,050 to 1,700 cm−1 and 2,700 to 3,200 cm−1 from tissues of patients at different stages of pathology (active PV, under therapy and PV in remission stage) as confirmed by histopathological and immunofluorescence analysis. Differences in the spectra depending on tissue illness stage have been detected at 1,150–1,250 cm−1 (amide III) and 1,420–1,450 cm−1 (CH3 deformation) regions and around 1,650 cm−1 (amide I) and 2,930 cm−1 (CH3 symmetric stretch). The analysis of tissue Raman spectra by the proposed univariate method has allowed us to effectively differentiate tissues at different stages of pathology.
Highlights
In the last years micro-Raman spectroscopy [1] has shown to be a very promising tool for specific molecular fingerprinting in medical applications
Its success has been strongly boosted by the development of specific data analysis methods enabling the extraction of the wealth of information embedded in Raman spectra of complex samples, such as human tissues, fluids and humours
The above described univariate or linear regression approach has been firstly applied to aqueous glucose solutions to simulate an experimental situation in which Raman spectra were obtained from different samples with no structural differences
Summary
In the last years micro-Raman spectroscopy [1] has shown to be a very promising tool for specific molecular fingerprinting in medical applications. The proposed approach for spectrum analysis can be considered as an extension of the many methods reported in the literature for quantitatively comparing Raman signals [8,9,10,11,12,13] and it could be useful for comparing Raman responses from different and independent samples of similar materials, such as tissue biopsies In spite of their differences due to individual characteristics and history, previous work [5,6,7] has shown that a basic common profile may be expected for Raman responses from tissues of subjects in the same state of pathology. The method here proposed permits one to find out the similarities in the spectra and to discriminate the spectra exhibiting possible anomalies, providing a powerful tool for the analysis of spectra with small differences
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