Micro-Raman Spectroscopy and Univariate Analysis for Monitoring Disease Follow-Up

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...

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Main Authors: Vito Capozzi, Giuseppe Perna, Ines Delfino, Carlo Camerlingo, Maria Lepore
Format: Article
Language:English
Published: MDPI AG 2011-08-01
Series:Sensors
Subjects:
Online Access:http://www.mdpi.com/1424-8220/11/9/8309/
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author Vito Capozzi
Giuseppe Perna
Ines Delfino
Carlo Camerlingo
Maria Lepore
author_facet Vito Capozzi
Giuseppe Perna
Ines Delfino
Carlo Camerlingo
Maria Lepore
author_sort Vito Capozzi
collection DOAJ
description 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.
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spelling doaj.art-2285b02dbcf54c37b6be5edd866700ac2022-12-22T04:23:40ZengMDPI AGSensors1424-82202011-08-011198309832210.3390/s110908309Micro-Raman Spectroscopy and Univariate Analysis for Monitoring Disease Follow-UpVito CapozziGiuseppe PernaInes DelfinoCarlo CamerlingoMaria LeporeMicro-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.http://www.mdpi.com/1424-8220/11/9/8309/oral tissuesRaman microspectroscopyunivariate data analysisfollow-up monitoring
spellingShingle Vito Capozzi
Giuseppe Perna
Ines Delfino
Carlo Camerlingo
Maria Lepore
Micro-Raman Spectroscopy and Univariate Analysis for Monitoring Disease Follow-Up
Sensors
oral tissues
Raman microspectroscopy
univariate data analysis
follow-up monitoring
title Micro-Raman Spectroscopy and Univariate Analysis for Monitoring Disease Follow-Up
title_full Micro-Raman Spectroscopy and Univariate Analysis for Monitoring Disease Follow-Up
title_fullStr Micro-Raman Spectroscopy and Univariate Analysis for Monitoring Disease Follow-Up
title_full_unstemmed Micro-Raman Spectroscopy and Univariate Analysis for Monitoring Disease Follow-Up
title_short Micro-Raman Spectroscopy and Univariate Analysis for Monitoring Disease Follow-Up
title_sort micro raman spectroscopy and univariate analysis for monitoring disease follow up
topic oral tissues
Raman microspectroscopy
univariate data analysis
follow-up monitoring
url http://www.mdpi.com/1424-8220/11/9/8309/
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AT inesdelfino microramanspectroscopyandunivariateanalysisformonitoringdiseasefollowup
AT carlocamerlingo microramanspectroscopyandunivariateanalysisformonitoringdiseasefollowup
AT marialepore microramanspectroscopyandunivariateanalysisformonitoringdiseasefollowup