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Raman microspectroscopy as a biomarking tool for in vitro diagnosis of cancer: a feasibility study

AIM: To elucidate whether Raman spectroscopy aided by extensive spectral database and neural network analysis can be a fast and confident biomarking tool for the diagnosis of various types of cancer. METHODS: Study included 27 patients with 11 different malignant tumors. Using Raman microscopy (RM)...

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Autores principales: Pavićević, Aleksandra, Glumac, Sofija, Sopta, Jelena, Popović-Bijelić, Ana, Mojović, Miloš, Bačić, Goran
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Croatian Medical Schools 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3541581/
https://www.ncbi.nlm.nih.gov/pubmed/23275320
http://dx.doi.org/10.3325/cmj.2012.53.551
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author Pavićević, Aleksandra
Glumac, Sofija
Sopta, Jelena
Popović-Bijelić, Ana
Mojović, Miloš
Bačić, Goran
author_facet Pavićević, Aleksandra
Glumac, Sofija
Sopta, Jelena
Popović-Bijelić, Ana
Mojović, Miloš
Bačić, Goran
author_sort Pavićević, Aleksandra
collection PubMed
description AIM: To elucidate whether Raman spectroscopy aided by extensive spectral database and neural network analysis can be a fast and confident biomarking tool for the diagnosis of various types of cancer. METHODS: Study included 27 patients with 11 different malignant tumors. Using Raman microscopy (RM) a total of 540 Raman spectra were recorded from histology specimens of both tumors and surrounding healthy tissues. Spectra were analyzed using the principal component analysis (PCA) and results, along with histopathology data, were used to train the neural network (NN) learning algorithm. Independent sets of spectra were used to test the accuracy of PCA/NN tissue classification. RESULTS: The confident tumor identification for the purpose of medical diagnosis has to be performed by taking into account the whole spectral shape, and not only particular spectral bands. The use of PCA/NN analysis showed overall sensitivity of 96% with 4% false negative tumor classification. The specificity of distinguishing tumor types was 80%. These results are comparable to previously published data where tumors of only one tissue type were examined and can be regarded satisfactorily for a relatively small database of Raman spectra used here. CONCLUSION: In vitro RM combined with PCA/NN is an almost fully automated method for histopathology at the level of macromolecules. Supported by an extensive tumor spectra database, it could become a customary histological analysis tool for fast and reliable diagnosis of different types of cancer in clinical settings.
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spelling pubmed-35415812013-01-17 Raman microspectroscopy as a biomarking tool for in vitro diagnosis of cancer: a feasibility study Pavićević, Aleksandra Glumac, Sofija Sopta, Jelena Popović-Bijelić, Ana Mojović, Miloš Bačić, Goran Croat Med J Medical Research in Biophysics AIM: To elucidate whether Raman spectroscopy aided by extensive spectral database and neural network analysis can be a fast and confident biomarking tool for the diagnosis of various types of cancer. METHODS: Study included 27 patients with 11 different malignant tumors. Using Raman microscopy (RM) a total of 540 Raman spectra were recorded from histology specimens of both tumors and surrounding healthy tissues. Spectra were analyzed using the principal component analysis (PCA) and results, along with histopathology data, were used to train the neural network (NN) learning algorithm. Independent sets of spectra were used to test the accuracy of PCA/NN tissue classification. RESULTS: The confident tumor identification for the purpose of medical diagnosis has to be performed by taking into account the whole spectral shape, and not only particular spectral bands. The use of PCA/NN analysis showed overall sensitivity of 96% with 4% false negative tumor classification. The specificity of distinguishing tumor types was 80%. These results are comparable to previously published data where tumors of only one tissue type were examined and can be regarded satisfactorily for a relatively small database of Raman spectra used here. CONCLUSION: In vitro RM combined with PCA/NN is an almost fully automated method for histopathology at the level of macromolecules. Supported by an extensive tumor spectra database, it could become a customary histological analysis tool for fast and reliable diagnosis of different types of cancer in clinical settings. Croatian Medical Schools 2012-12 /pmc/articles/PMC3541581/ /pubmed/23275320 http://dx.doi.org/10.3325/cmj.2012.53.551 Text en Copyright © 2012 by the Croatian Medical Journal. All rights reserved. http://creativecommons.org/licenses/by/2.5/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Medical Research in Biophysics
Pavićević, Aleksandra
Glumac, Sofija
Sopta, Jelena
Popović-Bijelić, Ana
Mojović, Miloš
Bačić, Goran
Raman microspectroscopy as a biomarking tool for in vitro diagnosis of cancer: a feasibility study
title Raman microspectroscopy as a biomarking tool for in vitro diagnosis of cancer: a feasibility study
title_full Raman microspectroscopy as a biomarking tool for in vitro diagnosis of cancer: a feasibility study
title_fullStr Raman microspectroscopy as a biomarking tool for in vitro diagnosis of cancer: a feasibility study
title_full_unstemmed Raman microspectroscopy as a biomarking tool for in vitro diagnosis of cancer: a feasibility study
title_short Raman microspectroscopy as a biomarking tool for in vitro diagnosis of cancer: a feasibility study
title_sort raman microspectroscopy as a biomarking tool for in vitro diagnosis of cancer: a feasibility study
topic Medical Research in Biophysics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3541581/
https://www.ncbi.nlm.nih.gov/pubmed/23275320
http://dx.doi.org/10.3325/cmj.2012.53.551
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