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Discrimination between two different grades of human glioma based on blood vessel infrared spectral imaging
Gliomas are brain tumours classified into four grades with increasing malignancy from I to IV. The development and the progression of malignant glioma largely depend on the tumour vascularization. Due to their tissue heterogeneity, glioma cases can be difficult to classify into a specific grade usin...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4569654/ https://www.ncbi.nlm.nih.gov/pubmed/26168973 http://dx.doi.org/10.1007/s00216-015-8891-z |
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author | Wehbe, Katia Forfar, Isabelle Eimer, Sandrine Cinque, Gianfelice |
author_facet | Wehbe, Katia Forfar, Isabelle Eimer, Sandrine Cinque, Gianfelice |
author_sort | Wehbe, Katia |
collection | PubMed |
description | Gliomas are brain tumours classified into four grades with increasing malignancy from I to IV. The development and the progression of malignant glioma largely depend on the tumour vascularization. Due to their tissue heterogeneity, glioma cases can be difficult to classify into a specific grade using the gold standard of histological observation, hence the need to base classification on a quantitative and reliable analytical method for accurately grading the disease. Previous works focused specifically on vascularization study by Fourier transform infrared (FTIR) spectroscopy, proving this method to be a way forward to detect biochemical changes in the tumour tissue not detectable by visual techniques. In this project, we employed FTIR imaging using a focal plane array (FPA) detector and globar source to analyse large areas of glioma tumour tissue sections via molecular fingerprinting in view of helping to define markers of the tumour grade. Unsupervised multivariate analysis (hierarchical cluster analysis and principal component analysis) of blood vessel spectral data, retrieved from the FPA images, revealed the fine structure of the borderline between two areas identified by a pathologist as grades III and IV. Spectroscopic indicators are found capable of discriminating different areas in the tumour tissue and are proposed as biomolecular markers for potential future use of grading gliomas. [Figure: see text] ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00216-015-8891-z) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4569654 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-45696542015-09-18 Discrimination between two different grades of human glioma based on blood vessel infrared spectral imaging Wehbe, Katia Forfar, Isabelle Eimer, Sandrine Cinque, Gianfelice Anal Bioanal Chem Research Paper Gliomas are brain tumours classified into four grades with increasing malignancy from I to IV. The development and the progression of malignant glioma largely depend on the tumour vascularization. Due to their tissue heterogeneity, glioma cases can be difficult to classify into a specific grade using the gold standard of histological observation, hence the need to base classification on a quantitative and reliable analytical method for accurately grading the disease. Previous works focused specifically on vascularization study by Fourier transform infrared (FTIR) spectroscopy, proving this method to be a way forward to detect biochemical changes in the tumour tissue not detectable by visual techniques. In this project, we employed FTIR imaging using a focal plane array (FPA) detector and globar source to analyse large areas of glioma tumour tissue sections via molecular fingerprinting in view of helping to define markers of the tumour grade. Unsupervised multivariate analysis (hierarchical cluster analysis and principal component analysis) of blood vessel spectral data, retrieved from the FPA images, revealed the fine structure of the borderline between two areas identified by a pathologist as grades III and IV. Spectroscopic indicators are found capable of discriminating different areas in the tumour tissue and are proposed as biomolecular markers for potential future use of grading gliomas. [Figure: see text] ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00216-015-8891-z) contains supplementary material, which is available to authorized users. Springer Berlin Heidelberg 2015-07-14 2015 /pmc/articles/PMC4569654/ /pubmed/26168973 http://dx.doi.org/10.1007/s00216-015-8891-z Text en © The Author(s) 2015 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Research Paper Wehbe, Katia Forfar, Isabelle Eimer, Sandrine Cinque, Gianfelice Discrimination between two different grades of human glioma based on blood vessel infrared spectral imaging |
title | Discrimination between two different grades of human glioma based on blood vessel infrared spectral imaging |
title_full | Discrimination between two different grades of human glioma based on blood vessel infrared spectral imaging |
title_fullStr | Discrimination between two different grades of human glioma based on blood vessel infrared spectral imaging |
title_full_unstemmed | Discrimination between two different grades of human glioma based on blood vessel infrared spectral imaging |
title_short | Discrimination between two different grades of human glioma based on blood vessel infrared spectral imaging |
title_sort | discrimination between two different grades of human glioma based on blood vessel infrared spectral imaging |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4569654/ https://www.ncbi.nlm.nih.gov/pubmed/26168973 http://dx.doi.org/10.1007/s00216-015-8891-z |
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