Classification of brain tumor extracts by high resolution ¹H MRS using partial least squares discriminant analysis

Detalhes bibliográficos
Autor(a) principal: Faria,A.V.
Data de Publicação: 2011
Outros Autores: Macedo Jr.,F.C., Marsaioli,A.J., Ferreira,M.M.C., Cendes,F.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Brazilian Journal of Medical and Biological Research
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-879X2011000200009
Resumo: High resolution proton nuclear magnetic resonance spectroscopy (¹H MRS) can be used to detect biochemical changes in vitro caused by distinct pathologies. It can reveal distinct metabolic profiles of brain tumors although the accurate analysis and classification of different spectra remains a challenge. In this study, the pattern recognition method partial least squares discriminant analysis (PLS-DA) was used to classify 11.7 T ¹H MRS spectra of brain tissue extracts from patients with brain tumors into four classes (high-grade neuroglial, low-grade neuroglial, non-neuroglial, and metastasis) and a group of control brain tissue. PLS-DA revealed 9 metabolites as the most important in group differentiation: γ-aminobutyric acid, acetoacetate, alanine, creatine, glutamate/glutamine, glycine, myo-inositol, N-acetylaspartate, and choline compounds. Leave-one-out cross-validation showed that PLS-DA was efficient in group characterization. The metabolic patterns detected can be explained on the basis of previous multimodal studies of tumor metabolism and are consistent with neoplastic cell abnormalities possibly related to high turnover, resistance to apoptosis, osmotic stress and tumor tendency to use alternative energetic pathways such as glycolysis and ketogenesis.
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spelling Classification of brain tumor extracts by high resolution ¹H MRS using partial least squares discriminant analysisBrainTumorMagnetic resonance spectroscopySpectroscopyMetabolismHigh resolution proton nuclear magnetic resonance spectroscopy (¹H MRS) can be used to detect biochemical changes in vitro caused by distinct pathologies. It can reveal distinct metabolic profiles of brain tumors although the accurate analysis and classification of different spectra remains a challenge. In this study, the pattern recognition method partial least squares discriminant analysis (PLS-DA) was used to classify 11.7 T ¹H MRS spectra of brain tissue extracts from patients with brain tumors into four classes (high-grade neuroglial, low-grade neuroglial, non-neuroglial, and metastasis) and a group of control brain tissue. PLS-DA revealed 9 metabolites as the most important in group differentiation: γ-aminobutyric acid, acetoacetate, alanine, creatine, glutamate/glutamine, glycine, myo-inositol, N-acetylaspartate, and choline compounds. Leave-one-out cross-validation showed that PLS-DA was efficient in group characterization. The metabolic patterns detected can be explained on the basis of previous multimodal studies of tumor metabolism and are consistent with neoplastic cell abnormalities possibly related to high turnover, resistance to apoptosis, osmotic stress and tumor tendency to use alternative energetic pathways such as glycolysis and ketogenesis.Associação Brasileira de Divulgação Científica2011-02-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-879X2011000200009Brazilian Journal of Medical and Biological Research v.44 n.2 2011reponame:Brazilian Journal of Medical and Biological Researchinstname:Associação Brasileira de Divulgação Científica (ABDC)instacron:ABDC10.1590/S0100-879X2010007500146info:eu-repo/semantics/openAccessFaria,A.V.Macedo Jr.,F.C.Marsaioli,A.J.Ferreira,M.M.C.Cendes,F.eng2016-09-26T00:00:00Zoai:scielo:S0100-879X2011000200009Revistahttps://www.bjournal.org/https://old.scielo.br/oai/scielo-oai.phpbjournal@terra.com.br||bjournal@terra.com.br1414-431X0100-879Xopendoar:2016-09-26T00:00Brazilian Journal of Medical and Biological Research - Associação Brasileira de Divulgação Científica (ABDC)false
dc.title.none.fl_str_mv Classification of brain tumor extracts by high resolution ¹H MRS using partial least squares discriminant analysis
title Classification of brain tumor extracts by high resolution ¹H MRS using partial least squares discriminant analysis
spellingShingle Classification of brain tumor extracts by high resolution ¹H MRS using partial least squares discriminant analysis
Faria,A.V.
Brain
Tumor
Magnetic resonance spectroscopy
Spectroscopy
Metabolism
title_short Classification of brain tumor extracts by high resolution ¹H MRS using partial least squares discriminant analysis
title_full Classification of brain tumor extracts by high resolution ¹H MRS using partial least squares discriminant analysis
title_fullStr Classification of brain tumor extracts by high resolution ¹H MRS using partial least squares discriminant analysis
title_full_unstemmed Classification of brain tumor extracts by high resolution ¹H MRS using partial least squares discriminant analysis
title_sort Classification of brain tumor extracts by high resolution ¹H MRS using partial least squares discriminant analysis
author Faria,A.V.
author_facet Faria,A.V.
Macedo Jr.,F.C.
Marsaioli,A.J.
Ferreira,M.M.C.
Cendes,F.
author_role author
author2 Macedo Jr.,F.C.
Marsaioli,A.J.
Ferreira,M.M.C.
Cendes,F.
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Faria,A.V.
Macedo Jr.,F.C.
Marsaioli,A.J.
Ferreira,M.M.C.
Cendes,F.
dc.subject.por.fl_str_mv Brain
Tumor
Magnetic resonance spectroscopy
Spectroscopy
Metabolism
topic Brain
Tumor
Magnetic resonance spectroscopy
Spectroscopy
Metabolism
description High resolution proton nuclear magnetic resonance spectroscopy (¹H MRS) can be used to detect biochemical changes in vitro caused by distinct pathologies. It can reveal distinct metabolic profiles of brain tumors although the accurate analysis and classification of different spectra remains a challenge. In this study, the pattern recognition method partial least squares discriminant analysis (PLS-DA) was used to classify 11.7 T ¹H MRS spectra of brain tissue extracts from patients with brain tumors into four classes (high-grade neuroglial, low-grade neuroglial, non-neuroglial, and metastasis) and a group of control brain tissue. PLS-DA revealed 9 metabolites as the most important in group differentiation: γ-aminobutyric acid, acetoacetate, alanine, creatine, glutamate/glutamine, glycine, myo-inositol, N-acetylaspartate, and choline compounds. Leave-one-out cross-validation showed that PLS-DA was efficient in group characterization. The metabolic patterns detected can be explained on the basis of previous multimodal studies of tumor metabolism and are consistent with neoplastic cell abnormalities possibly related to high turnover, resistance to apoptosis, osmotic stress and tumor tendency to use alternative energetic pathways such as glycolysis and ketogenesis.
publishDate 2011
dc.date.none.fl_str_mv 2011-02-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-879X2011000200009
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-879X2011000200009
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S0100-879X2010007500146
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Associação Brasileira de Divulgação Científica
publisher.none.fl_str_mv Associação Brasileira de Divulgação Científica
dc.source.none.fl_str_mv Brazilian Journal of Medical and Biological Research v.44 n.2 2011
reponame:Brazilian Journal of Medical and Biological Research
instname:Associação Brasileira de Divulgação Científica (ABDC)
instacron:ABDC
instname_str Associação Brasileira de Divulgação Científica (ABDC)
instacron_str ABDC
institution ABDC
reponame_str Brazilian Journal of Medical and Biological Research
collection Brazilian Journal of Medical and Biological Research
repository.name.fl_str_mv Brazilian Journal of Medical and Biological Research - Associação Brasileira de Divulgação Científica (ABDC)
repository.mail.fl_str_mv bjournal@terra.com.br||bjournal@terra.com.br
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