Brain metabolic pattern analysis using a magnetic resonance spectra classification software in experimental stroke
Jiménez Xarrié, Elena (Institut d'Investigació Biomèdica Sant Pau)
Dávila Huerta, Myriam (Universitat Autònoma de Barcelona. Departament de Bioquímica i de Biologia Molecular)
Candiota Silveira, Ana Paula (Universitat Autònoma de Barcelona. Institut de Biotecnologia i de Biomedicina "Vicent Villar Palasí")
Delgado Mederos, Raquel (Institut d'Investigació Biomèdica Sant Pau)
Ortega-Martorell, Sandra (Liverpool John Moores University. Department of Applied Mathematics)
Julià Sapé, Ma. Margarita (Universitat Autònoma de Barcelona. Departament de Bioquímica i de Biologia Molecular)
Arús i Caraltó, Carles (Universitat Autònoma de Barcelona. Departament de Bioquímica i de Biologia Molecular)
Martí-Fàbregas, Joan (Institut d'Investigació Biomèdica Sant Pau)
Universitat Autònoma de Barcelona

Date:	2017
Abstract:	Magnetic resonance spectroscopy (MRS) provides non-invasive information about the metabolic pattern of the brain parenchyma in vivo. The SpectraClassifier software performs MRS pattern-recognition by determining the spectral features (metabolites) which can be used objectively to classify spectra. Our aim was to develop an Infarct Evolution Classifier and a Brain Regions Classifier in a rat model of focal ischemic stroke using SpectraClassifier. A total of 164 single-voxel proton spectra obtained with a 7 Tesla magnet at an echo time of 12 ms from non-infarcted parenchyma, subventricular zones and infarcted parenchyma were analyzed with SpectraClassifier (). The spectra corresponded to Sprague-Dawley rats (healthy rats, n = 7) and stroke rats at day 1 post-stroke (acute phase, n = 6 rats) and at days 7 ± 1 post-stroke (subacute phase, n = 14). In the Infarct Evolution Classifier, spectral features contributed by lactate + mobile lipids (1. 33 ppm), total creatine (3. 05 ppm) and mobile lipids (0. 85 ppm) distinguished among non-infarcted parenchyma (100% sensitivity and 100% specificity), acute phase of infarct (100% sensitivity and 95% specificity) and subacute phase of infarct (78% sensitivity and 100% specificity). In the Brain Regions Classifier, spectral features contributed by myoinositol (3. 62 ppm) and total creatine (3. 04/3. 05 ppm) distinguished among infarcted parenchyma (100% sensitivity and 98% specificity), non-infarcted parenchyma (84% sensitivity and 84% specificity) and subventricular zones (76% sensitivity and 93% specificity). SpectraClassifier identified candidate biomarkers for infarct evolution (mobile lipids accumulation) and different brain regions (myoinositol content). The online version of this article (doi:10. 1186/s12868-016-0328-x) contains supplementary material, which is available to authorized users.
Grants:	Ministerio de Economía y Competitividad SAF2011-23870 Ministerio de Economía y Competitividad SAF2014-52332-R
Note:	Ajuts: EU FEDER funds Redes Temáticas de Investigación Cooperativa Sanitaria RETICS-INVICTUS-RD12/014/0002
Rights:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Language:	Anglès
Document:	Article ; recerca ; Versió publicada
Subject:	Magnetic resonance spectroscopy ; Metabolomics ; Pattern recognition ; Stroke ; Animal model
Published in:	BMC neuroscience, Vol. 18, issue 1 (Jan. 2017) , art. 13, ISSN 1471-2202

Dades de recerca relacionades amb l'article: https://ddd.uab.cat/record/166606
DOI: 10.1186/s12868-016-0328-x
PMID: 28086802

10 p, 1.4 MB

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Research literature > UAB research groups literature > Research Centres and Groups (research output) > Health sciences and biosciences > Institut de Biotecnologia i de Biomedicina (IBB)
Research literature > UAB research groups literature > Research Centres and Groups (research output) > Health sciences and biosciences > Institut de Recerca Sant Pau
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