Brain metabolic pattern analysis using a magnetic resonance spectra classification software in experimental stroke.
Background: 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 classif...
| Publicado en: | BMC Neuroscience Vol. 18; pp. 1 - 11 |
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| Autores principales: | , , , , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
BioMed Central
1/13/2017
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=120728947&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 120728947 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 14712202 1CI8 jtl: BMC Neuroscience issn: 14712202 maglogo: N pubinfo: dt: 1/13/2017 vid: 18 pid: 24147 pub: BioMed Central artinfo: ui: 120728947 120728947 NLM28086802 120728947 10.1186/s12868-016-0328-x NLM28086802 120728947 ppf: 1 ppct: 10 formats: tig: atl: Brain metabolic pattern analysis using a magnetic resonance spectra classification software in experimental stroke. aug: au: Jiménez-Xarrié, Elena Davila, Myriam Paula Candiota, Ana Delgado-Mederos, Raquel Ortega-Martorell, Sandra Juliú-Sapé, Margarida Arús, Carles Martí-Fábregas, Joan Candiota, Ana Paula Julià-Sapé, Margarida Martí-Fàbregas, Joan affil: Stroke Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, IIB-Sant Pau, Sant Antoni Maria Claret 167, 08025 Barcelona, Spain sug: subj: Magnetic Resonance Spectroscopy Image Processing, Computer Assisted Methods Software Cerebral Ischemia Classification Stroke Classification Brain Metabolism Inositol Metabolism Brain Lactic Acid Metabolism Metabolism Cerebral Ischemia Cerebral Ischemia Metabolism Creatine Metabolism Rats Sensitivity and Specificity Biochemistry Methods Stroke Metabolism Animal Studies Lipid Metabolism, Inborn Errors Stroke ab: Background: 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.Results: 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 ( http://gabrmn.uab.es/?q=sc ). 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).Conclusion: SpectraClassifier identified candidate biomarkers for infarct evolution (mobile lipids accumulation) and different brain regions (myoinositol content). pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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