Brain metabolic pattern analysis using a magnetic resonance spectra classification software in experimental stroke

Elena Jiménez-Xarrié, Myriam Davila, Ana Paula Candiota, Raquel Delgado-Mederos, Sandra Ortega-Martorell, Margarida Julià-Sapé, Carles Arús*, Joan Martí-Fàbregas

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

Abstract

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).

Original languageAmerican English
Article number13
JournalBMC Neuroscience
Volume18
Issue number1
DOIs
Publication statusPublished - 13 Jan 2017

Keywords

  • Animal model
  • Magnetic resonance spectroscopy
  • Metabolomics
  • Pattern recognition
  • Stroke

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