Quantification of human brain metabolites from in Vivo 1 H NMR magnitude spectra using automated artificial neural network analysis

Yrjö Hiltunen, Jouni Kaartinen, Juhani Pulkkinen, Anna-Maija Häkkinen, Nina Lundbom, Risto Kauppinen

    Research output: Contribution to journalArticleScientificpeer-review

    22 Citations (Scopus)

    Abstract

    Long echo time (TE =270 ms) in vivo proton NMR spectra resembling human brain metabolite patterns were simulated for lineshape fitting (LF) and quantitative artificial neural network (ANN) analyses. A set of experimental in vivo 1 H NMR spectra were first analyzed by the LF method to match the signal-to-noise ratios and linewidths of simulated spectra to those in the experi-mental data. The performance of constructed ANNs was compared for the peak area determinations of choline-containing compounds (Cho), total creatine (Cr), and N-acetyl aspartate (NAA) signals using both manually phase-corrected and magnitude spectra as in-puts. The peak area data from ANN and LF analyses for simulated spectra yielded high correlation coefficients demonstrating that the peak areas quantified with ANNgave similar results as LF analysis. Thus, a fully automated ANN method based on magnitude spectra has demonstrated potential for quantification of in vivo metabolites from long echo time spectroscopic imaging.
    Original languageEnglish
    Pages (from-to)1-5
    JournalJournal of Magnetic Resonance
    Volume154
    Issue number1
    DOIs
    Publication statusPublished - 2002
    MoE publication typeA1 Journal article-refereed

    Keywords

    • artificial neural network
    • 1H nuclear magnetic resonance spectroscopy
    • NMR spectroscopy
    • brain metabolites
    • metabolites
    • quantification
    • simulated spectra

    Fingerprint Dive into the research topics of 'Quantification of human brain metabolites from in Vivo 1 H NMR magnitude spectra using automated artificial neural network analysis'. Together they form a unique fingerprint.

  • Cite this