• DocumentCode
    1830940
  • Title

    Comparison of two strategies of background-accommodation: Influence on the metabolite concentration estimation from in vivo Magnetic Resonance Spectroscopy data

  • Author

    Cudalbu, C. ; Bucur, A. ; Graveron-Demilly, D. ; Beuf, O. ; Cavassila, S.

  • Author_Institution
    CNRS, Villeurbanne
  • fYear
    2007
  • fDate
    22-26 Aug. 2007
  • Firstpage
    2077
  • Lastpage
    2080
  • Abstract
    Localized proton magnetic resonance spectroscopy brain signals acquired at short echo-time contain contributions from metabolites, water and a ´background´ which mainly originates from macromolecules and lipids. The purpose of the present study was to compare the influence of the background-accommodation strategy on the metabolite concentration estimates. Two strategies were investigated to accommodate the background, 1) the measured background signal was incorporated in the metabolite basis-set; and 2) the background signal was estimated and subtracted from the in vivo signal using Subtract-QUEST. The influence of the background-accommodation strategy was addressed with the aid of Monte Carlo and in vivo studies. For the considered signals of this study, the concentration estimates obtained using the first approach were below those obtained with Subtract-QUEST. Indeed, the presence of residual contribution of metabolite signals with short longitudinal relaxation times (T1) in the measured background led to an underestimation of metabolite concentration estimates. Conversely, the observed underestimation of the background contribution using Subtract-QUEST led to an overestimation of the metabolite estimates.
  • Keywords
    Monte Carlo methods; NMR spectroscopy; biochemistry; biomedical NMR; brain; chemical variables measurement; medical signal processing; proton magnetic resonance; spectrochemical analysis; Monte Carlo method; Subtract-QUEST; background signal measurement; background-accommodation strategies; brain signals; in vivo proton magnetic resonance spectroscopy data; in vivo signal subtraction; lipids; longitudinal relaxation time; macromolecules; metabolite basis-set; metabolite concentration estimation; Animals; Coils; Frequency domain analysis; In vivo; Lipidomics; Magnetic resonance; Mathematical model; Polynomials; Protons; Spectroscopy; Algorithms; Animals; Brain; Data Interpretation, Statistical; Equipment Design; Magnetic Resonance Spectroscopy; Metabolism; Models, Statistical; Monte Carlo Method; Protons; Rats; Rats, Sprague-Dawley; Signal Processing, Computer-Assisted; Software; Water;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE
  • Conference_Location
    Lyon
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-0787-3
  • Type

    conf

  • DOI
    10.1109/IEMBS.2007.4352730
  • Filename
    4352730