Robust analysis of short echo time 1H MRSI of human brain

X. P. Zhu, K. Young, A. Ebel, B. J. Sober, L. Kaiser, G. Matson, W. M. Weiner, Norbert Schuff*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Short echo time proton MR Spectroscopic Imaging (MRSI) suffers from low signal-to-noise ratio (SNR), limiting accuracy to estimate metabolite intensities. A method to coherently sum spectra in a region of interest of the human brain by appropriate peak alignment was developed to yield a mean spectrum with increased SNR. Furthermore, principal component (PC) spectra were calculated to estimate the variance of the mean spectrum. The mean or alternatively the first PC (PC1) spectrum from the same region can be used for quantitation of peak areas of metabolites in the human brain at increased SNR. Monte Carlo simulations showed that both mean and PC1 spectra were more accurate in estimating regional metabolite concentrations than solutions that regress individual spectra against the tissue compositions of MRSI voxels. Back-to-back MRSI studies on 10 healthy volunteers showed that mean spectra markedly improved reliability of brain metabolite measurements, most notably for myo-inositol, as compared to regression methods.

Original languageEnglish
Pages (from-to)706-711
Number of pages6
JournalMagnetic Resonance in Medicine
Volume55
Issue number3
DOIs
StatePublished - Mar 2006
Externally publishedYes

Keywords

  • Brain
  • Noise reduction
  • Principal component analysis
  • Short TE magnetic resonance spectroscopic imaging
  • Spectroscopy

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