Quantification of non-water-suppressed MR spectra with correction for motion-induced signal reduction

Jyh Miin Lin, Shang Yueh Tsai*, Hua Shan Liu, Hsiao Wen Chung, Robert V. Mulkern, Chou Min Cheng, Tzu Chen Yeh, Nan Kuei Chen

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

16 Scopus citations

Abstract

Intrascan subject movement in clinical MR spectroscopic examinations may result in inconsistent water suppression that distorts the metabolite signals, frame-to-frame variations in spectral phase and frequency, and consequent reductions in the signal-to-noise ratio due to destructive averaging. Frame-to-frame phase/frequency corrections, although reported to be successful in achieving constructive averaging, rely on consistent water suppression, which may be difficult in the presence of intrascan motion. In this study, motion correction using non-water-suppressed data acquisition is proposed to overcome the above difficulties. The time-domain matrix-pencil postprocessing method was used to extract water signals from the non-water-suppressed spectroscopic data, followed by phase and frequency corrections of the metabolite signals based on information obtained from the water signals. From in vivo experiments on seven healthy subjects at 3.0 T, quantification of metabolites using the unsuppressed water signal as a reference showed improved correlation with water-suppressed data acquired in the absence of motion (R2 = 0.9669; slope = 0.94). The metabolite concentrations derived using the proposed approach were in good agreement with literature values. Computer simulations under various degrees of frequency and phase variations further demonstrated robust performance of the time-domain postprocessing approach.

Original languageEnglish
Pages (from-to)1394-1403
Number of pages10
JournalMagnetic Resonance in Medicine
Volume62
Issue number6
DOIs
StatePublished - 12 2009

Keywords

  • In vivo single voxel spectroscopy
  • Motion correction
  • Non-water suppressed MRS
  • Signal restoration
  • Spectral processing

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