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An automated algorithm for combining multivoxel MRS data acquired with phased-array coils.

Nimrod Maril·Robert E Lenkinski
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Abstract

PURPOSE: To develop a fully automated algorithm for combining multivoxel magnetic resonance spectroscopy (MRS) data acquired with a phased-array coil. MATERIALS AND METHODS: The frequency-domain fitting method of LCModel (Provencher SW, Magn Reson Med 1993;30:672-679) was utilized to analyze the individual data sets. The phase corrections and the metabolite areas were then extracted from the LCModel output files for each individual spectrum. These areas were used to determine the dominant metabolite for each spatial location and to combine the individual spectra in a weighted manner. RESULTS: The combination of MRS data acquired from a phantom and the brains of normal volunteers with a four array coil yielded improved signal-to-noise ratio (SNR) in all voxels. The average improvement in SNR of the combined spectrum, as compared with the best of the individual spectra at each spatial location, was 1.4. In the phantom, the predicted SNR improvement of two-fold was achieved at the center of the sample. In the brain, the maximum improvement was 1.8, due to sampling of the ventricles in the center of the sample. CONCLUSION: The method described in this report provides a means for employing phased-array coils in MRS with the same advantages as those found in MRI.

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AlgorithmsBrainHumansImage Processing, Computer-AssistedIn Vitro TechniquesMagnetic Resonance SpectroscopyPhantoms, ImagingReference ValuesJournal ArticleResearch Support, N.I.H., ExtramuralResearch Support, U.S. Gov't, P.H.S.

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Nimrod Maril, Robert E Lenkinski. 2005. An automated algorithm for combining multivoxel MRS data acquired with phased-array coils.. https://doi.org/10.1002/jmri.20261

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