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Robust quantification of short echo time 1 H magnetic resonance spectra using the Padé approximant
Author(s) -
Williamson David C.,
Hawesa Halima,
Thacker Neil A.,
Williams Stephen R.
Publication year - 2006
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.20842
Subject(s) - monte carlo method , spectral line , echo (communications protocol) , nuclear magnetic resonance , echo time , physics , time domain , in vivo , computational physics , resonance (particle physics) , algorithm , statistical physics , magnetic resonance imaging , mathematics , computer science , statistics , atomic physics , medicine , biology , computer network , microbiology and biotechnology , astronomy , computer vision , radiology
Accurate quantification of in vivo short echo time spectra is hampered by the presence of overlapping peaks and a significant baseline. In this work the Padé approximant in conjunction with Monte Carlo simulation is used to extract peak areas from short echo time 1 H spectra. We exploit the fact that the Padé approximant is known to model broad non‐Lorentzian signals as arbitrary sums of Lorentzian components to separate baseline components from sharper metabolite signals by combining the Padé approximant with Monte Carlo simulation. The simulation results demonstrate that the Padé approximant–Monte Carlo hybrid analysis is able to separate the metabolite signals from the baseline, while a least squares fitting of a time domain model may result in significant bias of the peak area estimations. For the in vivo data the estimates of the peak areas using the Padé approximant and AMARES compare well, with the exception of the NAA peak at 2.02 ppm. We suggest that the discrepancy may be due to the baseline contamination as supported by the simulation results; however, without an in vivo gold standard this remains difficult to demonstrate. Magn Reson Med, 2006. © 2006 Wiley‐Liss, Inc.