Which prior knowledge? Quantification of in vivo brain (13) C MR spectra following (13) C glucose infusion using AMARES
The recent developments in high magnetic field (13) C magnetic resonance spectroscopy with improved localization and shimming techniques have led to important gains in sensitivity and spectral resolution of (13) C in vivo spectra in the rodent brain, enabling the separation of several (13) C isotopomers of glutamate and glutamine. In this context, the assumptions used in spectral quantification might have a significant impact on the determination of the (13) C concentrations and the related metabolic fluxes. In this study, the time domain spectral quantification algorithm AMARES (advanced method for accurate, robust and efficient spectral fitting) was applied to (13) C magnetic resonance spectroscopy spectra acquired in the rat brain at 9.4 T, following infusion of [1,6-(13) C(2) ] glucose. Using both Monte Carlo simulations and in vivo data, the goal of this work was: (1) to validate the quantification of in vivo (13) C isotopomers using AMARES; (2) to assess the impact of the prior knowledge on the quantification of in vivo (13) C isotopomers using AMARES; (3) to compare AMARES and LCModel (linear combination of model spectra) for the quantification of in vivo (13) C spectra. AMARES led to accurate and reliable (13) C spectral quantification similar to those obtained using LCModel, when the frequency shifts, J-coupling constants and phase patterns of the different (13) C isotopomers were included as prior knowledge in the analysis. Magn Reson Med, 2012. © 2012 Wiley Periodicals, Inc.