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, 2013. © 2012 Wiley Periodicals, Inc.