Accurate quantification of in vivo short-echo-time (TE) (1)H spectra must account for contributions from both mobile metabolites and less mobile macromolecules, which can fluctuate in disease. The purpose of this study was to develop an approach for the acquisition and processing of macromolecule information to optimize metabolite quantification accuracy and precision. Human parietal white matter (8-cm(3) voxel) and posterior hippocampus (1.7-cm(3) voxel) metabolite levels were quantified, following manomolecule subtraction, from short-echo-time spectra (TE = 46 ms) acquired at 4.0 Tesla with localization by adiabatic selective refocusing (LASER). Nineteen metabolites were fit using a time domain Levenberg-Marquardt minimization that incorporated prior knowledge of metabolite lineshapes. The macromolecule contribution to the spectrum was reduced by 87% (P < 0.05) when the acquisition of single averages of the full spectrum and macromolecule spectrum were interleaved to reduce subtraction errors due to motion. Subtracting the Hankel Lanczos singular value decomposition (HLSVD) fit of the macromolecule spectrum, which contained no random noise, did not alter quantified metabolite levels but did not increase metabolite quantification precision. Several metabolites had higher concentrations in the posterior hippocampus compared to parietal white matter, which emphasizes the need to carefully control for partial volume contamination in hippocampal spectroscopy studies.
Copyright 2003 Wiley-Liss, Inc.