Quantitation of simulated short echo time ¹H human brain spectra by LCModel and AMARES

Abstract

LCModel and AMARES, two widely used quantitation tools for magnetic resonance spectroscopy (MRS) data, were employed to analyze simulated spectra similar to those typically obtained at short echo times (TEs) in the human brain at 1.5 T. The study focused mainly on the influence of signal-to-noise ratios (SNRs) and different linewidths on the accuracy and precision of the quantification results, and their effectiveness in accounting for the broad signal contribution of macromolecules and lipids (often called the baseline in in vivo MRS). When applied in their standard configuration (i.e., fitting a spline as a baseline for LCModel, and weighting the first data points for AMARES), both methods performed comparably but with their own characteristics. LCModel and AMARES quantitation benefited considerably from the incorporation of baseline information into the prior knowledge. However, the more accurate quantitation of the sum of glutamate and glutamine (Glx) favored the use of LCModel. Metabolite-to-creatine ratios estimated by LCModel with extended prior knowledge are more accurate than absolute concentrations, and are nearly independent of SNR and line broadening. In clinical magnetic resonance spectroscopy (MRS) of the brain, short echo times (TEs) are employed to optimize the signal-to-noise ratio (SNR), reduce signal attenuation due to transverse relaxation and scalar coupling, and enable the quantification of more than the three dominant singlet resonances (i.e., N-acetylaspartate (NAA), creatine (Cr), and choline (Cho)). Generally, it is difficult to quantify short-TE spectra because of the overlapping metabolite signals and the contribution of macromolecule and lipid components. In addition to software of MR tomographs and various in-house developments at research sites (1-3), two sophisticated and well documented software packages are widely used: LCModel (4) and Magnetic Resonance User Interface (MRUI) (5). These software packages are used worldwide by many groups not only because of their availability and performance, but also because they provide results with a broader basis of comparability. The commercially available software package LCModel (6) fits spectra in the frequency domain using a basis set of spectra of in vitro metabolite solutions acquired under conditions identical to those under which in vivo data are acquired. AMARES (7), which is part of the MRUI package (5), has the advantage of being free of charge to nonprofit organizations. This advanced quantitation toolbox analyzes spectra in the time domain utilizing a priori information that can be introduced flexibly. LCModel employs a "black box" approach, and thus requires less user interaction than AMARES.For application purposes, however, it is important to determine how quantitation depends on linewidth and SNR, and how the two methods handle the broad macromolecular and lipid signal contributions. Of course, the best way to account for macromolecular signal contribution is to acquire the macromolecular spectrum by inversion recovery (8) ...

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