Investigation of the influence of macromolecules and spline baseline in the fitting model of human brain spectra at 9.4T.

PURPOSE: In this study, the influence of experimentally measured macromolecules and spline baseline on the quantification results of proton MRS data was investigated.

METHODS: Proton MRS spectra from the left parietal lobe and the occipital lobe were acquired at 9.4T in the human brain using metabolite-cycled semi-LASER. Then, the left parietal lobe data, along with the occipital lobe, spectra were quantified and the influence of the inclusion of experimentally measured macromolecular basis sets in the fitting model was evaluated. Furthermore, the effect of the stiffness of the fitted spline baselines on the resulting metabolite concentrations was evaluated.

RESULTS: In general, concentrations were higher for metabolites in occipital lobe than the left parietal lobe. The inclusion of an experimentally acquired measured macromolecular basis set from another brain region neither affected the quantification results nor the resulting spline baselines significantly. A highly flexible spline baseline led to overestimation or underestimation of metabolite concentrations. Differences of above 15% in the quantification of metabolite levels for both lobes were observed for several metabolites using LCModel default settings for spline baselines and macromolecules in comparison to stiffer spline baselines.

CONCLUSION: Fitting with the default LCModel macromolecular basis set and spline baseline model had significant influence in the resulting spline baselines, leading to large deviations both in the concentrations and fitted macromolecular components. The number of knots in the spline may create overflexible baselines, which can potentially lead to quantification errors. Interestingly, the interchange of macromolecular basis set between occipital lobe and left parietal lobe spectra had less influence on the quantification results compared to the default LCModel settings.