Factors affecting the quantification of short echoin-vivo1H MR spectra: prior knowledge, peak elimination, and filtering

Short echo 1H in-vivo brain MR spectra are difficult to quantify for several reasons: low signal to noise ratio, the severe overlap of spectral lines, the presence of macromolecule resonances beneath the resonances of interest, and the effect of resonances adjacent to the spectral region of interest (SRI). This paper outlines several different quantification strategies and the effect of each on the precision of in-vivo metabolite measurements. In-vivo spectra were quantified with no operator interaction using a template of prior knowledge determined by mathematically modeling separate in-vitro metabolite spectra. Metabolite level estimates and associated precision were compared before and after the inclusion of macromolecule resonances as part of the prior knowledge, and following two different methods of handling resonances adjacent to the SRI. The effects of rectangular and exponential filters were also investigated. All methods were tested using repeated in-vivo spectra from one individual acquired at 1.5 T using stimulated echo acquisition mode (STEAM, TE = 20 ms) localization. The results showed that the inclusion of macromolecules in the prior knowledge was necessary to obtain metabolite levels consistent with the literature, while the fitting of resonances adjacent to the SRI concurrent with modeled metabolites optimized the precision of metabolite estimates. Metabolite levels and precision were also affected by rectangular and exponential filtering, suggesting caution must be taken when such filters are used.