## 3 Results
Therefore, one cannot expect to scan the water unsuppressed signal for one of the brain's region and consider that measurement provides a constant internal reference across the whole brain. Hence, for accurate metabolite concentration calculation, one must scan both waters, suppressed and unsuppressed, for each selected voxel. For the brain regions, (IP and PCC), metabolite concentrations were calculated while using both the proposed approach and the TARQUIN. For each metabolite average and 95% confidence interval over each region were calculated and compared. Based on our observation, TARQUIN does not calculate some of the metabolite's concentration (e.g., glycerol, valine, taurine and ATP) and also underestimates some other metabolites (e.g., glucose, Scylla-inositol, alanine, and glutamine). In the latter case, the metabolites concentration is either zero or very close to zero. Therefore, comparing the results for those metabolites is not possible. Figure 5 represents MR spectra of the one of the subjects' brain (PCC region), and the fitted model of the proposed approach along with the TARQUIN model. In Table 4, a comparison between our results and TARQUIN is provided. For each metabolite mean and 95% confidence interval of its concentration over all subjects within each selected brain are shown. For those metabolites with relatively high concentration, (i.e., NAA or creatine), the confidence interval is larger, relatively. Confidence interval can be a criterion to measure the consistency of the results because no ground truth is available for an in vivo data. The confidence intervals and the means are not unalike, except for Glutamate, as shown in Table 4. The TARQUIN results for glutamate vary significantly from our approach. One possible resolution can be the GLX metabolite concentration (i.e., Glutamate, Glutathione, and Glutamine). Because TARQUIN reports a very small concentration for Glutamine for all the subjects; therefore, its concentration might be assigned under the umbrella of GLX. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Metabolite** & **Concentration (Proposed)** & **Concentration (TARQUIN)** & **Ground Truth** \\ \hline NAA & \(\mathbf{12.65\pm 0.31}\) & \(11.73\pm 0.16\) & 12.5 \\ Creatine & \(\mathbf{10.08\pm 0.27}\) & \(9.32\pm 0.21\) & 10.0 \\ Choline & \(2.79\pm 0.14\) & \(\mathbf{2.94\pm 0.19}\) & 3.0 \\ Myo-inositol & \(\mathbf{7.56\pm 0.42}\) & \(8.13\pm 0.32\) & 7.5 \\ GABA & \(\mathbf{3.00\pm 0.17}\) & \(2.40\pm 0.72\) & 3.0 \\ Lactate & \(\mathbf{4.66\pm 0.21}\) & \(2.81\pm 0.24\) & 5.0 \\ Glutamate & \(\mathbf{12.8\pm 0.55}\) & \(13.64\pm 0.47\) & 12.5 \\ Glutathione & \(3.78\pm 0.18\) & \(\mathbf{4.71\pm 0.27}\) & 5.0 \\ Glutamine & \(4.85\pm 0.26\) & \(\mathbf{5.27\pm 0.12}\) & 6.0 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Mean and 95% confidence interval of the phantom’s metabolite concentration quantified by the proposed approach and the TARQUIN. Full width half maximum (FWHM) also can be considered as another comparison criterion. FWHM for metabolites should be less than 0.1 ppm [9]. This fact is considered as a peak matching criterion, such that large FWHM indicates poor peak matching. The FWHM for all of the metabolites are calculated while using both the proposed approach and TARQUIN. The average of FWHM for TARQUIN and the proposed approach are 0.0375 and 0.0404 ppm, respectively.