Improvement of Aspartate-Signal Fitting Accuracy in Asp-Edited MEGA-PRESS Spectra

Changes in the aspartate (Asp) concentration are potential biomarkers of malate–aspartate shuttle dysfunction as well as the disturbances in the synthesis of NAA. J-difference editing can be utilized to detect a resolved Asp signal at δ Asp ≈ 2.72 ppm. However, as this resonance has a complex shape, fitting of the Asp signal is challenging. In our study, we compare the performance of four Asp fitting models applied to data from three brain regions: the anterior cingulate gyrus (ACC), frontal white matter (DLPFA), and early visual cortex (VC). As a result, fitting with the phantom and simulated spectra can be recommended for robust Asp quantification spectra. This conclusion based on flexibility and suitability of these approaches for Asp fitting for all range of SNR. One gauss model shows the worst performance and could not be recommended for total Asp fitting. The absolute concentrations of Asp are quantified using a modified phantom calibration method. As a result, the estimated Asp concentrations are as close as possible to the biochemical estimations. The quantified Asp and tCr concentrations are, respectively, 1.69 ± 0.18 and 7.43 ± 0.71 for the ACC, 0.93 ± 0.14 and 5.86 ± 0.41 for the DLPFA, and 1.33 ± 0.35 and 8.4 ± 0.64 for the VC. Regional Asp variations in the brain are discovered; the Asp gray matter (GM) concentrations are higher than that in the white matter, and the Asp concentrations in the VC are significantly lower than that in the ACC, although the GM ratio is equal in all these regions.