Comparison of linear combination modeling strategies for GABA-edited MRS at 3T

Abstract

PurposeJ-difference-edited spectroscopy is a valuable approach for the in vivo detection of {gamma}-aminobutyric-acid (GABA) with MRS. A recent expert consensus article recommends linear combination modeling (LCM) of edited MRS but does not give specific details of implementation. This study explores different modeling strategies to adapt LCM for GABA-edited MRS. Methods61 medial parietal lobe GABA-edited MEGA-PRESS spectra from a recent 3T multi-site study were modeled using 102 different strategies combining six different approaches to account for co-edited macromolecules, three modeling ranges, three baseline knot spacings, and the use of basis sets with or without homocarnosine. The resulting GABA and GABA+ estimates (quantified relative to total creatine), the residuals at different ranges, SDs and CVs, and Akaike information criteria, were used to evaluate the models performance. ResultsSignificantly different GABA+ and GABA estimates were found when a well-parameterized MM3co basis function was included in the model. The mean GABA estimates were significantly lower when modeling MM, while the CVs were similar. A sparser spline knot spacing led to lower variation in the GABA and GABA+ estimates, and a narrower modeling range - only including the signals of interest - did not substantially improve or degrade modeling performance. Additionally, results suggest that LCM can separate GABA and the underlying co-edited MM3co. Incorporating homocarnosine into the modeling did not significantly improve variance in GABA+ estimates. ConclusionGABA-edited MRS is most appropriately quantified by LCM with a well-parameterized co-edited MM3co basis function with a constraint to the non-overlapped MM0.93, in combination with a sparse spline knot spacing (0.55 ppm) and a modeling range between 0.5 and 4 ppm. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=76 SRC="FIGDIR/small/445817v3_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@129ce60org.highwire.dtl.DTLVardef@1ac3797org.highwire.dtl.DTLVardef@1759d69org.highwire.dtl.DTLVardef@b190a3_HPS_FORMAT_FIGEXP M_FIG C_FIG 102 strategies to model GABA-edited MRS with linear combination modeling were evaluated to quantify GABA and GABA+ in Osprey. Significantly different GABA and GABA+ estimates were found when a well-parameterized macro-molecule at 3 ppm was included. The findings suggest that linear combination modeling needs to be adapted for quantification of GABA-edited MRS.