Comparison of different linear-combination modelling algorithms for short-TE proton spectra

Abstract

Short-TE proton MRS is used to study metabolism in the human brain. Common analysis methods model the data as linear combination of metabolite basis spectra. This large-scale multi-site study compares the levels of the four major metabolite complexes in short-TE spectra estimated by three linear-combination modelling (LCM) algorithms. 277 medial parietal lobe short-TE PRESS spectra (TE = 35 ms) from a recent 3T multi-site study were pre-processed with the Osprey software. The resulting spectra were modelled with Osprey, Tarquin and LCModel, using the same three vendor-specific basis sets (GE, Philips, and Siemens) for each algorithm. Levels of total N-acetylaspartate (tNAA), total choline (tCho), myoinositol (mI), and glutamate+glutamine (Glx) were quantified with respect to total creatine (tCr). Group means and CVs of metabolite estimates agreed well for tNAA and tCho across vendors and algorithms, but substantially less so for Glx and mI, with mI systematically estimated lower by Tarquin. The cohort mean coefficient of determination for all pairs of LCM algorithms across all datasets and metabolites was [Formula], indicating generally only moderate agreement of individual metabolite estimates between algorithms. There was a significant correlation between local baseline amplitude and metabolite estimates (cohort mean [Formula]). While mean estimates of major metabolite complexes broadly agree between linear-combination modelling algorithms at group level, correlations between algorithms are only weak-to-moderate, despite standardized pre-processing, a large sample of young, healthy and cooperative subjects, and high spectral quality. These findings raise concerns about the comparability of MRS studies, which typically use one LCM software and much smaller sample sizes. Graphical Abstract O_TBL View this table: org.highwire.dtl.DTLVardef@6775bdorg.highwire.dtl.DTLVardef@62f27borg.highwire.dtl.DTLVardef@1d77ccorg.highwire.dtl.DTLVardef@a4049aorg.highwire.dtl.DTLVardef@2a1feb_HPS_FORMAT_FIGEXP M_TBL C_TBL Three linear-combination algorithms (Osprey, Tarquin and LCMode) were used to quantify the levels of tNAA, tCho, mI, and Glx in 277 short-TE PRESS. Group means and CVs of metabolite estimates agreed well for tNAA and tCho, but substantially less so for Glx and mI with a cohort mean correlation coefficient of [Formula], indicating moderate agreement between algorithms. These findings raise concerns about the comparability of MRS studies, which typically use one LCM software and much smaller sample sizes.