Abstract
Purpose 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.
Methods 277 short-TE spectra from a recent 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), myo-inositol (mI), and glutamate+glutamine (Glx) were quantified with respect to total creatine (tCr).
Results 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 correlation coefficient for all pairs of LCM algorithms across all datasets and metabolites was , 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 ).
Conclusion 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.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
Introduction: Clarified the purpose of the study to compare common current practice and removed redundant algorithm details from the text Methods: Clarified MM and -CrCH2 definition. Added SNR and linewidth investigation and moved the secondary analysis to the supplemental material. Clarified the figure's purpose. Updated the description of the Osprey algorithm Results: Revised figure 2 to include zero lines and the MM only model, shortened figure description. Discussion: Updated sources of variance section about MM background contributions and included optimizer starting values.
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