  In vivo metabolite quantification by short echo time MR spectroscopy is a
challenge for which various methods have been proposed. In this study, the
reproducibility of quantification outcomes is questioned at three distinct
levels: (i) between-software (LCModel and cQUEST), (ii) withinsoftware (with
different parameter sets), and (iii) across software executions (when the
fitting algorithm uses random seeds, like cQUEST). After running multiple
quantification tasks on a dedicated platform (VIP), metrics from Bland-Altman
analysis were used to assess the variability of outcomes in signals acquired on
a lysolecithin rat model, from a study on demyelination. Results show
substantial variations at the three levels, allowing for more potent analyses
than from a single parameter set / single software point of view.

Optimization and Control;Methodology