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arXiv · 2303.05147

Computational Reproducibility in Metabolite Quantification Applied to Short Echo Time in Vivo MR Spectroscopy

Gaël Vila·Axel Bonnet·Fabien Chauveau·Sophie Gaillard·Françoise Durand-Dubief·Sorina Camarasu-Pop·Helene Ratiney
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Abstract

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.

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Gaël Vila, Axel Bonnet, Fabien Chauveau, Sophie Gaillard, Françoise Durand-Dubief, Sorina Camarasu-Pop, Helene Ratiney. 2023-03-09. Computational Reproducibility in Metabolite Quantification Applied to Short Echo Time in Vivo MR Spectroscopy. https://arxiv.org/abs/2303.05147

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