학술논문

Computational Reproducibility in Metabolite Quantification Applied to Short Echo Time In Vivo MR Spectroscopy
Document Type
Conference
Source
2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI) Biomedical Imaging (ISBI), 2023 IEEE 20th International Symposium on. :1-5 Apr, 2023
Subject
Bioengineering
Computing and Processing
Photonics and Electrooptics
Signal Processing and Analysis
Spectroscopy
In vivo
Analytical models
Computational modeling
Software algorithms
Fitting
Reproducibility of results
reproducibility
quantification
in vivo MR spectroscopy
Language
ISSN
1945-8452
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) within-software (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.