ArticleNMR in biomedicine2022
Comparison of seven modelling algorithms for γ-aminobutyric acid-edited proton magnetic resonance spectroscopy.
Article in NMR in biomedicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 2 of them syntheses that pooled it.
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Who cites it
29 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Functional MRS studies of GABA and glutamate/Glx - A systematic review and meta-analysis.Neuroscience and biobehavioral reviews · 2023Pooled it
- Brain metabolite alterations related to alcohol use: a meta-analysis of proton magnetic resonance spectroscopy studies.Molecular psychiatry · 2022Pooled it
- Methodological comparison of fetal brainExperimental physiology · 2026Article
- Concurrent Multimodal Imaging Demonstrates That EEG-Based Excitation/Inhibition Balance Reflects Glutamate and GABA Balance.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026Article
- A data-driven algorithm to determineMagnetic resonance in medicine · 2026Article
- MRS-Sim: Open-Source Framework for Simulating In Vivo-Like Magnetic Resonance Spectra.NMR in biomedicine · 2025Article
- Regional Excitatory-Inhibitory Balance Relates to Self-Reference Effect on Recollection via the Precuneus/Posterior Cingulate Cortex-Medial Prefrontal Cortex Connectivity.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Chemical shift and relaxation regularization improve the accuracy ofMagnetic resonance in medicine · 2025Article
- Metabolite TMagnetic resonance in medicine · 2025Article
- Age-related GABA- and glutamatergic differences in SMA during bimanual coordination.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- GABA, Glx, and GSH in the cerebellum: their role in motor performance and learning across age groups.Frontiers in aging neuroscience · 2025Article
- PyAMARES, an Open-Source Python Library for Fitting Magnetic Resonance Spectroscopy Data.Diagnostics (Basel, Switzerland) · 2024Article
- Model-based frequency-and-phase correction ofMagnetic resonance in medicine · 2024Article
- GABA-edited MEGA-PRESS at 3 T: Does a measured macromolecule background improve linear combination modeling?Magnetic resonance in medicine · 2024Article
- Simultaneous multi-transient linear-combination modeling of MRS data improves uncertainty estimation.Magnetic resonance in medicine · 2024Article
- The relationship between visual acuity loss and GABAergic inhibition in amblyopia.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- The impact of spectral basis set composition on estimated levels of cingulate glutamate and its associations with different personality traits.BMC psychiatry · 2024Article
- Impact of acquisition and modeling parameters on the test-retest reproducibility of edited GABA.NMR in biomedicine · 2024Article
- Model-based frequency-and-phase correction ofbioRxiv : the preprint server for biology · 2024Article
- Brain glutathione and GABA+ levels in autistic children.Autism research : official journal of the International Society for Autism Research · 2024Article
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Authors and funding
17 authors.
Funding
Abstract
Edited MRS sequences are widely used for studying γ-aminobutyric acid (GABA) in the human brain. Several algorithms are available for modelling these data, deriving metabolite concentration estimates through peak fitting or a linear combination of basis spectra. The present study compares seven such algorithms, using data obtained in a large multisite study. GABA-edited (GABA+, TE = 68 ms MEGA-PRESS) data from 222 subjects at 20 sites were processed via a standardised pipeline, before modelling with FSL-MRS, Gannet, AMARES, QUEST, LCModel, Osprey and Tarquin, using standardised vendor-specific basis sets (for GE, Philips and Siemens) where appropriate. After referencing metabolite estimates (to water or creatine), systematic differences in scale were observed between datasets acquired on different vendors' hardware, presenting across algorithms. Scale differences across algorithms were also observed. Using the correlation between metabolite estimates and voxel tissue fraction as a benchmark, most algorithms were found to be similarly effective in detecting differences in GABA+. An interclass correlation across all algorithms showed single-rater consistency for GABA+ estimates of around 0.38, indicating moderate agreement. Upon inclusion of a basis set component explicitly modelling the macromolecule signal underlying the observed 3.0 ppm GABA peaks, single-rater consistency improved to 0.44. Correlation between discrete pairs of algorithms varied, and was concerningly weak in some cases. Our findings highlight the need for consensus on appropriate modelling parameters across different algorithms, and for detailed reporting of the parameters adopted in individual studies to ensure reproducibility and meaningful comparison of outcomes between different studies.
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