Gannet: a batch-processing tool for the quantitative analysis of gamma-aminobutyric acid-edited MR spectroscopy spectra

Edden, Richard A.E., Puts, Nicolaas A.J., Harris, Ashley D., Barker, Peter B. and Evans, Christopher John ORCID: https://orcid.org/0000-0002-6619-4245 2014. Gannet: a batch-processing tool for the quantitative analysis of gamma-aminobutyric acid-edited MR spectroscopy spectra. Journal of Magnetic Resonance Imaging 40 (6) , pp. 1445-1452. 10.1002/jmri.24478

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Abstract

Purpose: The purpose of this study is to describe the Gannet toolkit for the quantitative batch analysis of gamma-aminobutyric acid (GABA) -edited MRS data. Materials and Methods: Using MEGA-PRESS editing and standard acquisition parameters, four MEGA-PRESS spectra were acquired in three brain regions in 10 healthy volunteers. These 120 datasets were processed without user intervention with Gannet, a Matlab-based tool that takes raw time-domain data input, processes it to generate the frequency-domain edited spectrum, and applies a simple modeling procedure to estimate GABA concentration relative to the creatine or, if provided, the unsuppressed water signal. A comparison of four modeling approaches is also presented. Results: All data were successfully processed by Gannet. Coefficients of variation across subjects ranged from 11% for the occipital region to 17% for the dorsolateral prefrontal region. There was no clear difference in fitting performance between the simple Gaussian model used by Gannet and the other more complex models presented. Conclusion: Gannet, the GABA Analysis Toolkit, can be used to process and quantify GABA-edited MRS spectra without user intervention.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Cardiff University Brain Research Imaging Centre (CUBRIC) Medicine Psychology
Subjects:	R Medicine > R Medicine (General)
Publisher:	John Wiley & Sons
ISSN:	1053-1807
Date of Acceptance:	28 September 2013
Last Modified:	31 Oct 2022 09:02
URI:	https://orca.cardiff.ac.uk/id/eprint/79617

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