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

J Magn Reson Imaging. 2014 Dec;40(6):1445-52. doi: 10.1002/jmri.24478. Epub 2013 Nov 13.


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.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Adult
  • Algorithms*
  • Brain / metabolism*
  • Data Interpretation, Statistical*
  • Female
  • Humans
  • Magnetic Resonance Spectroscopy / methods*
  • Male
  • Numerical Analysis, Computer-Assisted
  • Programming Languages*
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Software*
  • Tissue Distribution
  • gamma-Aminobutyric Acid / metabolism*


  • gamma-Aminobutyric Acid