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

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 region...

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Publicado en:Journal of Magnetic Resonance Imaging Vol. 40; no. 6; pp. 1445 - 1453
Autores principales: Edden, Richard A E, Puts, Nicolaas A J, Harris, Ashley D, Barker, Peter B, Evans, C John
Formato: research Journal Article
Publicado: Wiley-Blackwell Dec2014
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Dec2014
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      pub: Wiley-Blackwell
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        10.1002/jmri.24478
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        atl: Gannet: A batch-processing tool for the quantitative analysis of gamma-aminobutyric acid–edited MR spectroscopy spectra.
      aug:
        au:
          Edden, Richard A E
          Puts, Nicolaas A J
          Harris, Ashley D
          Barker, Peter B
          Evans, C John
      sug:
        subj:
          Algorithms
          Brain Metabolism
          Data Analysis, Statistical
          Magnetic Resonance Spectroscopy Methods
          Programming Languages
          Software
          GABA Metabolism
          Adult
          Female
          Human
          Male
          Computing Methodologies
          Reproducibility of Results
          Sensitivity and Specificity
          Adult: 19-44 years
          Female
          Male
      ab: 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.
      pubtype: Academic Journal
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        research
        Journal Article
      ougenre: Article
    language: English
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