Abstract
The aim of this work is to quantify individual and regional differences in the relative concentration of gamma-aminobutyric acid (GABA) in human brain with in vivo magnetic resonance spectroscopy. Spectral editing Mescher–Garwood point resolved spectroscopy (MEGA-PRESS) sequence and GABA analysis toolkit (Gannet) were used to detect and quantify GABA in anterior cingulate cortex (ACC) and occipital cortex (OCC) of healthy volunteers. Residual bootstrap, a model-based statistical analysis technique, was applied to resample the fitting residuals of GABA from the Gaussian fitting model (referred to as GABA+ thereafter) in both individual and group data of ACC and OCC. The inter-subject coefficient of variation (CV) of GABA+ in OCC (20.66 %) and ACC (12.55 %) with residual bootstrap was lower than that of a standard Gaussian model analysis (21.58 % and 16.73 % for OCC and ACC, respectively). The intra-subject uncertainty and CV of OCC were lower than that of ACC in both analyses. The residual bootstrap analysis thus provides a more robust uncertainty estimation of individual and group GABA+ detection in different brain regions, which may be useful in our understanding of GABA biochemistry in brain and its use for the diagnosis of related neuropsychiatric diseases.
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This work was partially supported by the Fundamental Research Funds for the Central Universities under Grant 2013QNA5004.
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Chen, M., Liao, C., Chen, S. et al. Uncertainty assessment of gamma-aminobutyric acid concentration of different brain regions in individual and group using residual bootstrap analysis. Med Biol Eng Comput 55, 1051–1059 (2017). https://doi.org/10.1007/s11517-016-1579-5
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DOI: https://doi.org/10.1007/s11517-016-1579-5