Literature DB >> 28882635

Impact of tissue correction strategy on GABA-edited MRS findings.

Eric C Porges1, Adam J Woods2, Damon G Lamb3, John B Williamson3, Ronald A Cohen1, Richard A E Edden4, Ashley D Harris5.   

Abstract

Tissue composition impacts the interpretation of magnetic resonance spectroscopy metabolite quantification. The goal of applying tissue correction is to decrease the dependency of metabolite concentrations on the underlying voxel tissue composition. Tissue correction strategies have different underlying assumptions to account for different aspects of the voxel tissue fraction. The most common tissue correction is the CSF-correction that aims to account for the cerebrospinal fluid (CSF) fraction in the voxel, in which it is assumed there are no metabolites. More recently, the α-correction was introduced to account for the different concentrations of GABA+in gray matter and white matter. In this paper, we show that the selected tissue correction strategy can alter the interpretation of results using data from a healthy aging cohort with GABA+ measurements in a frontal and posterior voxel. In a frontal voxel, we show an age-related decline in GABA+ when either no tissue correction (R2 = 0.25, p < 0.001) or the CSF-correction is applied (R2 = 0.08, p < 0.01). When applying the α-correction to the frontal voxel data, we find no relationship between age and GABA+ (R2 = 0.02, p = 0.15). However, with the α-correction we still find that cognitive performance is correlated with GABA+ (R2 = 0.11, p < 0.01). These data suggest that in healthy aging, while there is normal atrophy in the frontal voxel, GABA+ in the remaining tissue is not decreasing on average. This indicates that the selection of tissue correction can significantly impact the interpretation of MRS results.
Copyright © 2017 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Aging; Atrophy; CSF-correction; GABA; GABA-edited MRS; Gray matter; Tissue-correction; White matter; α-correction

Mesh:

Substances:

Year:  2017        PMID: 28882635      PMCID: PMC5705271          DOI: 10.1016/j.neuroimage.2017.08.073

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


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