Elsevier

NeuroImage

Volume 159, 1 October 2017, Pages 32-45
NeuroImage

Big GABA: Edited MR spectroscopy at 24 research sites

https://doi.org/10.1016/j.neuroimage.2017.07.021Get rights and content

Highlights

  • GABA-edited MEGA-PRESS data from 272 adults were collected from 24 sites.

  • GABA+ data showed good agreement across vendors and sites.

  • Variability in MM-suppressed GABA data was attributed in part to B0 field offsets.

  • Multi-site studies using GABA editing are feasible using a standardized protocol.

  • These results provide valuable benchmarks for the MRS community.

Abstract

Magnetic resonance spectroscopy (MRS) is the only biomedical imaging method that can noninvasively detect endogenous signals from the neurotransmitter γ-aminobutyric acid (GABA) in the human brain. Its increasing popularity has been aided by improvements in scanner hardware and acquisition methodology, as well as by broader access to pulse sequences that can selectively detect GABA, in particular J-difference spectral editing sequences. Nevertheless, implementations of GABA-edited MRS remain diverse across research sites, making comparisons between studies challenging. This large-scale multi-vendor, multi-site study seeks to better understand the factors that impact measurement outcomes of GABA-edited MRS. An international consortium of 24 research sites was formed. Data from 272 healthy adults were acquired on scanners from the three major MRI vendors and analyzed using the Gannet processing pipeline. MRS data were acquired in the medial parietal lobe with standard GABA+ and macromolecule- (MM-) suppressed GABA editing. The coefficient of variation across the entire cohort was 12% for GABA+ measurements and 28% for MM-suppressed GABA measurements. A multilevel analysis revealed that most of the variance (72%) in the GABA+ data was accounted for by differences between participants within-site, while site-level differences accounted for comparatively more variance (20%) than vendor-level differences (8%). For MM-suppressed GABA data, the variance was distributed equally between site- (50%) and participant-level (50%) differences. The findings show that GABA+ measurements exhibit strong agreement when implemented with a standard protocol. There is, however, increased variability for MM-suppressed GABA measurements that is attributed in part to differences in site-to-site data acquisition. This study's protocol establishes a framework for future methodological standardization of GABA-edited MRS, while the results provide valuable benchmarks for the MRS community.

Introduction

Magnetic resonance spectroscopy (MRS) is unique amongst the neuroimaging modalities in detecting endogenous signals from complex molecules in the brain noninvasively. Of particular interest is the detection and measurement of γ-aminobutyric acid (GABA), the major inhibitory neurotransmitter in the mammalian brain (McCormick, 1989). Healthy brain function relies on GABAergic inhibitory processes, and understanding GABAergic mechanisms in both healthy and pathological brain function has been one core focus of neuroscience. MRS measurements of GABA have been associated with individual differences in hemodynamic and electrophysiological signals (Donahue et al., 2010, Hu et al., 2013, Kapogiannis et al., 2013, Muthukumaraswamy et al., 2009) and a number of measures of cognition (Fujihara et al., 2015, Shibata et al., 2017, Yoon et al., 2016) and behavior (Boy et al., 2011, Greenhouse et al., 2017, Puts et al., 2011, Silveri et al., 2013). Differential levels of GABA have been observed in a number of neuropsychiatric disorders, such as schizophrenia (Kegeles et al., 2012, Öngür et al., 2010, Rowland et al., 2016, Yoon et al., 2010) and depression (Bhagwagar et al., 2008, Hasler et al., 2007, Price et al., 2009), neurodevelopmental disorders, such as autism spectrum disorder (Drenthen et al., 2016, Gaetz et al., 2014, Puts et al., 2016) and attention deficit hyperactivity disorder (Bollmann et al., 2015, Edden et al., 2012a), and neurological diseases, such as Parkinson's disease (Emir et al., 2012), amyotrophic lateral sclerosis (Foerster et al., 2012, Foerster et al., 2013) and diabetic neuropathy (Petrou et al., 2012).

The most common MRS approach for detecting the GABA signal is the Mescher–Garwood (MEGA) editing sequence (Mescher et al., 1998), a J-difference spectral editing technique that is typically implemented within a point resolved spectroscopy (PRESS) (Bottomley, 1987) acquisition. MEGA-PRESS and other spectral editing techniques exploit the known scalar coupling properties of molecules in order to separate their associated signals from the overlapping signals of other molecules. For lower-concentration metabolites such as GABA, spectral editing differentiates the weak signals of interest from the stronger, overlapping signals of higher-concentration metabolites. Difference editing techniques in particular use frequency-selective inversion pulses to achieve this (for methodological reviews, see Harris et al., 2017; Puts and Edden, 2012). The popularity of MEGA-PRESS is attributed to a number of factors, including the wide availability of the basic PRESS sequence across scanner platforms, its relatively straightforward implementation (Mullins et al., 2014), its reproducibility (Bogner et al., 2010, Brix et al., 2017, Geramita et al., 2011, Mikkelsen et al., 2016a, Near et al., 2014, O'Gorman et al., 2011, Shungu et al., 2016) and continued development of acquisition methodology and data processing tools (Chan et al., 2016, Edden et al., 2014).

However, despite these positive attributes, the diversity of implementations of MEGA-PRESS across research sites and vendors has meant that comparing data between different studies is difficult. For instance, pulse sequence parameters, and in particular pulse timings, differ between vendor-specific PRESS sequences and lead to subtle but important differences in the resolved GABA signal (Near et al., 2013b). Moreover, spectral editing of GABA is associated with a number of complexities, including TE-dependent J-evolution of the GABA spin system (Edden et al., 2012b), frequency and spatial effects of volume localization (Edden and Barker, 2007, Kaiser et al., 2008), sensitivity to B0 field frequency offsets (Edden et al., 2016, Harris et al., 2014) and contamination from co-edited macromolecules (MM) (Henry et al., 2001, Rothman et al., 1993). It is generally assumed that these factors limit the degree to which a GABA-edited measurement from one site can be compared to another at a different site.

In order to establish the extent to which site-, sequence- and vendor-specific differences impact quantitative MEGA-PRESS measurement outcomes, a multi-vendor, multi-site dataset has been assembled by an international consortium of GABA-edited MRS users. The consortium was formed with the aim of building a normative database of MEGA-PRESS data acquired on the major MRI scanner platforms at a range of imaging centers focused on neuroscience research. This dataset aims to capture some of the diversity of the sequences used, but within the framework of a standardized study design and acquisition protocol that would reflect typical MEGA-PRESS parameters. This approach reduced the number of confounding variables present within the dataset (e.g., standardizing key parameters such as TE, TR and editing pulse bandwidth), while maintaining diversity at the level of pulse sequence implementation (e.g., localization pulse waveforms/bandwidths, pulse timings and crusher gradient schemes).

This paper presents initial results from this multi-site study, focusing on how variance in creatine-referenced GABA measurements was distributed across research sites and scanner vendors and examining the influence of various acquisition- and participant-related effects. Given the complexity of this dataset, it is not possible to report on all aspects of the project in a single article, so for example, water-referenced quantification (including tissue-dependent correction factors) and site-to-site differences in voxel placement fidelity and segmentation will be presented in a future report.

Section snippets

Data collection

A consortium of 24 research institutions based in nine countries participated in this initiative, with each site contributing 5–12 datasets collected from consenting adult volunteers. Specific guidelines for each site's participant cohort were: 18–35 years old; approximately 50:50 female/male split; no known neurological or psychiatric illness. In total, data from 272 participants were collected. Participant demographics are provided in Table 1. Scanning was conducted in accordance with ethical

Results

GABA-edited MRS data were successfully acquired at all 24 sites. Following quality control analysis, seven GABA+ and 19 MM-suppressed GABA datasets (3% and 7% of the total collected data for either acquisition, respectively) were removed from further analysis. All MM-suppressed GABA data from site G3 were excluded as consistent, excessive center frequency offsets (approximately −0.1 ppm on average) resulted in extremely small or absent GABA signals. Fig. 2 shows the mean ± 1 SD GABA+ and

Discussion

This is the largest multi-site study to date applying GABA-edited MRS in the human brain. The aims at the outset were to establish the extent to which GABA-edited measurements are influenced by site-, sequence- and vendor-specific differences, and to investigate sources of observed variance. Overall, the major findings can be summarized as follows:

  • 1)

    The agreement between GABA+ values was surprisingly good, with whole-dataset CV (12%) not much higher than the mean within-site CV (10%), although

Acknowledgments

This work was supported by NIH grants R01 EB016089, R01 EB023963 and P41 EB015909. Data collection was supported by the Shandong Provincial Key Research and Development Plan of China (2016ZDJS07A16) and the National Natural Science Foundation of China for Young Scholars (no. 81601479). IDW thanks Mrs. J. Bigley of the University of Sheffield MRI Unit for her assistance with data acquisition. JJP was supported by NIAAA grant K23 AA020842. MPS was supported by NIH grant F32 EY025121. NAJP

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