GABA & Time Of Day

JOURNAL OF MAGNETIC RESONANCE IMAGING 31:204–209 (2010)

Technical Note

Diurnal Stability of g-aminobutyric Acid Concentration in Visual and Sensorimotor Cortex Christopher John Evans, PhD,1 David John McGonigle, PhD,1,2 and Richard Anthony Edward Edden, PhD1–3* Purpose: To establish the diurnal stability of edited magnetic resonance spectroscopy measurements of gammaaminobutyric acid (GABA) in visual and sensorimotor regions of the brain. Materials and Methods: GABA measurements were made in two regions of the brain (an occipital, ‘‘visual’’ region and a ‘‘sensorimotor’’ region centered on the precentral gyrus) using the MEGA-PRESS editing method, scanning eight healthy adults at five timepoints during a single day. GABA concentration was quantified from the ratio of the GABA integral to the unsuppressed water signal. Results: No significant effect of time on GABA concentration was seen (P ¼ 0.35). GABA was shown to be significantly more concentrated in visual regions than in sensorimotor regions (1.10 i.u. and 1.03 i.u., respectively; P ¼ 0.050). Coefficients of variability (CVs) across all subjects of 9.1% and 12% (visual and sensorimotor) were significantly higher than mean within-subjects CVs of 6.5% and 8.8. Conclusion: This study demonstrates the excellent reproducibility of MEGA-PRESS detection of GABA, demonstrating that the method is sufficiently sensitive to detect inter-subject variability, and suggests that (within the sensitivity limits of current measurements) time of day can be ignored in the design of MRS studies of visual and sensorimotor regions. Key Words: MRS; GABA; diurnal; circadian; MEGAPRESS; stability J. Magn. Reson. Imaging 2010;31:204–209. C 2009 Wiley-Liss, Inc. V

1

CUBRIC, School of Psychology, Cardiff University, Cardiff, Wales, UK. CUBRIC, School of Biosciences, Cardiff University, Cardiff, Wales, UK. 3 CUBRIC, School of Chemistry, Cardiff University, Cardiff, Wales, UK. Contract grant sponsor: Cardiff University Schools of Bioscience, Psychology, and Chemistry; the Welsh Institute of Cognitive Neuroscience. *Address reprint requests to: R.A.E.E., Park 367C, Division of Neuroradiology, Johns Hopkins University, 600 N Wolfe St, Baltimore MD. E-mail: [email protected] Received July 13, 2009; Accepted October 2, 2009. DOI 10.1002/jmri.21996 Published online in Wiley InterScience (www.interscience.wiley.com). 2

C 2009 Wiley-Liss, Inc. V

AS THE PRINCIPLE cortical inhibitory neurotransmitter, gamma-aminobutyric acid (GABA) is the target of significant research effort in both the neuroscientific and clinical communities. The emergence of robust localized methods for measuring the concentration of GABA in the human brain in vivo (1–3) has resulted in several studies into cortical plasticity (4) and neuroimaging contrast mechanisms (5,6). The precision of quantification is now sufficient, not only to detect gross differences between patient populations and healthy controls (e.g., Simister et al) (7), but also to detect both individual differences between healthy subjects (5,6) and task-driven changes within individuals (4). GABA plays an important role in many of the rhythms of life, over timescales from years to hours: GABA function shifts from excitation to inhibition during development (8); age-related loss of gray matter volume (9) drives a loss of GABA; GABA-related gene expression levels change with estrus cycle and age in rats (10); and GABA controls the mammalian circadian rhythms of the suprachiasmatic nuclei (11). Reflecting these processes, GABA levels have been shown to vary with age in cross-sectional studies (12), to vary with position in the menstrual cycle (13), and to change in the hypothalamus of rats (14) and cortex of hamsters (15) in a diurnal cycle. Given that GABA measurements are sufficiently sensitive to study basic science questions in healthy subjects, that GABA is involved in the regulation of circadian rhythms within the brain, and that it is rare to prioritize consistent time-of-day of MRS scans across a study cohort, it is important to establish that GABA concentrations are not significantly affected by time-of-day (within the range of sensitivity of current methods) in regions of interest. This study, therefore, was designed to investigate the diurnal stability of GABA measurements.

MATERIALS AND METHODS Eight healthy volunteers (7 male; age, 31.4 6 3.9 years) were recruited to this study under local ethics board approval. A short protocol containing two 10min MRS experiments to measure GABA in visual and sensorimotor regions and minimal preparatory

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GABA in Visual and Sensorimotor Cortex

Figure 1. Experimental design. a: MEGA-PRESS scans were acquired on 2 different days on a four-subject cycle. The order of sensorimotor and visual scans is shown by light gray and dark gray bars, respectively. b: Voxel locations for the sensorimotor region and the occipital visual region.

imaging was designed. On each of 2 days, four subjects were scanned at five different times during the day (as shown in Fig. 1a) on a cycle of approximately 2.5 h between measurements. For each subject, the acquisition order of the visual and sensorimotor MRS regions was alternated as shown by shading in Figure 1a. Due to the low concentration of GABA and the presence of overlapping signals from other metabolites, GABA is most commonly separated from the spectrum on the basis of its couplings: either through acquiring a two-dimensional (2D) J-spectrum (2) or by frequency-selective editing of the spectrum. This study used the MEGA-PRESS (1) method that relies upon selective refocusing of couplings to the triplet-like GABA signal at 3 ppm. To a PRESS localization sequence is added two 16-ms Gaussian editing pulses, which are applied either to the GABA spins at 1.9 ppm, or at 7.5 ppm in an interleaved manner, that is, symmetrically disposed about the water frequency. A total of 332 scans were acquired in a total experiment time of 10 min for both regions. Other relevant experimental parameters are as follows: TE ¼ 68 ms; TR ¼ 1.8 s; acquisition time 400 ms; voxel size 3 3 3 cm3. In addition, eight transients were

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acquired of the unsuppressed water signal for the same region (with identical receive and transmit gains) to be used in quantifying the data. All experiments were carried out on a GE Signa HDx 3 Tesla (T) MRI scanner (General Electric, Waukesha, WI), using an eight-element head coil for receive and the body coil for transmit. The sensorimotor region was defined in the axial plane as being centered on the ‘‘hand knob’’ (16) area of the precentral gyrus (as shown in Fig. 1b), and lined up with the upper surface of the brain in the sagittal plane. The visual region was defined (as used previously in Muthukumaraswamy et al) (5) to be centered on the median line, rotated in the sagittal plane so as to align with the cerebellar tentorium, and positioned as posteriorly as possible, while preventing protrusion from the occipital lobe and limiting inclusion of the sagittal sinus. The voxel location for each volunteer was determined before the day of scanning, as necessitated by the rapid protocol, from a 1-mm isotropic resolution FSPGR structural image (TR/TE ¼ 7.9/3.0 ms, TI ¼ 450 ms, Flip angle ¼ 20 ) of each subject. FAST segmentation (17) of this scan was also performed to determine the gray matter, white matter, and cerebrospinal fluid (CSF) composition of the voxel. MEGA-PRESS spectra were mulitipled by a 3.2 Hz exponential window function before Fourier transformation and fitted in the frequency domain over the range 2.82–3.56 ppm (the region of the GABA peak and the resolved surrounding baseline) by a single Gaussian peak of variable amplitude and width and a linear baseline. The water signal was fitted using a mixed Lorentz-Gaussian and a linear baseline. Both procedures were carried out in Matlab (The Mathworks, Natick, MA) using in-house software. GABA concentrations were quantified in institutional units (i.u.) as the ratio between the GABA integral and the water integral (18) multiplied by a constant factor that accounts for estimates of the T1 and T2 of water and GABA protons, estimates of the MR-visible water concentration and editing efficiency, and the number of scans in the experiment. Statistical Analysis The 80 GABA measurements recorded were classified according to subject, location (sensorimotor or visual), and time. Using SPSS 14.0, a repeated-measures twoway analysis of variance (ANOVA) was used to test for main effects of region and timepoint (where timepoint is treated as the repeated measure). Further statistical analysis was performed using Matlab): inter- and intra-subject variability was investigated by calculating the CV of measurements for each individual and region, and the coefficient of variation of measurements grouped across all subjects.

RESULTS Edited GABA spectra were acquired in all 80 experiments with excellent stability. Individual spectra from

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Figure 2. a: MEGA-PRESS spectra of visual and sensorimotor regions from a single session: on and off sub-spectra (above) are subtracted to give the edited difference spectra (below). b: Overlay of sensorimotor and visual MEGA-PRESS spectra, corrected by subtraction of a baseline spline through the chemical shift values marked by dots. c: Mean 6 standard deviation spectrum for the data in (b).

a single session are shown in Figure 2a: the on and off sub-spectra, and the difference spectra for somatosensory and occipital volumes. Fitting of the GABA peak and adjacent baseline (2.82–3.56 ppm) with the Gaussian-with-linear-baseline model was successful in all cases. The spectra (minus a baseline spline) are overlaid in Figure 2b, and a composite spectrum of the calculated mean 6 standard deviation for each datapoint is shown in Figure 2c. The intensity of the spectra has not been normalized; the relatively narrow range suggests that the receiver gain is adjusted consistently across volunteers (note that this procedural observation only relates to Figure 2 and that the subsequent quantification of each spectrum is achieved through an internal reference water scan with identical gain parameters). It is clear from the overlaid

Evans et al.

spectra and the mean/range spectrum that the degree of lipid excitation is highly variable across subjects. Water suppression could be improved by better prescan optimization, and lipid inclusion by optimization of outer-volume suppression (19) and optimization of chemical shift displacement directions. No statistically significant effect of timepoint on the GABA concentration was found (F ¼ 1.5; df ¼ 4; P ¼ 0.352). A statistically significant main effect on GABA concentration of region was found (F ¼ 5.56; df ¼ 7; P ¼ 0.050). Figure 3a shows the subject means by region (i.e., collapsed across timepoints), with error bars representing the standard error on the mean (SEM). Visual GABA concentration is greater than sensorimotor GABA in all but one subject. Figure 3b shows GABA concentration in the visual region as a function of time; Figure 3c shows the GABA concentration in the sensorimotor region as a function of time. Superimposed on the raw datapoints is the running mean, calculated as the mean of the eight measurements closest in time to that point (one measurement from each of the eight subjects). The first and second points are calculated over four and six subjects, respectively (as are the last and second last respectively). Figure 3d shows the same running mean and a shaded region representing the mean 6 SEM. These plots reinforce the difference between regions and the lack of any observable change in concentration with time. Segmentation of the prescribed voxels gave the following results: somatosensory voxel (32 6 3% gray matter; 54 6 7% white matter; 14 6 4% CSF); occipital voxel (32 6 12% gray matter; 56 6 7% white matter; 9 6 3% CSF), which are not significantly different. Individual coefficients of variation are shown in Table 1. A comparison of the CV across the whole group (column label ‘‘Group’’) with the mean within-subject CV (column label ‘‘Mean’’) is used to investigate the degree of inter- and intra-subject variability. The group CV is 9.1% for visual measurements and 12.0% for sensorimotor measurements. The mean individual CV is 6.5% for visual and 8.8% for sensorimotor.

DISCUSSION The principle aim of this study was to establish the diurnal variability of GABA in two regions of the brain, a region surrounding the central sulcus including both pre- and postcentral gyri, and an occipital region selected to include visual cortex, to better inform future MRS studies of GABA. Because we found no evidence of a time-dependence in GABA concentration within the limits of sensitivity of current methods, we conclude that time-of-day need not be considered as a factor in studies of the cortical regions used here. This is an important finding, because regularizing the time-of-day of scans would be a significant impediment to progress for clinical and nonclinical studies carried out within a busy MRI scanning schedule. For example, the current study, carried out over 2 complete days of scanning would have taken 8 weeks to complete if within-day


Figure 3. Concentration of GABA (calculated as a corrected ratio between GABA and water integrals) separated by subject and region (a). Individual measurements in the visual area (b) and the sensorimotor area (c) of all subjects plotted against time of day. The running mean (as defined in the text) is plotted as a dashed line. Running mean of the visual and sensorimotor data with shaded regions representing mean 6 SEM (d).

variability of GABA was significant. This finding is limited to two regions of the brain, and while there are structures in the brain such as the suprachiasmatic nuclei which may be more likely to show GABA changes, a significant proportion of GABA MRS stud-

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ies in the literature has focused on occipital regions. This is the first GABA reproducibility study to address time-of-day, the most extensive reproducibility study to date in terms of participants and repeats, and the first edited multi-repeat study to investigate GABA concentration in two regions. The concentration of GABA has been measured in eight individuals, at five timepoints spread over a total of over 12 hours, in both visual and sensorimotor regions. Averaging across the time and subject, the concentration of GABA was calculated as 1.102 6 0.100 i.u. for the occipital region and 1.028 6 0.123 i.u. for the central sulcal region (both mean 6 standard deviation). This significant difference (F ¼ 5.56; df ¼ 7; P ¼ 0.050) is consistent with a general gradient of increasing GABA along the anterior–posterior axis of the brain (20,21). The coefficients of variation are 9.1% for visual measurements and 12.0% for sensorimotor measurements. This difference in sensitivity is mirrored by a difference in the signal-to-noise ratio of sensorimotor versus visual spectra. The signal-tonoise ratio in the frequency domain, calculated as the amplitude of the fitted Gaussian function divided by the standard deviation of the noise within a 0.8 ppm range at high chemical shift, has a mean value of 49 in visual regions and 38 in sensorimotor regions. This is expected due to the greater proximity of the occipital visual region to the coil elements (than the sensorimotor region). Previous studies have been carried out to look at the reproducibility of GABA measurements. Lymer et al acquired 2D J-resolved MRS of a 3 3 3 cm3 occipital volume in one volunteer for 35 min at 1.5T to quantify GABA (22). Across three repeat scans in one volunteer, they calculated a coefficient of variation (CV) of 26%. Schulte and Boesiger (23) used direct 2D fitting of J-spectra acquired at 3T (allowing shorter acquisition times) and calculated an intra-subject CV of 17% and an inter-subject CV of 22%. Bogner et al. acquired MEGA-PRESS of two 2.5 3 3 cm3 occipital volumes in 1 volunteers for 6.5 min at 3T to quantify GABA (24). In a complex protocol which scanned eight volunteers twice and three volunteers four times, they calculated a coefficient of variation (CV) of GABA concentration relative to water of 15% and relative to creatine of 13.3%. Mullins et al applied TE-averaged PRESS acquisition (a technique equivalent to acquiring the F1 ¼ 0 line of a J-spectrum) to a 2 3 3 cm3 volume in the anterior cingulate of six subjects for 9 min at 3T (25). Two equivalent scans were acquired per subject and a CV of 50% was calculated. In the same study, fitting of a TE ¼ 40 ms PRESS spectrum gave a CV of 13% for GABA. Because the current study applies MEGA-PRESS at 3T, it most closely resembles the study by Bogner and colleagues. The CV of visual measurements in the current study is 9% and is broadly consistent in terms of technique sensitivity with the 13% found in their study, considering the longer scan time (54% longer, corresponding to a 24% SNR gain) and the larger volume (20% larger) studied. Further gains in MEGA-PRESS sensitivity have been shown to be accessible through postprocessing phase- and frequency-correction (26) and

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Table 1 Coefficients of Variation (CV) Calculated Over Five Time Points for Each Subject and Region (and Their Mean), and CV Over All Results for the Region (Group Column) Subject

1

2

3

4

5

6

7

8

Mean

Group

CVvisual CVsensorimotor

8.0% 15.8%

4.6% 8.5%

7.1% 4.4%

12.1% 9.5%

7.9% 13.6%

2.5% 6.3%

4.9% 8.4%

5.0% 3.9%

6.5% 8.8%

9.1% 12.0%

through the IVS technique (27). However, refocusing pulses with bandwidth 1300 Hz were used in this study, comparing favorably with the GABA spins’ chemical shift difference of 141 Hz, so the potential gains from IVS would only be of the order of 10%. Given the absence of time effects in the data, it is appropriate to investigate inter- and intra-subject variance, because each repeat measurement within an individual was acquired in a separate scanning session with three other volunteers being scanned in the intervening 2 h. In both visual and sensorimotor regions, the mean individual CV (6.5% and 8.8%) is less than the group CV (9.1% and 12.0%). This is good evidence for the sensitivity of the technique to individual differences, as supported by recent work correlating resting GABA concentration in healthy volunteers with behavioral and functional neuroimaging metrics (5,6). Other sources of within-subject variability which exist in the experiment and which may contribute to the remaining variance are as follows: transmit gain calibrations (leading to imperfect inversion from editing pulses), subject movement, voxel positioning (leading to inclusion of different gray matter/white matter/CSF partial volumes), and fitting imperfect data. It is interesting to note that the degree of variability differs greatly between subjects, from 2.5% (subject 6 visual) to 15.8% (subject 1 somatosensory). This is thought to be due to a combination of real physiological processes (e.g., Floyer-Lea et al and Behar et al) (4,28), the small sample number (the standard deviation of five repeats is not reliable), variable subject compliance, and the variable interaction between the geometry of each subject’s cortex and voxel placement. The most commonly raised limitation of the MEGAPRESS method for the detection of GABA at 3T is contamination of the edited peak by macromolecules; the macromolecular contribution comes from signals at 3 ppm that are coupled to 1.7 ppm (29). Because the echo time of 68 ms is chosen due to coupling considerations, as well as the need to limit T2 decay, it cannot be lengthened to accommodate more selective editing pulses. Therefore, applying the editing pulses at 1.9 ppm will also invert signals at 1.7 ppm, leading to co-editing. An elegant method for reducing this coediting has been suggested by Henry et al (30) but it does not generalize well to MEGA-PRESS of GABA at 3T, because symmetrical suppression of the 1.7 ppm component with less selective editing pulses results in significant loss of GABA signal. This method has, however, been applied to MEGA-PRESS of GABA at 7T (31) and at 3T to suppress NAA aspartate signals in MEGA-PRESS detection of NAAG (32). In addition, it

should be emphasized that differentiating GABA from structurally related compounds (such as homocarnosine which contains a GABA unit) is not currently possible. The model used to fit the edited GABA spectrum (Gaussian) more closely resembles the acquired signal than simulated data or acquired in vitro GABA data, which do agree closely (26). It is likely that this is due to the mixture of components that contribute to the in vivo edited spectrum. Quantitation of GABA concentration within heterogeneous (and relatively large) voxels is methodologically challenging, and there are several possible approaches with differing levels of complexity. The quantification applied here is relatively simple: the water signal is used as an internal reference without correcting for either the percentage of the voxel that is CSF or for differences in water T1 and T2 for the different compartments. Thus, the GABA concentration reported in institutional units is simply the ratio of the GABA signal to the unsuppressed water signal multiplied by a universal scaling factor as mentioned above. Due to the rapid protocol design applied in this study, it was not possible to generate accurate voxel segmentation data for each scan individually. Before the day of scanning, the location of the occipital and sensorimotor voxels was chosen for each subject with reference to the subject’s (previously acquired) highresolution structural scan, and subject-specific (but not scan-specific) voxel segmentations were generated. These segmentation results suggest that the planned voxels are relatively consistent in composition between individuals, although the percentage of gray matter in the occipital region is particularly variable (32 6 12%). It is not clear whether this reflects differences in global anatomy, the interaction between local cortical geometry and voxel placement, or limitations in the segmentation methodology. That the GABA concentrations have a much lower CV than the GM segmentation percentages suggests that the latter is partly responsible. In conclusion, this time-of-day GABA stability study leads to three conclusions: that MEGA-PRESS of GABA in occipital and sensorimotor cortex is not sensitive to any circadian changes in GABA concentration; that GABA concentration is lower in sensorimotor cortex than occipital visual cortex; and that MEGA-PRESS of GABA at 3T is sufficiently sensitive to reveal inter-subject differences in concentration.

ACKNOWLEDGMENTS We thank Gareth Barker and Dikoma Shungu for assistance in the original sequence programming.


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