emission tomography (PET) and single photon emission tomography (SPECT).

Transcription

1 Supplementary Notes for Manuscript NMED-NT53311 Title: Magnetic Resonance Imaging of Glutamate Authors: Kejia Cai, Mohammad Haris, Anup Singh, Feliks Kogan, Joel H. Greenberg, Hari Hariharan, John A. Detre, Ravinder Reddy SUPPLEMENTARY NOTE Glutamate (Glu) and gamma-aminobutyric acid (GABA) are the major excitatory and inhibitory neurotransmitters in the brain, respectively. Conventional magnetic resonance spectroscopy ( 1 HMRS) of aliphatic protons is capable of quantifying neurotransmitters and other small molecules, but it generally provides poor spatial and temporal resolution. Other major approaches for imaging neurotransmitter function to date are positron emission tomography (PET) and single photon emission tomography (SPECT). PET and SPECT exploit radioactive ligands that bind to the receptors of these neurotransmitters 1,2. PET studies have measured the distribution of the Glu receptor; specifically, a noncompetitive and highly selective antagonist for the metabotropic Glu receptor subtype 5 (mglur5), 3-(6-Methyl-pyridin-2-ylethynyl)-cyclohex-2-enone-O- 11C-methyloxime ( 11 C-ABP688), was evaluated for its potential as a PET agent 1. Despite their high specificity to Glu receptors, the major shortcomings of PET and SPECT are radiation exposure, low resolution, imaging logistics due to the short half-lives of radio ligands, and their limited applicability to functional studies. While magnetic resonance imaging (MRI) is noninvasive and provides high resolution and exquisite structural details, existing MRI methods are not capable of imaging the distribution of neurotransmitters in brain. Functional MRI (fmri) provides information based on changes in blood flow and metabolism, but lacks the sensitivity and specificity to probe these neurotransmitters. Given these shortcomings, there is a clear need for 1

2 developing improved methods for imaging of these neurotransmitters, preferably with high spatial and temporal resolution using noninvasive and nonradioactive means. Here we show both theoretically and experimentally that chemical exchange saturation transfer (CEST) between the amine protons of glutamate (Glu) and bulk water can be exploited to image Glu with high spatial resolution at ultra high magnetic fields. SUPPLEMENTARY METHODS Theoretical Considerations Consider two nuclear spin I = 1/2 systems, A (water) and B (solute), with a distinct chemical shift difference, ω, and an exchangeable proton on the solute that exchanges with water protons. In a static magnetic field, application of a long low power RF pulse at the resonance of B without affecting the resonance of A leads to the equalization of the populations in the two spin states of B, a situation referred to as spin saturation, and no signal is observed from spin B. Since the B spins are in exchange with that of A spins, the saturated magnetization is transferred to A spins and a concomitant decrease in the signal intensity of the A spins occurs. Subsequently, longitudinal relaxation returns each nuclear spin system to its equilibrium values and eventually the system reaches a steady state. The steady state magnetization is given by Equation [1], M sat 1 = [1] M + kft 0 1 where, M sat is the steady-state amplitude of water proton magnetization during the irradiation of exchangeable spin B; M 0 is the amplitude of the water proton magnetization in the absence of saturation, k is the acid catalyzed exchange rate constant between water 1w 2

3 and B, and f is the mole fraction of protons on B, and T 1w is the longitudinal relaxation time of water protons 3-5. For dilute solutions, where [H 2 O] >> [B], f can be written as: n[ B] f = [2] 2[ H 2 O] where n is the number of exchangeable protons in the solute. In the case of glutamate, n = 3 (in aqueous solution there are three exchanging amine protons NH + 3 ). The saturation transfer magnetization is then imaged to detect the CEST effect. In order for the CEST effect to be efficiently observed, the slow to intermediate exchange condition (chemical shift of exchangeable spins, ω > k) must be fulfilled. In implementing this method in vivo, there are two issues that require special attention; one is the direct saturation of water and the other is the background magnetization transfer effect in biological tissues. To account for these effects in biological tissues, two images are acquired; one with saturation at the resonance frequency of exchanging spin(s) M sat (+ ω) and the other at the equal frequency offset difference on the other side of the bulk water peak M sat ( ω). The difference of these two images normalized by an image obtained without any saturation (M 0 ) yields the CEST effect of the solute. However, in situations where the transverse relaxation times of water are short (such as in biological tissues) and high saturation pulse amplitudes are required, as in this study, there will be substantial direct saturation of water. The fraction of the water signal that is directly saturated by the saturation pulse (applied at ± ω) attenuates the CEST effect. Consequently, calculation of the CEST effect by normalizing with M 0 will lead to a substantial underestimation. This can be alleviated to some extent by using M sat ( ω) to normalize the data 6. This is given by Equation [3], 3

4 M sat( Δω) M sat( Δω) CEST asym ( Δω) = [3] M ( Δω) where CEST asym contrast at 3 p.p.m. is referred to as GluCEST. It is worthwhile noting that for situations where free water T 2 is long, as in the case of phantom studies, the direct saturation effect is very small and the calculated CEST asym value is nearly the same with either M 0 or M sat ( ω) normalization. Other factors that influence the CEST effect are the amplitude and duration of the saturation pulse. An analytical expression for the CEST effect can be derived 7-10 from theoretical analysis of a two-site exchange model in the presence of steady-state RF saturation as Equation [4], CEST asym sat αkf ( R1 w + kf ) tsat ( Δω ) = [1 e ] [4] R + kf where, α is the factor that accounts for suboptimal saturation with α = 1 describing complete saturation, R 1w (1/T 1w ) is the longitudinal relaxation rate of water protons and t sat is the length of the saturation pulse. The effects of B 0 and B 1 variations on the observed CEST contrast are rather complex. Since the CEST contrast is based on subtraction of images with ve and +ve frequency saturation, any asymmetry created with local B 0 variation will contaminate the observed CEST contrast with asymmetric effects due to direct saturation. Hence, an accurate measurement of local B 0 and correction is essential. B 1 variations affect both the CEST effect (Equation 4 provides a hint for this through the empirical factor α) as well as the amount of direct saturation contamination. We have adopted the use of B 1 dependent calibration curves for B 1 correction. 1w 4

5 While the above discussion illustrates the general methodology of CEST, analytical equations are valid in the steady-state with long saturation times (> 3T 1 ), and a two-pool exchange model. As we are using non-steady-state experimental conditions and are also dealing with multiple exchanging metabolites in brain, numerical analysis of full Bloch- McConnell equations 11 as described previously 7 were used for analyzing the experimental data presented here. Experimental Methods Pulse Sequence New pulse sequence codes were developed for both Varian and Siemens scanners to use a frequency selective saturation pulse followed by a segmented RF spoiled gradient echo (GRE) readout sequence. To take into account scanner system limitations, the sequence uses saturation pulse trains with variable shapes and durations as well as delays. Results with minimal artifacts were obtained using a series of 10 to 30 Hanning windowed rectangular pulses of 100 ms duration each separated by a 200 µs delay. The excitation bandwidth of this saturation pulse train was 5 Hz for a 1 s saturation duration with a 1% bandwidth of 20 Hz. The total repetition time of the sequence was adjusted to stay within RF specific absorption rate (SAR) limits. The sequence schematic diagram is given below: 5

6 Figure 1: GluCEST imaging pulse sequence. The basic sequence consists of an outer shot loop containing the frequency selective saturation pulse train followed by an inner loop of segmented fast low angle shot (FLASH) gradient echo acquisitions and ending with a delay (T1delay in the Fig.1). Shot loops are repeated using the number of shots required per image acquisition. We use a centric phase encoding order scheme to maintain the best CEST contrast. The whole sequence can be repeated to generate images with saturation applied at different offset frequencies. Phantom Preparations In order to measure the ph dependence of GluCEST, phantoms with a 10mM Glu (Sigma Aldrich, USA) concentration in phosphate buffered saline (PBS) were prepared in 10mm NMR tubes at a varying ph from 3 to 8. The ph was adjusted using 1N NaOH and HCl. For measuring the concentration dependence of GluCEST, imaging phantoms with 2, 4, 6, 8 and 10 mm concentrations of Glu were prepared in PBS at ph 7. These samples were added to small test tubes (10 mm diameter), and immersed inside a large PBS phantom. 6

7 To evaluate the contribution of other major 1 HMRS visible metabolites, we prepared solutions of these metabolites (ph 7) in the range of their physiological concentrations [creatine (Cr, 6 mm), myoinositol (MI, 10 mm), N-acetyle aspartate (NAA, 10 mm), glutamine (Gln, 2 mm), taurine (2 mm), aspartate (Asp, 2 mm), Glu (10 mm) and GABA (2 mm)] (Sigma Aldrich, USA). Phantom Imaging The imaging parameters were: slice thickness = 10 mm, GRE flip angle = 10 o, GRE readout TR = 5.6 ms, TE = 2.7 ms, field of view = mm 2, matrix size = , and one saturation pulse at a root mean square B 1 (B 1rms ) of 155 Hz (3.6µT) and 2 s duration and 64 segments acquired every 15 s. Multiple CEST images were collected using a saturation pulse at frequencies ranging from 5 to +5 p.p.m. in steps of 0.2 p.p.m.. Z-spectra were obtained from these images by plotting the normalized image intensity as a function of the resonance offset of the saturation pulse for each sample. The z-spectral asymmetry plots were fitted to the two pool exchange simulation results to derive exchange rate. Animal Experiments All the studies were performed according to an approved Institutional Animal Care and Use Committee (IACUC) protocol. 7

8 Animal Preparation for MCAO Sprague-Dawley male rats ( g) were anesthetized with isoflurane (4% for induction, 1.5% maintenance) in a mixture of 70% nitrous oxide and 30% oxygen given by nose cone. A polyethylene catheter (PE50) was inserted into the tail artery to monitor arterial blood pressure and the rat was placed into a stereotaxic head holder. Following a midline incision, the scalp over the right hemisphere was reflected and a small region (1.5 mm diameter) of the skull 5 mm lateral to and 1 mm posterior to Bregma was thinned with a high-speed dental drill. A laser Doppler flow (LDF) probe (1 mm tip diameter, 0.25 fiber separation) was positioned over the thinned skull and held in place by a plastic probe holder cemented to the skull. This probe was attached to a flow meter (PeriFlux 4001, Perimed, Stockholm, Sweden) permitting measurement of changes in cerebral blood flow in the territory of the middle cerebral artery (MCA) during occlusion. Focal cerebral ischemia was induced with the filament technique as previously described 12,13. Through a midline neck incision, the right external and internal carotid arteries were dissected from the surrounding connective tissue. A silicone-coated nylon monofilament (Doccol Corporation, Redlands, CA, USA) was inserted through the right common carotid artery into the internal carotid artery until LDF indicated adequate MCA occlusion by a sharp decrease in blood flow to 25-30% of baseline. Blood pressure and LDF were monitored for 30 minutes prior to placing the animal into the bore of the magnet. Imaging of Healthy and MCAO Rats 8

9 Healthy (n=2) and MCAO rats (n=3) were transferred to a 9.4T horizontal bore small animal scanner (Varian, Palo Alto, CA) and placed in a 35-mm diameter commercial quadrature proton coil (m2m Imaging Corp., Cleveland, OH). Animals were kept under anesthesia (1.5% isoflurane in 1 liters/min oxygen) and kept warm with warm air generated from a heater (SA Instruments, Inc., Stony Brook, NY). Respiration and body temperature was monitored using a MRI compatible small animal monitor system (SA Instruments, Inc., Stony Brook, NY). CEST imaging of the healthy rat brain was performed using the following sequence parameters: field of view = mm 2, slice thickness = 2 mm, GRE flip angle = 15 o, GRE readout TR = 6.2 ms, TE = 2.9 ms, matrix size = , number of averages = 2, and one saturation pulse with duration = 1s and B 1rms = 250Hz (5.9µT) followed by a 32 segment acquisition every 4s. CEST images were collected at multiple frequencies ranging from -5 to + 5 p.p.m. in steps of 0.2 p.p.m.. B 1 and B 0 maps were also acquired. GluCEST contrast was averaged for regions of interest from both the gray matter (GM) and white matter (WM) of the rat brain. The same sequence parameters were used for imaging MCAO rats. Sequential MCAO rat brain CEST imaging was started 1 h post MCAO and continued till 4.5 h post MCAO. GluCEST contrast was averaged for regions of interest from both the ipsilateral and contralateral hemispheres of the MCAO rat brain. Rat Tumor Model Preparation To validate GluCEST in vivo, a rat brain tumor model was used. It is well known that brain tumors disrupt the function of the blood brain barrier locally in a nonhomogeneous 9

10 manner 14. This compromised blood brain barrier enables the uptake of a fraction of the injected Glu in the tumor region. To develop intracranial tumors, rat gliosarcoma cells (9L) were used. Syngeneic female Fisher rats (F344/NCR, four-six weeks old) weighing g were used to generate tumor-bearing rats as described previously 15. Briefly, general anesthesia was induced by isoflurane followed by intraperitonial injection of a ketamine (91 mg kg 1 ) and acepromazine (9.1 mg kg 1 ) mixture. A 10 µl suspension of 50,000 9L cells in phosphate buffered saline was injected into the cortex at a depth of 2 mm with a Hamilton syringe and a 30-gauge needle using a stereotactic apparatus (3 mm lateral and 3mm posterior to the bregma). These rats were subjected to MRI and MRS five weeks after implantation of tumor cells. Rat Tumor Imaging and Spectroscopy Rats (n=3) with brain tumors were anesthetized with isoflurane (3% for induction, 1.5% maintenance) and a polyethylene catheter (PE50) was inserted into the tail vein for Glu injection. The same protocol as described in the MCAO model experiment was followed for animal placement in the magnet, monitoring as well as GluCEST imaging. In addition, along with GluCEST maps, stimulated echo acquisition mode (STEAM) localized 1 HMRS spectra were obtained using a vendor (Varian) provided pulse sequence with the following parameters: voxel size = mm 3 (Voxel volume 440 µl), spectral width = 4 khz, Number of points = 2048, average = 128, TE = 8 ms, Tm = 7 ms, and TR = 6s. A water suppression pulse sequence with variable pulse power and 10

11 optimized relaxation delays (VAPOR) was pre-encoded to the STEAM sequence. The 1 HMRS voxel was chosen mostly from the tumor region of the brain. Localized shimming was performed to obtain localized water line width values of p.p.m. or less. After collecting the baseline CEST map and 1 HMRS data, the animals were injected with a 2.5 ml, 100 mm glutamate solution through the catheter inserted in the tail vein. CEST and 1 HMRS data were gathered periodically for about 2 h post injection. 1 HMRS spectra were obtained from the raw free induction decay data by exponential apodization (30Hz), Fourier transformation, phase correction and baseline removal. The spectral region between 0.5 p.p.m. and 4 p.p.m. of the resultant spectrum was fitted to a sum of Gaussian functions using non-linear least squares fitting (MATLAB nlinfit routine). Peak integrals for all metabolites were calculated from the fitted peaks. In vivo Exchange Rate Measurement The in vivo exchange rate in a healthy rat brain at 9.4T was measured using a previously described method 7. Specifically, images were acquired using a saturation pulse with a 2 s duration at varying saturation B 1rms values (25 to 500 Hz). Exchange rate was then calculated using the relationship between the exchange rate and amplitude of the saturation pulse that gives the maximum CEST effect. Human Studies GluCEST imaging and z-spectrum acquisitions on human brains at 7T were performed on three normal male volunteers (age: years). The study was conducted under an approved Institutional Review Board protocol of the University of Pennsylvania. 11

12 Informed consent from each volunteer was obtained after explaining the study protocol. The imaging parameters were: slice thickness = 10 mm, GRE flip angle=10 o, GRE readout TR = 5.6 ms, TE = 2.7 ms, field of view = mm 2, matrix size = , with one saturation pulse at a B 1rms of 155 Hz (3.6 µt) and a 1 s duration and 64 segments acquired every 15 s. Raw CEST images were acquired at varying saturation offset frequencies ranging from -5 to +5 p.p.m. with 0.1 p.p.m. steps. Brain z-spectra were calculated from B 0 corrected CEST images and the resulting CEST asym curves were corrected for B 1 inhomogeneity (see below for details). Final z-spectra and CEST asymmetry curves were smoothed using a 3-point moving average algorithm. GluCEST maps were obtained from the final CEST asym curves. 1 HMRS spectra were obtained from GM and WM regions using a standard point resolved spectroscopy (PRESS) 16 localization technique with the following parameters: voxel size = mm 3, spectral width = 4 khz, number of points = 2048, average = 100, TE = 16 ms, and TR = 3 s. Water suppression was achieved using the variable pulse power and optimized relaxation delays method (VAPOR). 1 HMRS spectra were fitted to sum of Gaussian functions using non-linear least squares fitting (MATLAB nlinfit routine). Peak integrals were calculated and normalized with a non-water suppressed proton signal for calculating metabolite concentrations in vivo. B 0 and B 1 Maps and Corrections To alleviate B 0 and B 1 inhomogeneities, B 0 and B 1 maps from the same imaging slices were obtained. A B 0 field map was obtained from four complex (magnitude and phase) gradient echo images with TE = 2.13, 4.17, 6.21, and 8.25 ms. Following phase 12

13 unwrapping, the accumulated pixel phase Δθ 0 is related to the frequency offset by Equation [5], B Δθ ΔTE 0 0 = [5] The final B 0 field map was obtained by minimizing the pixel by pixel chi-squared error statistic to Equation [5] given the echo time differences (ΔTE) and pixel phase differences Δ θ ) using linear least squares fitting. B 0 maps were used for B 0 correction of the ( 0 original GluCEST images. CEST data, acquired in the neighborhood of ± 3.0 p.p.m. at steps of 0.1 p.p.m., and B 0 maps were used to generate corrected GluCEST images (± 3.0 p.p.m.) using a procedure similar to that described previously 17. Specifically, CEST images obtained from to p.p.m. and -2.2 to -3.8 p.p.m. with a step size of 0.1 p.p.m. were interpolated using cubic spline to generate CEST images with a step size of 0.01 p.p.m.. Corrected GluCEST images at ±3.0 p.p.m. were generated from the interpolated CEST images by picking values according to amount of frequency shift as measured from the B 0 map. The corrected ± 3.0 p.p.m. images were then used for computing the final GluCEST map. B 1 field maps were obtained using a 2D single slice fast spin echo readout sequence with TE = 12 ms, TR = 6 s, image matrix. Two images were obtained using preparation square pulses with duration (τ) and flip angles of 30 o and 60 o. The RF pulse amplitude for a 30 o flip angle was used as the reference B 1 or B 1ref. Flip angle (θ) maps were generated by solving Equation [6], cos(2θ ) S(2θ ) = [6] cos( θ ) S( θ ) 13

14 where S(θ) and S(2θ) denote pixel signals in an image with preparation flip angle θ and 2θ respectively. From the flip angle map, a B 1 field map can be obtained using the relation, B 1 = θ (360 τ) 1. The coefficient B 1 /B 1ref has been used for B 1 correction of GluCEST contrast. Numerical Simulations Bloch McConnell equation solvers were written in MATLAB incorporating relaxation and chemical exchange for the experimental conditions used in this study. This included incorporating saturation pulse trains identical to the experimental conditions applied at different frequency offsets and B 1rms values. We simulated the magnetization available at the end of the saturation pulse train and calculated z-spectra, CEST asymmetry plots and GluCEST values for different experimental conditions, exchange rates and relaxation times. Specifically, we used a single site exchange model for phantom simulations (free water and Glu) and five-site exchange model (free-, bound pool of water, Glu (+GABA), Cr, and amide protons) for in vivo brain simulations. We also developed specific software subroutines in MATLAB to analyze the experimental data. These programs are available upon request. For the simulation results reported in Table 1, we used the five site exchange simulation program. As indicated in the footnotes of the table, we used free water, bound water, amide protons, Cr and (Glu+GABA) as the 5 sites. For getting estimates of bound water GluCEST, the concentrations of amide protons, Cr and (Glu+GABA) metabolites were set to zero in our simulations. For estimating the contribution of a specific metabolite to GluCEST, the concentrations of all other metabolites were zeroed keeping the bound 14

15 water concentration fixed. Separate simulations were done for WM and GM using the parameters given in Table 1. Image Processing and Display All image processing and data analysis was performed using MATLAB (version 7.5, R2007b). Acquired images were corrected for B 0 and B 1 and CEST contrast was calculated from the Equation [3]. GluCEST contrast was mapped as false-colors onto anatomical proton images. SUPPLEMENTARY DISCUSSION It should be noted that 1 HMRS measured Glu -CH 2 (2.3 p.p.m.) resonances will also have some contamination from brain glutamine (~1 mm) and the composite resonance is usually referred to as Glx. As a result, the 1 HMRS derived [Glu] may have some potential contribution, albeit small, from glutamine. On the other hand, since glutamine does not exhibit CEST it will not affect the GluCEST. The experimental CEST contrast resulting from a phantom with different metabolites (MI, Cr, NAA, taurine, GABA, Asp, Gln and Glu) at their physiological concentration and ph 7 show that, with the experimental parameters used, CEST contrast arises primarily from Glu. GABA amine protons exhibit a broad CEST peak centered at 2.75 p.p.m., which can be clearly localized at a lower ph. Therefore, despite a 0.25 p.p.m. (~75 Hz at 7T) separation between the amine resonances of GABA and Glu, their CEST peaks do interfere with each other. 15

16 Long saturation RF pulses with high B 1 are required for CEST imaging due to the fairly small CEST agent concentration and relatively fast chemical exchange rate, and could potentially result in significant RF heat deposition in tissue beyond the SAR limits of the Food and Drug Administration (FDA). However, with the pulse sequence design and the experimental parameters that were employed in the current study, SAR was kept well under the allowed FDA limits. In previous work, the CEST effect from amide protons has been used to measure ph in vivo, as well as to map protein concentrations in vivo 18,19. The CEST effect from amide protons is observed at 3.5 p.p.m. downfield from water protons (absolute shift 8.2 p.p.m.), which is separated by 0.5 p.p.m. from the amine protons of Glu. The exchange rates of amide protons are about 30 s -1, leading to a CEST contrast (amide proton transfer (APT)) at 3.5 p.p.m. offset of <2% in human brain tumors and ~1% in contralateral normal appearing white matter 18. Also, based on the literature reports, it appears that at physiological ph, amide protons from several major proteins may not exhibit observable CEST effects 4. This may be due to their unfavorable exchange rates for the CEST effect at the saturation parameters used. When using asymmetry analysis, the amide proton contribution may be compensated by an occurrence of nuclear Overhauser effects from protons up field from water. 20 During ischemia induced by MCAO model as well as euthanasia 19, it was reported that the APT CEST decreases significantly due to decreased ph from 7.0 to 6.5. If the APT contribution dominated GluCEST, we would expect GluCEST also to decrease when the ph decreases. However, the GluCEST measured from the MCAO model in this study increased with a decrease in ph from 7.0 to 6.5. This supports the hypothesis that APT 16

17 contribution to the GluCEST is small. Similarly, most of the amide and amine protons are on large proteins whose exchange rates are < 100 s 1 and T 2 are in the order of 10 µs and may have only minor contributions (~1%) to the observed GluCEST (see Table 1). In the MCAO model, changes in T 2, MTR and water content are expected to introduce only minor changes in GluCEST. Specifically, since the computation of GluCEST maps involves subtraction of two images obtained by saturating at positive and negative offsets with respect to the bulk water resonance, any change in MTR will be subtracted out. On the other hand, while an increase in water content leads to a reduction in [Glu] and hence GluCEST, an increase in water T 2 leads to increased GluCEST. Thus, the effects of changes in water content and T 2 compete with each other thereby their net effect on GluCEST may not be appreciable. Overall, based on the numerical simulations of full Bloch-McConnell equations, we estimated that the Glu contributions to the observed GluCEST in human brain in vivo are ~70-75%. This relative contribution may have a slight variation per site depending on the coil or field strength or experimental parameters. 17

18 SUPPLEMENTARY TABLE 1 Simulation results on potential contributions to in-vivo human brain GluCEST at 7T. Metabolites T 1 (s) T 2 (s) ω (p.p.m.) Concentration (M) Exchange Rate (s -1 ) CEST at 3 p.p.m. (%) GM WM GM WM Free Water a Bound Water b (-1.4%) -0.22(-3.7%) Amide c (10.7%) 0.90 (15.3%) Creatine d (8.2%) 0.44 (7.5%) Glutamate e (75.0%) 4.08 (69.4%) GABA f (7.5%) 0.68 (11.6%) 5-pool combined simulation Experimental Total 10.35* 6.38* 11.55± ±0.29 a For simulation, the measured T 1 and an estimated T 2 for free water are used. T 2 is estimated from the observed T 2 with removal of all exchange contributions to T 2 relaxation rate 7,21. b For simulation, the bound water parameters were used from reference 22. This reflects MTR asymmetry contribution. c-f Simulations used 3 components, free water, bound water and metabolite of interest. Metabolite relative contributions are given in parenthesis as % values. c For simulation, all parameters were taken from reference 19. d For simulation, the concentrations were taken from reference 23, 24 and exchange rate estimated from measurements from phantoms and heart tissue samples. e For simulation, the concentrations were taken from reference 23, 24 and exchange rate measured in vivo from rat brain. f For simulation, the concentration was taken from reference 25 and relaxation and exchange rate parameters were assumed to be the same as glutamate. * The sum of individual contributions is slightly less than the 5 pool simulation results (GM/WM = 10.29%/5.88%) due to repeated addition of the negative bound water contribution. Simulated 5-pool CEST effect at 3 p.p.m. is 11.13%/6.85% (GM/WM) and 9.45%/5.85% (GM/WM) if the exchange rate of glutamate and GABA is set as 1500 and 2500 s -1 respectively. 18

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