In vivo characterization of glycogen storage disease type III in a mouse model using glycoNOE MRI.

PURPOSE: Glycogen storage disease type III (GSD III) is a rare inherited metabolic disease characterized by excessive accumulation of glycogen in liver, skeletal muscle, and heart. Currently, there are no widely available noninvasive methods to assess tissue glycogen levels and disease load. Here, we use glycogen nuclear Overhauser effect (glycoNOE) MRI to quantify hepatic glycogen levels in a mouse model of GSD III. METHODS: Agl knockout mice (n = 13) and wild-type controls (n = 10) were scanned for liver glycogen content using glycoNOE MRI. All mice were fasted for 12 to 16 h before MRI scans. GlycoNOE signal was quantified by fitting the Z-spectrum using a four-pool Voigt lineshape model. Next, the fitted direct water saturation pool was removed and glycoNOE signal was estimated from the integral of the residual Z spectrum within -0.6 to -1.4 ppm. Glycogen concentration was also measured ex vivo using a biochemical assay. RESULTS: GlycoNOE MRI clearly distinguished Agl knockout mice from wild-type controls, showing a statistically significant difference in glycoNOE signals in the livers across genotypes. There was a linear correlation between glycoNOE signal and glycogen concentration determined by the biochemical assay. The obtained glycoNOE maps of mouse livers also showed higher glycogen levels in Agl knockout mice compared to wild-type mice. CONCLUSION: GlycoNOE MRI was used successfully as a noninvasive method to detect liver glycogen levels in mice, suggesting the potential of this method to be applied to assess glycogen storage diseases.

Ultrafast Z-spectroscopic imaging in vivo at 3T using through-slice spectral encoding (TS-UFZ).

PURPOSE: Acquisition of high-resolution Z-spectra for CEST or magnetization transfer contrast (MTC) MRI requires excessive scan times. Ultrafast Z-spectroscopy (UFZ) has been proposed to address this; however, the quality of in vivo UFZ spectra has been insufficient. Here, we present a simple approach to improve this. THEORY AND METHODS: UFZ imaging acquires full Z-spectra by encoding the spectral dimension spatially via a gradient applied concurrently with the RF saturation pulse. Different from previous implementations, both this saturation gradient and its readout were applied in the slice direction, resulting in a relatively uniform voxel composition. Phase-encoding was applied in both in-plane directions, allowing additional under-sampling and acceleration. RESULTS: In phantoms, UFZ imaging with through-slice Z-spectral encoding (TS-UFZ) provided Z-spectra of salicylic acid and egg white in excellent agreement with conventional acquisitions. In vivo brain Z-spectra were influenced by flow through the imaging slice which affected the Z-spectral baseline. Still, CEST signals could be quantified after baseline fitting and mapping the residual CEST signal. Amide proton transfer (APT) contrast intensities obtained by TS-UFZ were on the same order of magnitude as conventional CEST but with different contrast across slice which likely is a result of different tissue regions contributing. CONCLUSION: TS-UFZ approach improves signal stability and spectral uniformity over previous implementations and allows high spectral-resolution imaging of saturation transfer effects in the human brain at 3T. This implementation allows for further acceleration by reducing phase encoding steps and thus opens up the possibility of mapping dynamic CEST signals in vivo with a practical temporal resolution.

Deep learning-based Lorentzian fitting of water saturation shift referencing spectra in MRI.

PURPOSE: Water saturation shift referencing (WASSR) Z-spectra are used commonly for field referencing in chemical exchange saturation transfer (CEST) MRI. However, their analysis using least-squares (LS) Lorentzian fitting is time-consuming and prone to errors because of the unavoidable noise in vivo. A deep learning-based single Lorentzian Fitting Network (sLoFNet) is proposed to overcome these shortcomings. METHODS: A neural network architecture was constructed and its hyperparameters optimized. Training was conducted on a simulated and in vivo-paired data sets of discrete signal values and their corresponding Lorentzian shape parameters. The sLoFNet performance was compared with LS on several WASSR data sets (both simulated and in vivo 3T brain scans). Prediction errors, robustness against noise, effects of sampling density, and time consumption were compared. RESULTS: LS and sLoFNet performed comparably in terms of RMS error and mean absolute error on all in vivo data with no statistically significant difference. Although the LS method fitted well on samples with low noise, its error increased rapidly when increasing sample noise up to 4.5%, whereas the error of sLoFNet increased only marginally. With the reduction of Z-spectral sampling density, prediction errors increased for both methods, but the increase occurred earlier (at 25 vs. 15 frequency points) and was more pronounced for LS. Furthermore, sLoFNet performed, on average, 70 times faster than the LS-method. CONCLUSION: Comparisons between LS and sLoFNet on simulated and in vivo WASSR MRI Z-spectra in terms of robustness against noise and decreased sample resolution, as well as time consumption, showed significant advantages for sLoFNet.

A numerical human brain phantom for dynamic glucose-enhanced (DGE) MRI: On the influence of head motion at 3T.

PURPOSE: Dynamic glucose-enhanced (DGE) MRI relates to a group of exchange-based MRI techniques where the uptake of glucose analogues is studied dynamically. However, motion artifacts can be mistaken for true DGE effects, while motion correction may alter true signal effects. The aim was to design a numerical human brain phantom to simulate a realistic DGE MRI protocol at 3T that can be used to assess the influence of head movement on the signal before and after retrospective motion correction. METHODS: MPRAGE data from a tumor patient were used to simulate dynamic Z-spectra under the influence of motion. The DGE responses for different tissue types were simulated, creating a ground truth. Rigid head movement patterns were applied as well as physiological dilatation and pulsation of the lateral ventricles and head-motion-induced B0 -changes in presence of first-order shimming. The effect of retrospective motion correction was evaluated. RESULTS: Motion artifacts similar to those previously reported for in vivo DGE data could be reproduced. Head movement of 1 mm translation and 1.5 degrees rotation led to a pseudo-DGE effect on the order of 1% signal change. B0 effects due to head motion altered DGE changes due to a shift in the water saturation spectrum. Pseudo DGE effects were partly reduced or enhanced by rigid motion correction depending on tissue location. CONCLUSION: DGE MRI studies can be corrupted by motion artifacts. Designing post-processing methods using retrospective motion correction including B0 correction will be crucial for clinical implementation. The proposed phantom should be useful for evaluation and optimization of such techniques.

The relayed nuclear Overhauser effect in magnetization transfer and chemical exchange saturation transfer MRI.

Magnetic resonance (MR) is a powerful technique for noninvasively probing molecular species in vivo but suffers from low signal sensitivity. Saturation transfer (ST) MRI approaches, including chemical exchange saturation transfer (CEST) and conventional magnetization transfer contrast (MTC), allow imaging of low-concentration molecular components with enhanced sensitivity using indirect detection via the abundant water proton pool. Several recent studies have shown the utility of chemical exchange relayed nuclear Overhauser effect (rNOE) contrast originating from nonexchangeable carbon-bound protons in mobile macromolecules in solution. In this review, we describe the mechanisms leading to the occurrence of rNOE-based signals in the water saturation spectrum (Z-spectrum), including those from mobile and immobile molecular sources and from molecular binding. While it is becoming clear that MTC is mainly an rNOE-based signal, we continue to use the classical MTC nomenclature to separate it from the rNOE signals of mobile macromolecules, which we will refer to as rNOEs. Some emerging applications of the use of rNOEs for probing macromolecular solution components such as proteins and carbohydrates in vivo or studying the binding of small substrates are discussed.

Radiofrequency labeling strategies in chemical exchange saturation transfer MRI.

Chemical exchange saturation transfer (CEST) MRI has generated great interest for molecular imaging applications because it can image low-concentration solute molecules in vivo with enhanced sensitivity. CEST effects are detected indirectly through a reduction in the bulk water signal after repeated perturbation of the solute proton magnetization using one or more radiofrequency (RF) irradiation pulses. The parameters used for these RF pulses-frequency offset, duration, shape, strength, phase, and interpulse spacing-determine molecular specificity and detection sensitivity, thus their judicious selection is critical for successful CEST MRI scans. This review article describes the effects of applying RF pulses on spin systems and compares conventional saturation-based RF labeling with more recent excitation-based approaches that provide spectral editing capabilities for selectively detecting molecules of interest and obtaining maximal contrast.

Magnetic resonance imaging of glycogen using its magnetic coupling with water.

Glycogen plays a central role in glucose homeostasis and is abundant in several types of tissue. We report an MRI method for imaging glycogen noninvasively with enhanced detection sensitivity and high specificity, using the magnetic coupling between glycogen and water protons through the nuclear Overhauser enhancement (NOE). We show in vitro that the glycogen NOE (glycoNOE) signal is correlated linearly with glycogen concentration, while pH and temperature have little effect on its intensity. For validation, we imaged glycoNOE signal changes in mouse liver, both before and after fasting and during glucagon infusion. The glycoNOE signal was reduced by 88 ± 16% (n = 5) after 24 h of fasting and by 76 ± 22% (n = 5) at 1 h after intraperitoneal (i.p.) injection of glucagon, which is known to rapidly deplete hepatic glycogen. The ability to noninvasively image glycogen should allow assessment of diseases in which glucose metabolism or storage is altered, for instance, diabetes, cardiac disease, muscular disorders, cancer, and glycogen storage diseases.

Detection of electrostatic molecular binding using the water proton signal.

PURPOSE: Saturation transfer MRI has previously been used to probe molecular binding interactions with signal enhancement via the water signal. Here, we detail the relayed nuclear overhauser effect (rNOE) based mechanisms of this signal enhancement, develop a strategy of quantifying molecular binding affinity, i.e., the dissociation constant ( KD$$ {K}_D $$ ), and apply the method to detect electrostatic binding of several charged small biomolecules. Another goal was to estimate the detection limit for transient receptor-substrate binding. THEORY AND METHODS: The signal enhancement mechanism was quantitatively described by a three-step magnetization transfer model, and numerical simulations were performed to verify this theory. The binding equilibria of arginine, choline, and acetyl-choline to anionic resin were studied as a function of ligand concentration, pH, and salt content. Equilibrium dissociation constants ( KD$$ {K}_D $$ ) were determined by fitting the multiple concentration data. RESULTS: The numerical simulations indicate that the signal enhancement is sufficient to detect the molecular binding of sub-millimolar (∼100 µM) concentration ligands to low micromolar levels of molecular targets. The measured rNOE signals from arginine, choline, and acetyl-choline binding experiments show that several magnetization transfer pathways (intra-ligand rNOEs and intermolecular rNOEs) can contribute. The rNOEs that arise from molecular ionic binding were influenced by pH and salt concentration. The molecular binding strengths in terms of KD$$ {K}_{\mathrm{D}} $$ ranged from 70-160 mM for the three cations studied. CONCLUSION: The capability to use MRI to detect the transient binding of small substrates paves a pathway towards the detection of micromolar level receptor-substrate binding in vivo.

Deep learning-based classification of preclinical breast cancer tumor models using chemical exchange saturation transfer magnetic resonance imaging.

Chemical exchange saturation transfer (CEST) magnetic resonance imaging has shown promise for classifying tumors based on their aggressiveness, but CEST contrast is complicated by multiple signal sources and thus prolonged acquisition times are often required to extract the signal of interest. We investigated whether deep learning could help identify pertinent Z-spectral features for distinguishing tumor aggressiveness as well as the possibility of acquiring only the pertinent spectral regions for more efficient CEST acquisition. Human breast cancer cells, MDA-MB-231 and MCF-7, were used to establish bi-lateral tumor xenografts in mice to represent higher and lower aggressive tumors, respectively. A convolutional neural network (CNN)-based classification model, trained on simulated data, utilized Z-spectral features as input to predict labels of different tissue types, including MDA-MB-231, MCF-7, and muscle tissue. Saliency maps reported the influence of Z-spectral regions on classifying tissue types. The model was robust to noise with an accuracy of more than 91.5% for low and moderate noise levels in simulated testing data (SD of noise less than 2.0%). For in vivo CEST data acquired with a saturation pulse amplitude of 2.0 µT, the model had a superior ability to delineate tissue types compared with Lorentzian difference (LD) and magnetization transfer ratio asymmetry (MTRasym ) analysis, classifying tissues to the correct types with a mean accuracy of 85.7%, sensitivity of 81.1%, and specificity of 94.0%. The model's performance did not improve substantially when using data acquired at multiple saturation pulse amplitudes or when adding LD or MTRasym spectral features, and did not change when using saliency map-based partial or downsampled Z-spectra. This study demonstrates the potential of CNN-based classification to distinguish between different tumor types and muscle tissue, and speed up CEST acquisition protocols.

Towards robust glucose chemical exchange saturation transfer imaging in humans at 3 T: Arterial input function measurements and the effects of infusion time.

Dynamic glucose-enhanced (DGE) magnetic resonance imaging (MRI) has shown potential for tumor imaging using D-glucose as a biodegradable contrast agent. The DGE signal change is small at 3 T (around 1%) and accurate detection is hampered by motion. The intravenous D-glucose injection is associated with transient side effects that can indirectly generate subject movements. In this study, the aim was to study DGE arterial input functions (AIFs) in healthy volunteers at 3 T for different scanning protocols, as a step towards making the glucose chemical exchange saturation transfer (glucoCEST) protocol more robust. Two different infusion durations (1.5 and 4.0 min) and saturation frequency offsets (1.2 and 2.0 ppm) were used. The effect of subject motion on the DGE signal was studied by using motion estimates retrieved from standard retrospective motion correction to create pseudo-DGE maps, where the apparent DGE signal changes were entirely caused by motion. Furthermore, the DGE AIFs were compared with venous blood glucose levels. A significant difference (p = 0.03) between arterial baseline and postinfusion DGE signal was found after D-glucose infusion. The results indicate that the measured DGE AIF signal change depends on both motion and blood glucose concentration change, emphasizing the need for sufficient motion correction in glucoCEST imaging. Finally, we conclude that a longer infusion duration (e.g. 3-4 min) should preferably be used in glucoCEST experiments, because it can minimize the glucose infusion side effects without negatively affecting the DGE signal change.

Mechanism and quantitative assessment of saturation transfer for water-based detection of the aliphatic protons in carbohydrate polymers.

PURPOSE: CEST MRI experiments of mobile macromolecules, for example, proteins, carbohydrates, and phospholipids, often show signals due to saturation transfer from aliphatic protons to water. Currently, the mechanism of this nuclear Overhauser effect (NOE)-based transfer pathway is not completely understood and could be due either to NOEs directly to bound water or NOEs relayed intramolecularly via exchangeable protons. We used glycogen as a model system to investigate this saturation transfer pathway in sugar polymer solution. METHODS: To determine whether proton exchange affected saturation transfer, saturation spectra (Z-spectra) were measured for glycogen solutions of different pH, D2 O/H2 O ratio, and glycogen particle size. A theoretical model was derived to analytically describe the NOE-based signals in these spectra. Numerical simulations were performed to verify this theory, which was further tested by fitting experimental data for different exchange regimes. RESULTS: Signal intensities of aliphatic NOEs in Z-spectra of glycogen in D2 O solution were influenced by hydroxyl proton exchange rates, whereas those in H2 O were not. This indicates that the primary transfer pathway is an exchange-relayed NOE from these aliphatic protons to neighboring hydroxyl protons, followed by the exchange to water protons. Experimental data for glycogen solutions in D2 O and H2 O could be analyzed successfully using an analytical theory derived for such relayed NOE transfer, which was further validated using numerical simulations with the Bloch equations. CONCLUSION: The predominant mechanism underlying aliphatic signals in Z-spectra of mobile carbohydrate polymers is intramolecular relayed NOE transfer followed by proton exchange.

d-glucose weighted chemical exchange saturation transfer (glucoCEST)-based dynamic glucose enhanced (DGE) MRI at 3T: early experience in healthy volunteers and brain tumor patients.

PURPOSE: Dynamic glucose enhanced (DGE) MRI has shown potential for imaging glucose delivery and blood-brain barrier permeability at fields of 7T and higher. Here, we evaluated issues involved with translating d-glucose weighted chemical exchange saturation transfer (glucoCEST) experiments to the clinical field strength of 3T. METHODS: Exchange rates of the different hydroxyl proton pools and the field-dependent T2 relaxivity of water in d-glucose solution were used to simulate the water saturation spectra (Z-spectra) and DGE signal differences as a function of static field strength B0 , radiofrequency field strength B1 , and saturation time tsat . Multislice DGE experiments were performed at 3T on 5 healthy volunteers and 3 glioma patients. RESULTS: Simulations showed that DGE signal decreases with B0 , because of decreased contributions of glucoCEST and transverse relaxivity, as well as coalescence of the hydroxyl and water proton signals in the Z-spectrum. At 3T, because of this coalescence and increased interference of direct water saturation and magnetization transfer contrast, the DGE effect can be assessed over a broad range of saturation frequencies. Multislice DGE experiments were performed in vivo using a B1 of 1.6 µT and a tsat of 1 second, leading to a small glucoCEST DGE effect at an offset frequency of 2 ppm from the water resonance. Motion correction was essential to detect DGE effects reliably. CONCLUSION: Multislice glucoCEST-based DGE experiments can be performed at 3T with sufficient temporal resolution. However, the effects are small and prone to motion influence. Therefore, motion correction should be used when performing DGE experiments at clinical field strengths.

Thiol-water proton exchange of glutathione, cysteine, and N-acetylcysteine: Implications for CEST MRI.

Amide-, amine-, and hydroxyl-water proton exchange can generate MRI contrast through chemical exchange saturation transfer (CEST). In this study, we show that thiol-water proton exchange can also generate quantifiable CEST effects under near-physiological conditions (pH = 7.2 and 37°C) through the characterization of the pH dependence of thiol proton exchange in phosphate-buffered solutions of glutathione, cysteine, and N-acetylcysteine. The spontaneous, base-catalyzed, and buffer-catalyzed exchange contributions to the thiol exchange were analyzed. The thiol-water proton exchange of glutathione and cysteine was found to be too fast to generate a CEST effect around neutral pH due to significant base catalysis. The thiol-water proton exchange of N-acetylcysteine was found to be much slower, yet still in the fast-exchange regime with significant base and buffer catalysis, resulting in a 9.5% attenuation of the water signal at pH 7.2 in a slice-selective CEST NMR experiment. Furthermore, the N-acetylcysteine thiol CEST was also detectable in human serum albumin and agarose phantoms.

CEST MRI of 3-O-methyl-D-glucose uptake and accumulation in brain tumors.

PURPOSE: 3-O-Methyl-D-glucose (3-OMG) is a nonmetabolizable structural analog of glucose that offers potential to be used as a CEST-contrast agent for tumor detection. Here, we explore it for CEST-detection of malignant brain tumors and compare it with D-glucose. METHODS: Glioma xenografts of a U87-MG cell line were implanted in five mice. Dynamic 3-OMG weighted images were collected using CEST-MRI at 11.7 T at a single offset of 1.2 ppm, showing the effect of accumulation of the contrast agent in the tumor, following an intravenous injection of 3-OMG (3 g/kg). RESULTS: Tumor regions showed higher enhancement as compared to contralateral brain. The CEST contrast enhancement in the tumor region ranged from 2.5-5.0%, while it was 1.5-3.5% in contralateral brain. Previous D-glucose studies of the same tumor model showed an enhancement of 1.5-3.0% and 0.5-1.5% in tumor and contralateral brain, respectively. The signal gradually stabilized to a value that persisted for the length of the scan. CONCLUSIONS: 3-OMG shows a CEST contrast enhancement that is approximately twice as much as that of D-glucose for a similar tumor line. In view of its suggested low toxicity and transport properties across the BBB, 3-OMG provides an option to be used as a nonmetallic contrast agent for evaluating brain tumors.

CEST MRI monitoring of tumor response to vascular disrupting therapy using high molecular weight dextrans.

PURPOSE: Vascular disrupting therapy of cancer has become a promising approach not only to regress tumor growth directly but also to boost the delivery of chemotherapeutics in the tumor. An imaging approach to monitor the changes in tumor vascular permeability, therefore, has important applications for monitoring of vascular disrupting therapies. METHODS: Mice bearing CT26 subcutaneous colon tumors were injected intravenously with 150 kD dextran (Dex150, diameter, d~ 20 nm, 375 mg/kg), tumor necrosis factor-alpha (TNF-α; 1 µg per mouse), or both (n = 3 in each group). The Z-spectra were acquired before and 2 h after the injection, and the chemical exchange saturation transfer (CEST) signals in the tumors as quantified by asymmetric magnetization transfer ratio (MTRasym ) at 1 ppm were compared. RESULTS: The results showed a significantly stronger CEST contrast enhancement at 1 ppm (∆MTRasym = 0.042 ± 0.002) in the TNF-α-treated tumors than those by Dex150 alone (∆MTRasym = 0.000 ± 0.005, P = 0.0229) or TNF-α alone (∆MTRasym = 0.002 ± 0.004, P = 0.0264), indicating that the TNF-α treatment strongly augmented the tumor uptake of 150 kD dextran. The MRI findings were verified by fluorescence imaging and immunofluorescence microscopy. CONCLUSIONS: High molecular weight dextrans can be used as safe and sensitive CEST MRI contrast agents for monitoring tumor response to vascular disrupting therapy and, potentially, for developing dextran-based theranostic drug delivery systems.

Quantification and tracking of genetically engineered dendritic cells for studying immunotherapy.

PURPOSE: Genetically encoded reporters can assist in visualizing biological processes in live organisms and have been proposed for longitudinal and noninvasive tracking of therapeutic cells in deep tissue. Cells can be labeled in situ or ex vivo and followed in live subjects over time. Nevertheless, a major challenge for reporter systems is to identify the cell population that actually expresses an active reporter. METHODS: We have used a nucleoside analog, pyrrolo-2'-deoxycytidine, as an imaging probe for the putative reporter gene, Drosophila melanogaster 2'-deoxynucleoside kinase. Bioengineered cells were imaged in vivo in animal models of brain tumor and immunotherapy using chemical exchange saturation transfer MRI. The number of transduced cells was quantified by flow cytometry based on the optical properties of the probe. RESULTS: We performed a comparative analysis of six different cell lines and demonstrate utility in a mouse model of immunotherapy. The proposed technology can be used to quantify the number of labeled cells in a given region, and moreover is sensitive enough to detect less than 10,000 cells. CONCLUSION: This unique technology that enables efficient selection of labeled cells followed by in vivo monitoring with both optical and MRI. Magn Reson Med 79:1010-1019, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Phenols as Diamagnetic T2 -Exchange Magnetic Resonance Imaging Contrast Agents.

Although T2 -exchange (T2ex ) NMR phenomena have been known for decades, there has been a resurgence of interest to develop T2ex MRI contrast agents. One indispensable advantage of T2ex MR agents is the possibility of using non-toxic and/or bio-compatible diamagnetic compounds with intermediate exchangeable protons. Herein a library of phenol-based compounds is screened and their T2ex contrast (exchange relaxivity, r2ex ) at 9.4 T determined. The T2ex contrast of phenol protons allows direct detection by MRI at a millimolar concentration level. The effect of chemical modification of the phenol on the T2ex MRI contrast through modulation of exchange rate and chemical shift was also studied and provides a guideline for use of endogenous and exogenous phenols for T2ex MRI contrast. As a proof-of-principle application, phenol T2ex contrast can be used to detect enzyme activity in a tyrosinase-catalyzed catechol oxidation reaction.

GlucoCEST magnetic resonance imaging in vivo may be diagnostic of acute renal allograft rejection.

Acute cellular renal allograft rejection (AR) frequently occurs after kidney transplantations. It is a sterile T-cell mediated inflammation leading to increased local glucose metabolism. Here we demonstrate in an allogeneic model of Brown Norway rat kidneys transplanted into uninephrectomized Lewis rats the successful implementation of the recently developed glucose chemical exchange saturation transfer (glucoCEST) magnetic resonance imaging. This technique is a novel method to assess and differentiate AR. Renal allografts undergoing AR showed significantly increased glucoCEST contrast ratios of cortex to medulla of 1.61 compared to healthy controls (1.02), syngeneic Lewis kidney to Lewis rat transplants without rejection (0.92), kidneys with ischemia reperfusion injury (0.99) and kidneys affected by cyclosporine A toxicity (1.10). Receiver operating characteristic curve analysis showed an area under the curve value of 0.92, and the glucoCEST contrast ratio predicted AR with a sensitivity of 100% and a specificity of 69% at a threshold level over 1.08. In defined animal models of kidney injuries, the glucoCEST contrast ratios of cortex to medulla correlated positively with mRNA expression levels of T-cell markers (CD3, CD4, CD8a/b), but did not correlate to impaired renal perfusion. Thus, the glucoCEST parameter may be valuable for the assessment and follow up treatment of AR.

Investigation of the contribution of total creatine to the CEST Z-spectrum of brain using a knockout mouse model.

The current study aims to assign and estimate the total creatine (tCr) signal contribution to the Z-spectrum in mouse brain at 11.7 T. Creatine (Cr), phosphocreatine (PCr) and protein phantoms were used to confirm the presence of a guanidinium resonance at this field strength. Wild-type (WT) and knockout mice with guanidinoacetate N-methyltransferase deficiency (GAMT-/-), which have low Cr and PCr concentrations in the brain, were used to assign the tCr contribution to the Z-spectrum. To estimate the total guanidinium concentrations, two pools for the Z-spectrum around 2 ppm were assumed: (i) a Lorentzian function representing the guanidinium chemical exchange saturation transfer (CEST) at 1.95 ppm in the 11.7-T Z-spectrum; and (ii) a background signal that can be fitted by a polynomial function. Comparison between the WT and GAMT-/- mice provided strong evidence for three types of contribution to the peak in the Z-spectrum at 1.95 ppm, namely proteins, Cr and PCr, the latter fitted as tCr. A ratio of 20 ± 7% (protein) and 80 ± 7% tCr was found in brain at 2 µT and 2 s saturation. Based on phantom experiments, the tCr peak was estimated to consist of about 83 ± 5% Cr and 17 ± 5% PCr. Maps for tCr of mouse brain were generated based on the peak at 1.95 ppm after concentration calibration with in vivo magnetic resonance spectroscopy.