Towards the molecular origin of glutamate CEST (GluCEST) imaging in rat brain

Glutamate chemical exchange saturation transfer (GluCEST) MRI to evaluate the relationship between demyelination and glutamate content in depressed mice

Glutamatergic alteration is one of the potential mechanisms of depression. However, there is no consensus on whether glutamate metabolism changes affect the myelin structure of depression in mouse models. Glutamate chemical exchange saturation transfer (GluCEST) is a novel and powerful molecular imaging technique that can visualize glutamate distribution. In this study, we used the GluCEST imaging technique to look at glutamate levels in mice under chronic unpredictable mild stress (CUMS) and how they relate to demyelination. The CUMS mice were exposed to different stress factors for 6 weeks. Evaluated of depression in CUMS mice by behavioral tests. MRI scans were then performed, including T2-mapping, GluCEST, and diffusion tensor imaging (DTI) sequences. Brain tissues were collected for Luxol Fast Blue staining and immunofluorescence staining to analyze the changes in the myelin sheath. Artificially sketched regions of interest (ROI) (corpus callosum, hippocampus, and thalamus) were used to calculate the GluCEST value, fractional anisotropy (FA), and T2 value. Compared with the control group, the GluCEST value in the ROIs of CUMS mice significantly decreased. Similarly, the FA value in ROIs was lower in the CUMS group than in the CTRL group, but the T2 value did not differ significantly between the two groups. The histological results showed that ROIs in the CUMS group had demyelination compared with the CTRL group, indicating that DTI was more sensitive than T2 mapping in detecting myelin abnormalities. Furthermore, the GluCEST value in the ROIs correlates positively with the FA value. These findings suggest that altered glutamate metabolism may be one of the important factors leading to demyelination in depression, and GluCEST is expected to serve as an imaging biological marker for the diagnosis of demyelination in depression.

Enhancing SNR in CEST imaging: A deep learning approach with a denoising convolutional autoencoder

PURPOSE

To develop a SNR enhancement method for CEST imaging using a denoising convolutional autoencoder (DCAE) and compare its performance with state-of-the-art denoising methods.

METHOD

The DCAE-CEST model encompasses an encoder and a decoder network. The encoder learns features from the input CEST Z-spectrum via a series of one-dimensional convolutions, nonlinearity applications, and pooling. Subsequently, the decoder reconstructs an output denoised Z-spectrum using a series of up-sampling and convolution layers. The DCAE-CEST model underwent multistage training in an environment constrained by Kullback-Leibler divergence, while ensuring data adaptability through context learning using Principal Component Analysis-processed Z-spectrum as a reference. The model was trained using simulated Z-spectra, and its performance was evaluated using both simulated data and in vivo data from an animal tumor model. Maps of amide proton transfer (APT) and nuclear Overhauser enhancement (NOE) effects were quantified using the multiple-pool Lorentzian fit, along with an apparent exchange-dependent relaxation metric.

RESULTS

In digital phantom experiments, the DCAE-CEST method exhibited superior performance, surpassing existing denoising techniques, as indicated by the peak SNR and Structural Similarity Index. Additionally, in vivo data further confirm the effectiveness of the DCAE-CEST in denoising the APT and NOE maps when compared with other methods. Although no significant difference was observed in APT between tumors and normal tissues, there was a significant difference in NOE, consistent with previous findings.

CONCLUSION

The DCAE-CEST can learn the most important features of the CEST Z-spectrum and provide the most effective denoising solution compared with other methods.

Toward quantitative CEST imaging of glutamate in the mouse brain using a multi-pool exchange model calibrated by 1H-MRS

PURPOSE

To develop a CEST quantification model to map glutamate concentration in the mouse brain at 11.7 T, overcoming the limitations of conventional glutamate-weighted CEST (gluCEST) contrast (magnetization transfer ratio with asymmetric analysis).

METHODS

1H-MRS was used as a gold standard for glutamate quantification to calibrate a CEST-based quantitative pipeline. Joint localized measurements of Z-spectra at B1 = 5 μT and quantitative 1H-MRS were carried out in two voxels of interest in the mouse brain. A six-pool Bloch-McConnell model was found appropriate to fit experimental data. Glutamate exchange rate was estimated in both regions with this dedicated multi-pool fitting model and using glutamate concentration determined by 1H-MRS.

RESULTS

Glutamate exchange rate was estimated to be ˜1300 Hz in the mouse brain. Using this calibrated value, maps of glutamate concentration in the mouse brain were obtained by pixel-by-pixel fitting of Z-spectra at B1 = 5 μT. A complementary study of simulations, however, showed that the quantitative model has high sensitivity to noise, and therefore, requires high-SNR acquisitions. Interestingly, fitted [Glu] seemed to be overestimated compared to 1H-MRS measurements, although it was estimated with simulations that the model has no intrinsic fitting bias with our experimental level of noise. The hypothesis of an unknown proton-exchanging pool contributing to gluCEST signal is discussed.

CONCLUSION

High-resolution mapping of glutamate in the brain was made possible using the proposed calibrated quantification model of gluCEST data. Further studying of the in vivo molecular contributions to gluCEST signal could improve modeling.

Enhancing amide proton transfer imaging in ischemic stroke using a machine learning approach with partially synthetic data

Amide proton transfer (APT) imaging, a technique sensitive to tissue pH, holds promise in the diagnosis of ischemic stroke. Achieving accurate and rapid APT imaging is crucial for this application. However, conventional APT quantification methods either lack accuracy or are time-consuming. Machine learning (ML) has recently been recognized as a potential solution to improve APT quantification. In this paper, we applied an ML model trained on a new type of partially synthetic data, along with an optimization approach utilizing recursive feature elimination, to predict APT imaging in an animal stroke model. This partially synthetic datum is not a simple blend of measured and simulated chemical exchange saturation transfer (CEST) signals. Rather, it integrates the underlying components including all CEST, direct water saturation, and magnetization transfer effects partly derived from measurements and simulations to reconstruct the CEST signals using an inverse summation relationship. Training with partially synthetic data requires less in vivo data compared to training entirely with fully synthetic or in vivo data, making it a more practical approach. Since this type of data closely resembles real tissue, it leads to more accurate predictions than ML models trained on fully synthetic data. Results indicate that an ML model trained on this partially synthetic data can successfully predict the APT effect with enhanced accuracy, providing significant contrast between stroke lesions and normal tissues, thus clearly delineating lesions. In contrast, conventional quantification methods such as the asymmetric analysis method, three-point method, and multiple-pool model Lorentzian fit showed inadequate accuracy in quantifying the APT effect. Moreover, ML methods trained using in vivo data and fully synthetic data exhibited poor predictive performance due to insufficient training data and inaccurate simulation pool settings or parameter ranges, respectively. Following optimization, only 13 frequency offsets were selected from the initial 69, resulting in significantly reduced scan time.

Rapid and quantitative CEST-MRI sequence using water presaturation

PURPOSE

Despite the significant potential for in vivo metabolic imaging in preclinical and clinical applications, CEST MRI suffers from long scan time and inaccurate quantification. This study aims to suppress the contaminations among signals under different frequencies, which could shorten the TR and thereby facilitate CEST imaging acceleration and quantification.

METHODS

A novel sequence is proposed by applying a water-presaturation (WPS) module at the beginning of each TR. WPS CEST quickly knocks down the residual signal from previous TRs so that the magnetization of all TRs recovers from zero, which aligns well with the formula of quasi-steady-state theorem and enables accurate quantification within shorter TR. WPS CEST was assessed by simulations, creatine phantom, and healthy human brain scans at 3 T.

RESULTS

In simulation and phantom experiment, WPS CEST allows accurate estimation of exchange rate (ksw) using omega plot and using shorter delay time (Td) and saturation time (Ts) (e.g., 1 s/1 s) compared with the conventional CEST. Simulations further showed that WPS CEST could obtain consistent spin-lock relaxation (R1ρ) values over varied Tds and Tss. Six human scans indicated that R1ρ collected from conventional sequences showed significant differences between two groups with Td and Ts of (1 s/1 s) and (2 s/2 s) (amide: 1.721 ± 0.051 s-1 vs. 1.622 ± 0.050 s-1, p = 0.001; nuclear Overhauser enhancement: 1.792 ± 0.046 s-1 vs. 1.687 ± 0.053 s-1, p = 0.004), whereas WPS CEST scans using these 2 Td/Ts values obtained the same mean R1ρ (amide: 1.616 ± 0.053 s-1 vs. 1.616 ± 0.048 s-1, p = 0.862; nuclear Overhauser enhancement: 1.688 ± 0.064 s-1 vs. 1.684 ± 0.054 s-1, p = 0.544).

CONCLUSION

WPS CEST demonstrated accurate quantitation within shorter TR compared with conventional sequences, and thereby may allow rapid quantitative CEST scans in various situations.

A Denoising Convolutional Autoencoder for SNR Enhancement in Chemical Exchange Saturation Transfer imaging: (DCAE-CEST)

Purpose

To develop a SNR enhancement method for chemical exchange saturation transfer (CEST) imaging using a denoising convolutional autoencoder (DCAE), and compare its performance with state-of-the-art denoising methods.

Method

The DCAE-CEST model encompasses an encoder and a decoder network. The encoder learns features from the input CEST Z-spectrum via a series of 1D convolutions, nonlinearity applications and pooling. Subsequently, the decoder reconstructs an output denoised Z-spectrum using a series of up-sampling and convolution layers. The DCAE-CEST model underwent multistage training in an environment constrained by Kullback-Leibler divergence, while ensuring data adaptability through context learning using Principal Component Analysis processed Z-spectrum as a reference. The model was trained using simulated Z-spectra, and its performance was evaluated using both simulated data and in-vivo data from an animal tumor model. Maps of amide proton transfer (APT) and nuclear Overhauser enhancement (NOE) effects were quantified using the multiple-pool Lorentzian fit, along with an apparent exchange-dependent relaxation metric.

Results

In digital phantom experiments, the DCAE-CEST method exhibited superior performance, surpassing existing denoising techniques, as indicated by the peak SNR and Structural Similarity Index. Additionally, in vivo data further confirms the effectiveness of the DCAE-CEST in denoising the APT and NOE maps when compared to other methods. While no significant difference was observed in APT between tumors and normal tissues, there was a significant difference in NOE, consistent with previous findings.

Conclusion

The DCAE-CEST can learn the most important features of the CEST Z-spectrum and provide the most effective denoising solution compared to other methods.

Ameliorative effect of Nyctanthes arbor-tristis L. by suppression of pentylenetetrazole-induced kindling in mice: An insight from EEG, neurobehavioral and in-silico studies

Epilepsy is an abiding condition associated with recurrent seizure attacks along with associated neurological and psychological emanation owing to disparity of excitatory and inhibitory neurotransmission. The current study encompasses the assessment of the Nyctanthes arbor-tristis L. methanolic extract (Na.Cr) in the management of convulsive state and concomitant conditions owing to epilepsy. The latency of seizure incidence was assessed using pentylenetetrazol (PTZ) kindling models along with EEG in Na.Cr pretreated mice, trailed by behavior assessment (anxiety and memory), biochemical assay, histopathological alterations, chemical profiling through GCMS, and molecular docking. The chronic assessment of PTZ-induced kindled mice depicted salvation in a dose-related pattern and outcomes were noticeable with extract at 400 mg/kg. The extract at 400 mg/kg defends the progress of kindling seizures and associated EEG. Co-morbid conditions in mice emanating owing to epileptic outbreaks were validated by behavioral testing and the outcome depicted a noticeable defense related to anxiety (P<0.001) and cognitive deficit (P<0.001) at 400 mg/kg. The isolated brains were evaluated for oxidative stress and the outcome demonstrated a noticeable effect in a dose-dependent pattern. Treatment with Na.Cr. also preserved the brain from PTZ induced neuronal damage as indicated by histopathological analysis. Furthermore, the GCMS outcome predicted 28 compounds abundantly found in the plant. The results congregated in the current experiments deliver valued evidence about the defensive response apportioned by Na.Cr which might be due to decline in oxidative stress, AChE level, and GABAergic modulation. These activities may contribute to fundamental pharmacology and elucidate some mechanisms behind the activities of Nyctanthes arbor-tristis.

Investigation of metabolite correlates of CEST in the human brain at 7 T

Metabolite-weighted chemical exchange saturation transfer MRI can be used to indirectly image metabolites such as creatine and glutamate. This study aims to further explore the contrast of CEST at 2 ppm in the human brain at 7T and investigate the metabolite correlates of CEST at 2 ppm via correlations with magnetic resonance spectroscopy (MRS). Simulations were performed to establish the optimal acquisition parameters, such as total saturation time (tsat) and B1 root mean squared (B1rms) for CEST at 2 ppm in the human brain. Parameters were validated via in vitro phantom studies at 7T using concentrations, pH and temperature comparable to what is found in the human brain. Finally, 10 healthy volunteers were scanned at 7T for comparison with MRS. Our results show that the optimal parameters to acquire CEST at 2 ppm images are: B1rms = 2.14 μT & tsat = 1500 ms, respectively. Comparison with MRS showed no significant correlation between CEST at 2 ppm and total Creatine measured by MRS (R = 0.19; p-value = 0.273). However, a significant correlation was found between CEST at 2 ppm and Glu (R = 0.39; p-value = 0.033), indicating the broad Glutamate-weighted CEST as the main measurable contributor to CEST at 2 ppm. We identified and confirmed optimal CEST at 2 ppm sequence parameters and validated CEST at 2 ppm measurements in a controlled in vitro environment. Our findings suggest that glutamate is a substantial contributor to the CEST at 2 ppm contrast observed in the human brain, whereas the creatine contribution to CEST at 2 ppm in the brain did not show a measurable contribution.

Machine learning-based amide proton transfer imaging using partially synthetic training data

PURPOSE

Machine learning (ML) has been increasingly used to quantify CEST effect. ML models are typically trained using either measured data or fully simulated data. However, training with measured data often lacks sufficient training data, whereas training with fully simulated data may introduce bias because of limited simulations pools. This study introduces a new platform that combines simulated and measured components to generate partially synthetic CEST data, and to evaluate its feasibility for training ML models to predict amide proton transfer (APT) effect.

METHODS

Partially synthetic CEST signals were created using an inverse summation of APT effects from simulations and the other components from measurements. Training data were generated by varying APT simulation parameters and applying scaling factors to adjust the measured components, achieving a balance between simulation flexibility and fidelity. First, tissue-mimicking CEST signals along with ground truth information were created using multiple-pool model simulations to validate this method. Second, an ML model was trained individually on partially synthetic data, in vivo data, and fully simulated data, to predict APT effect in rat brains bearing 9 L tumors.

RESULTS

Experiments on tissue-mimicking data suggest that the ML method using the partially synthetic data is accurate in predicting APT. In vivo experiments suggest that our method provides more accurate and robust prediction than the training using in vivo data and fully synthetic data.

CONCLUSION

Partially synthetic CEST data can address the challenges in conventional ML methods.

A rapid method for phosphocreatine-weighted imaging in muscle using double saturation power-chemical exchange saturation transfer

Monitoring the variation in phosphocreatine (PCr) levels following exercise provides valuable insights into muscle function. Chemical exchange saturation transfer (CEST) has emerged as a sensitive method with which to measure PCr levels in muscle, surpassing conventional MR spectroscopy. However, existing approaches for quantifying PCr CEST signals rely on time-consuming fitting methods that require the acquisition of the entire or a section of the CEST Z-spectrum. Additionally, traditional fitting methods often necessitate clear CEST peaks, which may be challenging to obtain at low magnetic fields. This paper evaluated the application of a new model-free method using double saturation power (DSP), termed DSP-CEST, to estimate the PCr CEST signal in muscle. The DSP-CEST method requires the acquisition of only two or a few CEST signals at the PCr frequency offset with two different saturation powers, enabling rapid dynamic imaging. Additionally, the DSP-CEST approach inherently eliminates confounding signals, offering enhanced robustness compared with fitting methods. Furthermore, DSP-CEST does not demand clear CEST peaks, making it suitable for low-field applications. We evaluated the capability of DSP-CEST to enhance the specificity of PCr CEST imaging through simulations and experiments on muscle tissue phantoms at 4.7 T. Furthermore, we applied DSP-CEST to animal leg muscle both before and after euthanasia and observed successful reduction of confounding signals. The DSP-CEST signal still has contaminations from a residual magnetization transfer (MT) effect and an aromatic nuclear Overhauser enhancement effect, and thus only provides a PCr-weighted imaging. The residual MT effect can be reduced by a subtraction of DSP-CEST signals at 2.6 and 5 ppm. Results show that the residual MT-corrected DSP-CEST signal at 2.6 ppm has significant variation in postmortem tissues. By contrast, both the CEST signal at 2.6 ppm and a conventional Lorentzian difference analysis of CEST signal at 2.6 ppm demonstrate no significant variation in postmortem tissues.

Estimating the synaptic density deficit in Alzheimer's disease using multi-contrast CEST imaging

In vivo noninvasive imaging of neurometabolites is crucial to improve our understanding of the underlying pathophysiological mechanism in neurodegenerative diseases. Abnormal changes in synaptic organization leading to synaptic degradation and neuronal loss is considered as one of the primary factors driving Alzheimer's disease pathology. Magnetic resonance based molecular imaging techniques such as chemical exchange saturation transfer (CEST) and magnetic resonance spectroscopy (MRS) can provide neurometabolite specific information which may relate to underlying pathological and compensatory mechanisms. In this study, CEST and short echo time single voxel MRS was performed to evaluate the sensitivity of cerebral metabolites to beta-amyloid (Aβ) induced synaptic deficit in the hippocampus of a mouse model of Alzheimer's disease. The CEST based spectra (Z-spectra) were acquired on a 9.4 Tesla small animal MR imaging system with two radiofrequency (RF) saturation amplitudes (1.47 μT and 5.9 μT) to obtain creatine-weighted and glutamate-weighted CEST contrasts, respectively. Multi-pool Lorentzian fitting and quantitative T1 longitudinal relaxation maps were used to obtain metabolic specific apparent exchange-dependent relaxation (AREX) maps. Short echo time (TE = 12 ms) single voxel MRS was acquired to quantify multiple neurometabolites from the right hippocampus region. AREX contrasts and MRS based metabolite concentration levels were examined in the ARTE10 animal model for Alzheimer's disease and their wild type (WT) littermate counterparts (age = 10 months). Using MRS voxel as a region of interest, group-wise analysis showed significant reduction in Glu-AREX and Cr-AREX in ARTE10, compared to WT animals. The MRS based results in the ARTE10 mice showed significant decrease in glutamate (Glu) and glutamate-total creatine (Glu/tCr) ratio, compared to WT animals. The MRS results also showed significant increase in total creatine (tCr), phosphocreatine (PCr) and glutathione (GSH) concentration levels in ARTE10, compared to WT animals. In the same ROI, Glu-AREX and Cr-AREX demonstrated positive associations with Glu/tCr ratio. These results indicate the involvement of neurotransmitter metabolites and energy metabolism in Aβ-mediated synaptic degradation in the hippocampus region. The study also highlights the feasibility of CEST and MRS to identify and track multiple competing and compensatory mechanisms involved in heterogeneous pathophysiology of Alzheimer's disease in vivo.

Evaluation of the molecular origin of amide proton transfer-weighted imaging

PURPOSE

To evaluate the assumption in amide proton transfer weighted (APTw) imaging that the APT dominates over the relayed nuclear Overhauser enhancement (rNOE) and other CEST effects such as those from amines/guanidines, thereby providing imaging of mobile proteins/peptides.

METHODS

We introduced two auxiliary asymmetric analysis metrics that can vary the relative contributions from amine/guanidinium CEST and other effects. By comparing these metrics with the conventional asymmetric analysis metric on healthy rat brains, we can approximately assess the contribution from amines/guanidines to APTw and determine whether the APT dominates over the rNOE effect. To further investigate the molecular origin of APTw, we used samples of dialyzed tissue homogenates to eliminate small metabolites and supernatants of homogenates to separate lipids from other components.

RESULTS

When the APTw signal is positive using high saturation amplitudes (e.g., 2-3 μT), the contributions from amines/guanidines are significant and cannot be ignored. The APTw signal from the dialyzed homogenates and the controls has negligible changes, indicating that it primarily originates from macromolecules rather than small metabolites. Additionally, the APTw signals with low saturation amplitudes (e.g., 1 μT) were negative in tissue homogenates but positive in their supernatants, suggesting that proteins contribute positively to APTw signals, whereas lipids contribute negatively to it.

CONCLUSION

The positive APTw signal using high saturation amplitudes could have significant contributions from soluble proteins through CEST, including amide/amine/guanidine proton transfer effects. In contrast, the negative APTw signal using low saturation amplitudes has significant contribution from lipids through rNOE.

Nuclear Overhauser enhancement imaging at -1.6 ppm in rat brain at 4.7T

PURPOSE

A new nuclear Overhauser enhancement (NOE)-mediated saturation transfer signal at around -1.6 ppm, termed NOE(-1.6), has been reported at high fields of 7T and 9.4T previously. This study aims to validate the presence of this signal at a relatively low field of 4.7T and evaluate its variations in different brain regions and tumors.

METHODS

Rats were injected with monocrystalline iron oxide nanoparticles to reduce the NOE(-1.6) signal. CEST signals were measured using different saturation powers before and after injection to assess the presence of this signal. Multiple-pool Lorentzian fits, with/without inclusion of the NOE(-1.6) pool, were performed on CEST Z-spectra obtained from healthy rat brains and rats with 9L tumors. These fits aimed to further validate the presence of the NOE(-1.6) signal and quantify its amplitude.

RESULTS

The NOE(-1.6) signal exhibited a dramatic change following the injection of monocrystalline iron oxide nanoparticles, confirming its presence at 4.7T. The NOE(-1.6) signal reached its peak at a saturation power of ∼0.75 μT, indicating an optimized power level. The multiple-pool Lorentzian fit without the NOE(-1.6) pool showed higher residuals around -1.6 ppm compared to the fit with this pool, further supporting the presence of this signal. The NOE(-1.6) signal did not exhibit significant variation in the corpus callosum and caudate putamen regions, but it showed a significant decrease in tumors, which aligns with previous findings at 9.4T.

CONCLUSION

This study successfully demonstrated the presence of the NOE(-1.6) signal at 4.7T, which provides valuable insights into its potential applications at lower field strengths.

Validation of the presence of fast exchanging amine CEST effect at low saturation powers and its influence on the quantification of APT

PURPOSE

Accurately quantifying the amide proton transfer (APT) effect and the underlying exchange parameters is crucial for its applications, but previous studies have reported conflicting results. In these quantifications, the CEST effect from the fast exchange amine was always ignored because it was considered weak with low saturation powers. This paper aims to evaluate the influence of the fast exchange amine CEST on the quantification of APT at low saturation powers.

METHODS

A quantification method with low and high saturation powers was used to distinguish APT from the fast exchange amine CEST effect. Simulations were conducted to assess the method's capability to separate APT from the fast exchange amine CEST effect. Animal experiments were performed to assess the relative contributions from the fast exchange amine and amide to CEST signals at 3.5 ppm. Three APT quantification methods, each with varying degrees of contamination from the fast exchange amine, were employed to process the animal data to assess the influence of the amine on the quantification of APT effect and the exchange parameters.

RESULTS

The relative size of the fast exchange amine CEST effect to APT effect gradually increases with increasing saturation power. At 9.4 T, it increases from approximately 20% to 40% of APT effect with a saturation power increase from 0.25 to 1 μT.

CONCLUSION

The fast exchange amine CEST effect leads overestimation of APT effect, fitted amide concentration, and amide-water exchange rate, potentially contributing to the conflicting results reported in previous studies.

Isolation of amide proton transfer effect and relayed nuclear Overhauser enhancement effect at -3.5ppm using CEST with double saturation powers

PURPOSE

Quantifications of amide proton transfer (APT) and nuclear Overhauser enhancement (rNOE(-3.5)) mediated saturation transfer with high specificity are challenging because their signals measured in a Z-spectrum are overlapped with confounding signals from direct water saturation (DS), semi-solid magnetization transfer (MT), and CEST of fast-exchange pools. In this study, based on two canonical CEST acquisitions with double saturation powers (DSP), a new data-postprocessing method is proposed to specifically quantify the effects of APT and rNOE.

METHODS

For CEST imaging with relatively low saturation powers (ω 1 2 $$ {\upomega}_1^2 $$ ), both the fast-exchange CEST effect and the semi-solid MT effect roughly depend onω 1 2 $$ {\upomega}_1^2 $$ , whereas the slow-exchange APT/rNOE(-3.5) effect do not, which is exploited to isolate a part of the APT and rNOE effects from the confounding signals in this study. After a mathematical derivation for the establishment of the proposed method, numerical simulations based on Bloch equations are then performed to demonstrate its specificity to detections of the APT and rNOE effects. Finally, an in vivo validation of the proposed method is conducted using an animal tumor model at a 4.7 T MRI scanner.

RESULTS

The simulations show that DSP-CEST can quantify the effects of APT and rNOE and substantially eliminate the confounding signals. The in vivo experiments demonstrate that the proposed DSP-CEST method is feasible for the imaging of tumors.

CONCLUSION

The data-postprocessing method proposed in this study can quantify the APT and rNOE effects with considerably increased specificities and a reduced cost of imaging time.

Assignment of molecular origins of NOE signal at -3.5 ppm in the brain

PURPOSE

Nuclear Overhauser enhancemen mediated saturation transfer effect, termed NOE (-3.5 ppm), is a major source of CEST MRI contrasts at 3.5 ppm in the brain. Previous phantom experiments have demonstrated that both proteins and lipids, two major components in tissues, have substantial contributions to NOE (-3.5 ppm) signals. Their relative contributions in tissues are informative for the interpretation of NOE (-3.5 ppm) contrasts that could provide potential imaging biomarkers for relevant diseases, which remain incompletely understood.

METHODS

Experiments on homogenates and supernatants of brain tissues collected from healthy rats, that could isolate proteins from lipids, were performed to evaluate the relative contribution of lipids to NOE (-3.5 ppm) signals. On the other hand, experiments on ghost membranes with varied pH, and reconstituted phospholipids with different chemical compositions were conducted to study the dependence of NOE (-3.5 ppm) on physiological conditions. Besides, CEST imaging on rat brains bearing 9 L tumors and healthy rat brains was performed to analyze the causes of the NOE (-3.5 ppm) contrast variations between tumors and normal tissues, and between gray matter and white matter.

RESULTS

Our experiments reveal that lipids have dominant contributions to the NOE (-3.5 ppm) signals. Further analysis suggests that decreased NOE (-3.5 ppm) signals in tumors and higher NOE (-3.5 ppm) signals in white matter than in gray matter are mainly explained by changes in membrane lipids, rather than proteins.

CONCLUSION

NOE (-3.5 ppm) could be exploited as a highly sensitive MRI contrast for imaging membrane lipids in the brain.

The exchange rate of creatine CEST in mouse brain

PURPOSE

To estimate the exchange rate of creatine (Cr) CEST and to evaluate the pH sensitivity of guanidinium (Guan) CEST in the mouse brain.

METHODS

Polynomial and Lorentzian line-shape fitting (PLOF) were implemented to extract the amine, amide, and Guan CEST signals from the brain Z-spectrum at 11.7T. Wild-type (WT) and knockout mice with the guanidinoacetate N-methyltransferase deficiency (GAMT-/- ) that have low Cr and phosphocreatine (PCr) concentrations in the brain were used to extract the CrCEST signal. To quantify the CrCEST exchange rate, a two-step Bloch-McConnell (BM) fitting was used to fit the CrCEST line-shape, B1 -dependent CrCEST, and the pH response with different B1 values. The pH in the brain cells was altered by hypercapnia to measure the pH sensitivity of GuanCEST.

RESULTS

Comparison between the Z-spectra of WT and GAMT-/- mice suggest that the CrCEST is between 20% and 25% of the GuanCEST in the Z-spectrum at 1.95 ppm between B1  = 0.8 and 2 μT. The CrCEST exchange rate was found to be around 240-480 s-1 in the mouse brain, which is significantly lower than that in solutions (∼1000 s-1 ). The hypercapnia study on the mouse brain revealed that CrCEST at B1  = 2 μT and amineCEST at B1  = 0.8 μT are highly sensitive to pH change in the WT mouse brain.

CONCLUSIONS

The in vivo CrCEST exchange rate is slow, and the acquisition parameters for the CrCEST should be adjusted accordingly. CrCEST is the major contribution to the opposite pH-dependence of GuanCEST signal under different conditions of B1 in the brain.

Chemical exchange saturation transfer imaging of creatine, phosphocreatine, and protein arginine residue in tissues

Chemical exchange saturation transfer (CEST) MRI has become a promising technique to assay target proteins and metabolites through their exchangeable protons, noninvasively. The ubiquity of creatine (Cr) and phosphocreatine (PCr) due to their pivotal roles in energy homeostasis through the creatine phosphate pathway has made them prime targets for CEST in the diagnosis and monitoring of disease pathologies, particularly in tissues heavily dependent on the maintenance of rich energy reserves. Guanidinium CEST from protein arginine residues (i.e. arginine CEST) can also provide information about the protein profile in tissue. However, numerous obfuscating factors stand as obstacles to the specificity of arginine, Cr, and PCr imaging through CEST, such as semisolid magnetization transfer, fast chemical exchanges such as primary amines, and the effects of nuclear Overhauser enhancement from aromatic and amide protons. In this review, the specific exchange properties of protein arginine residues, Cr, and PCr, along with their validation, are discussed, including the considerations necessary to target and tune their signal effects through CEST imaging. Additionally, strategies that have been employed to enhance the specificity of these exchanges in CEST imaging are described, along with how they have opened up possible applications of protein arginine residues, Cr and PCr CEST imaging in the study and diagnosis of pathology. A clear understanding of the capabilities and caveats of using CEST to image these vital metabolites and mitigation strategies is crucial to expanding the possibilities of this promising technology.

A snapshot of the vast array of diamagnetic CEST MRI contrast agents

Since the inception of CEST MRI in the 1990s, a number of compounds have been identified as suitable for generating contrast, including paramagnetic lanthanide complexes, hyperpolarized atom cages and, most interesting, diamagnetic compounds. In the past two decades, there has been a major emphasis in this field on the identification and application of diamagnetic compounds that have suitable biosafety profiles for usage in medical applications. Even in the past five years there has been a tremendous growth in their numbers, with more and more emphasis being placed on finding those that can be ultimately used for patient studies on clinical 3 T scanners. At this point, a number of endogenous compounds present in tissue have been identified, and also natural and synthetic organic compounds that can be administered to highlight pathology via CEST imaging. Here we will provide a very extensive snapshot of the types of diamagnetic compound that can generate CEST MRI contrast, together with guidance on their utility on typical preclinical and clinical scanners and a review of the applications that might benefit the most from this new technology.

Glutamate-weighted CEST (gluCEST) imaging for mapping neurometabolism: An update on the state of the art and emerging findings from in vivo applications

Glutamate is the primary excitatory neurotransmitter in the mammalian central nervous system. As such, its proper regulation is essential to the healthy function of the human brain, and dysregulation of glutamate metabolism and compartmentalization underlies numerous neurological and neuropsychiatric pathologies. Glutamate-weighted chemical exchange saturation transfer (gluCEST) MRI is one of the only ways to non-invasively observe the relative concentration and spatial distribution of glutamate in the human brain. In the past 10 years, gluCEST has developed from a proof-of-concept experiment carried out in imaging phantoms and model systems to an increasingly sophisticated technique applied to reveal deviations from baseline neural metabolism in human beings, most notably in patients experiencing seizures of various origins or those on the psychosis spectrum. This article traces that progress, including in-depth discussion of the technical specifics of gluCEST and potential challenges to performing these experiments rigorously. We discuss the neurobiological context of glutamate, including the widely accepted hypotheses and models in the literature regarding its involvement in neurodegenerative diseases and other pathology. We then review the state of the art of in vivo glutamate detection by magnetic resonance imaging and the limitations on this front of in vivo MR spectroscopy. The gluCEST experiment is introduced and its advantages, challenges and limitations are thoroughly explored, beginning with the phantom experiment results demonstrated in the initial publication, through the latest approaches to correcting human brain images for B₁ inhomogeneity. We then give a comprehensive overview of preclinical applications demonstrated to date, including Alzheimer's disease, Parkinson's disease, Huntington's disease, Traumatic brain injury and cancer, followed by a similar discussion of human studies. Finally, we highlight emerging applications, and discuss technical improvements on the horizon that hold promise for improving the robustness and versatility of gluCEST and its increasing presence in the arena of translational and precision medicine.

Amine-weighted chemical exchange saturation transfer magnetic resonance imaging in brain tumors

Amine-weighted chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) is particularly valuable as an amine- and pH-sensitive imaging technique in brain tumors, targeting the intrinsically high concentration of amino acids with exchangeable amine protons and reduced extracellular pH in brain tumors. Amine-weighted CEST MRI contrast is dependent on the glioma genotype, likely related to differences in degree of malignancy and metabolic behavior. Amine-weighted CEST MRI may provide complementary value to anatomic imaging in conventional and exploratory therapies in brain tumors, including chemoradiation, antiangiogenic therapies, and immunotherapies. Continual improvement and clinical testing of amine-weighted CEST MRI has the potential to greatly impact patients with brain tumors by understanding vulnerabilities in the tumor microenvironment that may be therapeutically exploited.

Lateralization of temporal lobe epileptic foci with automated chemical exchange saturation transfer measurements at 3 Tesla

BACKGROUND

Magnetic Resonance Imaging (MRI) is an indispensable tool for the diagnosis of temporal lobe epilepsy (TLE). However, about 30% of TLE patients show no lesion on structural MRI (sMRI-negative), posing a significant challenge for presurgical evaluation. This study aimed to investigate whether chemical exchange saturation transfer (CEST) MRI at 3 Tesla can lateralize the epileptic focus of TLE and study the metabolic contributors to the CEST signal measured.

METHODS

Forty TLE subjects (16 males and 24 females) were included in this study. An automated data analysis pipeline was established, including segmentation of the hippocampus and amygdala (HA), calculation of four CEST metrics and quantitative relaxation times (T₁ and T₂), and construction of prediction models by logistic regression. Furthermore, a modified two-stage Bloch-McConnell fitting method was developed to investigate the molecular imaging mechanism of 3 T CEST in identifying epileptic foci of TLE.

FINDINGS

The mean CEST ratio (CESTR) metric within 2.25-3.25 ppm in the HA was the most powerful index in predicting seizure laterality, with an area under the receiver-operating characteristic curve (AUC) of 0.84. And, the combination of T₂ and CESTR further increased the AUC to 0.92. Amine and guanidinium moieties were the two leading contributors to the CEST contrast between the epileptogenic HA and the normal HA.

INTERPRETATION

CEST at 3 Tesla is a powerful modality that can predict seizure laterality with high accuracy. This study can potentially facilitate the clinical translation of CEST MRI in identifying the epileptic foci of TLE or other localization-related epilepsies.

FUNDING

National Natural Science Foundation of China, Science Technology Department of Zhejiang Province, and Zhejiang University.

Assignment of molecular origins of NOE signal at -3.5 ppm in the brain

Purpose

Nuclear Overhauser Enhancement mediated saturation transfer effect, termed NOE(-3.5 ppm), is a major source of chemical exchange saturation transfer (CEST) MRI contrasts at 3.5 ppm in the brain. Previous phantom experiments have demonstrated that both proteins and lipids, two major components in tissues, have substantial contributions to NOE(-3.5 ppm) signals. Their relative contributions in tissues are informative for the interpretation of NOE(-3.5 ppm) contrasts that could provide potential imaging biomarkers for relevant diseases, which remain incompletely understood.

Methods

Experiments on homogenates and supernatants of brain tissues collected from healthy rats, that could isolate proteins from lipids, were performed to evaluate the relative contribution of lipids to NOE(-3.5 ppm) signals. On the other hand, experiments on ghost membranes with varied pH, and reconstituted phospholipids with different chemical compositions were conducted to study the dependence of NOE(-3.5 ppm) on physiological conditions. Besides, CEST imaging on rat brains bearing 9L tumors and healthy rat brains was performed to analyze the causes of the NOE(-3.5 ppm) contrast variations between tumors and normal tissues, and between gray matter and white matter.

Results

Our experiments reveal that lipids have dominant contributions to the NOE (-3.5 ppm) signals. Further analysis suggests that decreased NOE(-3.5 ppm) signals in tumors and higher NOE(-3.5 ppm) signals in white matter than in gray matter are mainly explained by changes in membrane lipids, rather than proteins.

Conclusion

NOE(-3.5 ppm) could be exploited as a highly sensitive MRI contrast for imaging membrane lipids in the brain.

NOE-weighted imaging in tumors using low-duty-cycle 2π-CEST

PURPOSE

Nuclear Overhauser enhancement (NOE)-mediated CEST imaging at -3.5 ppm has shown clinical interest in diagnosing tumors. Multiple-pool Lorentzian fit has been used to quantify NOE, which, however, requires a long scan time. Asymmetric analysis of CEST signals could be a simple and fast method to quantify this NOE, but it has contamination from the amide proton transfer (APT) at 3.5 ppm. This work proposes a new method using an asymmetric analysis of a low-duty-cycle pulsed-CEST sequence with a flip angle of 360°, termed 2π-CEST, to reduce the contribution from APT.

METHODS

Simulations were used to evaluate the capability of the 2π-CEST to reduce APT. Experiments on animal tumor models were performed to show its advantages compared with the conventional asymmetric analysis. Samples of reconstituted phospholipids and proteins were used to evaluate the molecular origin of this NOE.

RESULTS

The 2π-CEST has reduced contribution from APT. In tumors where we show that the NOE is comparable to the APT effect, reducing the contamination from APT is crucial. The results show that the NOE signal obtained with 2π-CEST in tumor regions appears more homogeneous than that obtained with the conventional method. The phantom study showed that both phospholipids and proteins contribute to the NOE at -3.5 ppm.

CONCLUSION

The NOE at -3.5 ppm has a different contrast mechanism from APT and other CEST/NOE effects. The proposed 2π-CEST is more accurate than the conventional asymmetric analysis in detecting NOE, and requires much less scan time than the multiple-pool Lorentzian fit.

B0 Correction for 3T Amide Proton Transfer (APT) MRI Using a Simplified Two-Pool Lorentzian Model of Symmetric Water and Asymmetric Solutes

Amide proton transfer (APT)-weighted MRI is a promising molecular imaging technique that has been employed in clinic for detection and grading of brain tumors. MTRasym, the quantification method of APT, is easily influenced by B0 inhomogeneity and causes artifacts. Current model-free interpolation methods have enabled moderate B0 correction for middle offsets, but have performed poorly at limbic offsets. To address this shortcoming, we proposed a practical B0 correction approach that is suitable under time-limited sparse acquisition scenarios and for B1 ≥ 1 μT under 3T. In this study, this approach employed a simplified Lorentzian model containing only two pools of symmetric water and asymmetric solutes, to describe the Z-spectral shape with wide and ‘invisible’ CEST peaks. The B0 correction was then performed on the basis of the fitted two-pool Lorentzian lines, instead of using conventional model-free interpolation. The approach was firstly evaluated on densely sampled Z-spectra data by using the spline interpolation of all acquired 16 offsets as the gold standard. When only six offsets were available for B0 correction, our method outperformed conventional methods. In particular, the errors at limbic offsets were significantly reduced (n = 8, p < 0.01). Secondly, our method was assessed on the six-offset APT data of nine brain tumor patients. Our MTRasym (3.5 ppm), using the two-pool model, displayed a similar contrast to the vendor-provided B0-orrected MTRasym (3.5 ppm). While the vendor failed in correcting B0 at 4.3 and 2.7 ppm for a large portion of voxels, our method enabled well differentiation of B0 artifacts from tumors. In conclusion, the proposed approach could alleviate analysis errors caused by B0 inhomogeneity, which is useful for facilitating the comprehensive metabolic analysis of brain tumors.

Evaluating the Cisplatin Dose Dependence of Testicular Dysfunction using Creatine Chemical Exchange Saturation Transfer Imaging

Chemical exchange saturation transfer (CEST) imaging is a non-invasive molecular imaging technique for indirectly measuring low-concentration endogenous metabolites. Conventional CEST has low specificity, owing to the effects of spillover, magnetization transfer (MT), and T1 relaxation, thus necessitating an inverse Z-spectrum analysis. We aimed to investigate the usefulness of inverse Z-spectrum analysis in creatine (Cr)-CEST in mice, by conducting preclinical 7T-magnetic resonance imaging (MRI) and comparing the conventional analysis metric magnetization transfer ratio (MTRconv) with the novel metric apparent exchange-dependent relaxation (AREX). We performed Cr-CEST imaging using 7T-MRI on mouse testes, using C57BL/6 mice as the control and a cisplatin-treated model. We prepared different doses of cisplatin to observe its dose dependence effect on testicular function. CEST imaging was obtained using an MT pulse with varying saturation frequencies, ranging from −4.8 ppm to +4.8 ppm. The application of control mouse testes improved the specificity of the CEST effect and image contrast between the testes and testicular epithelium. The cisplatin-treated model revealed impaired testicular function, and the Cr-CEST imaging displayed decreased Cr levels in the testes. There was a significant difference between the low- and high-dose models. The MTR values of Cr-CEST reflected the cisplatin dose dependence of testicular dysfunction.

Evaluation of Temozolomide Treatment for Glioblastoma Using Amide Proton Transfer Imaging and Diffusion MRI

Simple Summary

Glioblastoma (GBM), the most frequent and malignant histological type of glioma, is associated with a very high mortality rate. MRI is a useful method for the evaluation of tumor growth. However, there are few studies that have quantitatively evaluated the changes in disease state after TMZ treatment against GBM, and it is not fully understood how the effects of treatment are reflected in the quantitative values measured on MRI. We used the C6 glioma rat model to evaluate the tumor changes due to chemotherapy at different doses of TMZ in terms of quantitative values measured by neurite orientation dispersion and density imaging (NODDI) and amide proton transfer (APT) imaging using 7T-MRI. These methods can evaluate the microstructural changes caused by TMZ-induced tumor growth inhibition.

Abstract

This study aimed to evaluate tumor changes due to chemotherapy with temozolomide (TMZ) in terms of quantitative values measured by APT imaging and NODDI. We performed TMZ treatment (administered orally by gavage to the TMZ-40 mg and TMZ-60 mg groups) on 7-week-old male Wistar rats with rat glioma C6 implanted in the right brain. T₂WI, APT imaging, diffusion tensor imaging (DTI), and NODDI were performed on days 7 and 14 after implantation using 7T-MRI, and the calculated quantitative values were statistically compared. Then, HE staining was performed on brain tissue at day 7 and day 14 for each group to compare the results with the MR images. TMZ treatment inhibited tumor growth and necrotic area formation. The necrotic areas observed upon hematoxylin and eosin (HE) staining were consistent with the MTR low-signal areas observed upon APT imaging. The intracellular volume fraction (ICVF) map of the NODDI could best show the microstructure of the tumor, and its value could significantly highlight the difference in treatment effects at different TMZ doses. APT imaging and NODDI can be used to detect the microstructural changes caused by TMZ-induced tumor growth inhibition. The ICVF may be useful as a parameter for determining the effect of TMZ.

Relaxation-Compensated Chemical Exchange Saturation Transfer MRI in the Brain at 7T: Application in Relapsing-Remitting Multiple Sclerosis

Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) can probe tissue biochemistry in vivo with high resolution and sensitivity without requiring exogenous contrast agents. Applying CEST MRI at ultrahigh field provides advantages of increasing spectral resolution and improving sensitivity to metabolites with faster proton exchange rates such as glutamate, a critical neurotransmitter in the brain. Prior magnetic resonance spectroscopy and CEST MRI studies have revealed altered regulation of glutamate in patients with multiple sclerosis (MS). While CEST imaging facilitates new strategies for investigating the pathology underlying this complex and heterogeneous neurological disease, CEST signals are contaminated or diluted by concurrent effects (e.g., semi-solid magnetization transfer (MT) and direct water saturation) and are scaled by the T1 relaxation time of the free water pool which may also be altered in the context of disease. In this study of 20 relapsing-remitting MS patients and age- and sex-matched healthy volunteers, glutamate-weighted CEST data were acquired at 7.0 T. A Lorentzian fitting procedure was used to remove the asymmetric MT contribution from CEST z-spectra, and the apparent exchange-dependent relaxation (AREX) correction was applied using an R1 map derived from an inversion recovery sequence to further isolate glutamate-weighted CEST signals from concurrent effects. Associations between AREX and cognitive function were examined using the Minimal Assessment of Cognitive Function in MS battery. After isolating CEST effects from MT, direct water saturation, and T1 effects, glutamate-weighted AREX contrast remained higher in gray matter than in white matter, though the difference between these tissues decreased. Glutamate-weighted AREX in normal-appearing gray and white matter in MS patients did not differ from healthy gray and white matter but was significantly elevated in white matter lesions. AREX in some cortical regions and in white matter lesions correlated with disability and measures of cognitive function in MS patients. However, further studies with larger sample sizes are needed to confirm these relationships due to potential confounding effects. The application of MT and AREX corrections in this study demonstrates the importance of isolating CEST signals for more specific characterization of the contribution of metabolic changes to tissue pathology and symptoms in MS.

Whole brain mapping of glutamate distribution in adult and old primates at 11.7T

Glutamate is the amino acid with the highest cerebral concentration. It plays a central role in brain metabolism. It is also the principal excitatory neurotransmitter in the brain and is involved in multiple cognitive functions. Alterations of the glutamatergic system may contribute to the pathophysiology of many neurological disorders. For example, changes of glutamate availability are reported in rodents and humans during Alzheimer's and Huntington's diseases, epilepsy as well as during aging. Most studies evaluating cerebral glutamate have used invasive or spectroscopy approaches focusing on specific brain areas. Chemical Exchange Saturation Transfer imaging of glutamate (gluCEST) is a recently developed imaging technique that can be used to study relative changes in glutamate distribution in the entire brain with higher sensitivity and at higher resolution than previous techniques. It thus has strong potential clinical applications to assess glutamate changes in the brain. High field is a key condition to perform gluCEST images with a meaningful signal to noise ratio. Thus, even if some studies started to evaluate gluCEST in humans, most studies focused on rodent models that can be imaged at high magnetic field. In particular, systematic characterization of gluCEST contrast distribution throughout the whole brain has never been performed in humans or non-human primates. Here, we characterized for the first time the distribution of the gluCEST contrast in the whole brain and in large-scale networks of mouse lemur primates at 11.7 Tesla. Because of its small size, this primate can be imaged in high magnetic field systems. It is widely studied as a model of cerebral aging or Alzheimer's disease. We observed high gluCEST contrast in cerebral regions such as the nucleus accumbens, septum, basal forebrain, cortical areas 24 and 25. Age-related alterations of this biomarker were detected in the nucleus accumbens, septum, basal forebrain, globus pallidus, hypophysis, cortical areas 24, 21, 6 and in olfactory bulbs. An age-related gluCEST contrast decrease was also detected in specific neuronal networks, such as fronto-temporal and evaluative limbic networks. These results outline regional differences of gluCEST contrast and strengthen its potential to provide new biomarkers of cerebral function in primates.

Deep neural network based CEST and AREX processing: Application in imaging a model of Alzheimer's disease at 3 T

PURPOSE

To optimize and apply deep neural network based CEST (deepCEST) and apparent exchange dependent-relaxation (deepAREX) for imaging the mouse brain with Alzheimer's disease (AD) at 3T MRI.

METHODS

CEST and T₁ data of central and anterior brain slices of 10 AD mice and 10 age-matched wild type (WT) mice were acquired at a 3T animal MRI scanner. The networks of deepCEST/deepAREX were optimized and trained on the WT data. The CEST/AREX contrasts of AD and WT mice predicted by the networks were analyzed and further validated by immunohistochemistry.

RESULTS

After optimization and training on CEST data of WT mice, deepCEST/deepAREX could rapidly (~1 s) generate precise CEST and AREX results for unseen CEST data of AD mice, indicating the accuracy and generalization of the networks. Significant lower amide weighted (3.5 ppm) signal related to amyloid β-peptide (Aβ) plaque depositions, which was validated by immunohistochemistry results, was detected in both central and anterior brain slices of AD mice compared to WT mice. Decreased magnetization transfer (MT) signal was also found in AD mice especially in the anterior slice.

CONCLUSION

DeepCEST/deepAREX could rapidly generate accurate CEST/AREX contrasts in animal study. The well-optimized deepCEST/deepAREX have potential for AD differentiation at 3T MRI.

Comparative evaluation of polynomial and Lorentzian lineshape-fitted amine CEST imaging in acute ischemic stroke

Purpose

Chemical exchange saturation transfer signals from amines are sensitive to pH, and detection of these signals can serve as an alternative pH imaging method to amide proton transfer (APT). However, conflicting results regarding amine CEST imaging at 2 ppm in ischemic stroke have been reported. Here, we correlated amine CEST with APT in animal stroke models to evaluate its specificity to pH, and investigated the reason for the different results through simulations and sample studies.

Methods

A three‐point quantification method was used to quantify APT. A polynomial fit method and a multiple‐pool Lorentzian fit method were used to quantify amine CEST. Samples of creatine and glutamate were prepared to study the different CEST effects from arginine amine and fast exchanging pools. Samples of tissue homogenates with different pH were prepared to study the variation in CEST signals due only to changes in pH.

Results

The polynomial fit of amine CEST at 2 ppm had a significant correlation with APT, whereas the Lorentzian fit did not. Further studies showed that arginine amine contributed to the polynomial fit, whereas both the arginine amine and the fast exchanging pools contributed to the Lorentzian fit with their CEST effects varying in opposite directions after stroke. The CEST signal from the fast exchanging pool decreased, probably due to the reduced pool concentration but not pH.

Conclusion

The variation in opposite directions led to an insignificant correlation of the Lorentzian fit of amine CEST with APT and the different results in different experimental conditions.

Metabolic Magnetic Resonance Imaging in Neuroimaging: Magnetic Resonance Spectroscopy, Sodium Magnetic Resonance Imaging and Chemical Exchange Saturation Transfer

Magnetic resonance (MR) is a powerful and versatile technique that offers much more beyond conventional anatomic imaging and has the potential of probing in vivo metabolism. Although MR spectroscopy (MRS) predates clinical MR imaging (MRI), its clinical application has been limited by technical and practical challenges. Other MR techniques actively being developed for in vivo metabolic imaging include sodium concentration imaging and chemical exchange saturation transfer. This article will review some of the practical aspects of MRS in neuroimaging, introduce sodium MRI and chemical exchange saturation transfer MRI, and highlight some of their emerging clinical applications.

The use of variable delay multipulse chemical exchange saturation transfer for separately assessing different CEST pools in the human brain at 7T

PURPOSE

Current challenges of in vivo CEST imaging include overlapping signals from different pools. The overlap arises from closely resonating pools and/or the broad magnetization transfer contrast (MTC) from macromolecules. This study aimed to evaluate the feasibility of variable delay multipulse (VDMP) CEST to separately assess solute pools with different chemical exchange rates in the human brain in vivo, while mitigating the MTC.

METHODS

VDMP saturation buildup curves were simulated for amines, amides, and relayed nuclear Overhauser effect. VDMP data were acquired from glutamate and bovine serum albumin phantoms, and from six healthy volunteers at 7T. For the in vivo data, MTC removal was performed via a three-pool Lorentzian fitting. Different B₁ amplitudes and mixing times were used to evaluate CEST pools with different exchange rates.

RESULTS

The results show the importance of removing MTC when applying VDMP in vivo and the influence of B₁ for distinguishing different pools. Finally, the optimal B₁ and mixing times to effectively saturate slow- and fast-exchanging components are also reported. Slow-exchanging amides and rNOE components could be distinguished when using B₁ = 1 μT and t_mix = 10 ms and 40 ms, respectively. Fast-exchanging components reached the highest saturation when using a B₁ = 2.8 μT and t_mix = 0 ms.

CONCLUSION

VDMP is a powerful CEST-editing tool, exploiting chemical exchange-rate differences. After MTC removal, it allows separate assessment of slow- and fast-exchanging solute pools in in vivo human brain.

Chemical exchange saturation transfer imaging for epilepsy secondary to tuberous sclerosis complex at 3 T: Optimization and analysis

The homeostasis of various metabolites is impaired in epilepsy secondary to the tuberous sclerosis complex (TSC). Chemical exchange saturation transfer (CEST) imaging is an emerging molecular MRI technique that can detect various metabolites and proteins in vivo. However, the role of CEST imaging for TSC-associated epilepsy has not been assessed. Here, we aim to investigate the feasibility of applying CEST imaging to TSC-associated epilepsy, optimize the CEST acquisition parameters, and provide an analysis method for exploring the dominant molecular contributors to the CEST signal measured. Nine TSC epilepsy patients were scanned on a 3-T MRI system. The CEST saturation frequencies were swept from -6 to 6 ppm with 12 different combinations of saturation power (4, 3, 2 and 1 μT) and duration (1000, 700 and 400 ms). Furthermore, a two-stage simulation method based on the seven-pool Bloch-McConnell model was proposed to assess the contribution of each exchangeable pool to the CEST signal in normal-appearing white matter and cortical tubers, which avoided the complexity and uncertainty of full Bloch-McConnell fitting. The results showed that under the optimal saturation duration of 1000 ms, the greatest contrast between tubers and normal tissues occurred around 3, 2.5, 1.75 and 3.5 ppm for B₁ of 4, 3, 2 and 1 μT, respectively. At the optimal frequency offsets, the CEST values of tubers were significantly higher than those in the normal brain tissues (P < 0.01). Furthermore, the two-stage analysis suggested that the amine pool played a dominant role in yielding the contrast between cortical tubers and normal tissues. These results indicate that CEST MRI may serve as a potentially useful tool for identifying tubers in TSC, and the two-stage analysis method may provide a route for investigating the molecular contributions to the CEST contrast in biological tissues.

Glutamate Chemical Exchange Saturation Transfer Imaging and Functional Alterations of Hippocampus in Rat Depression Model: A Pilot Study

BACKGROUND

Adjusting abnormal glutamate neurotransmission is a crucial mechanism in the treatment of depression. However, few non-invasive techniques could effectively detect changes in glutamate neurotransmitters, and no consensus exists on whether glutamate could affect resting-state function changes in depression.

PURPOSE

To study the changes in glutamate chemical exchange saturation transfer (GluCEST) value in the hippocampus of rat model exposed to chronic unpredictable mild stress (CUMS), and to explore the effect of this change on the activity of hippocampal glutamatergic neurons.

STUDY TYPE

Prospective animal study.

ANIMAL MODEL

Twenty male Sprague-Dawley rats (200-300 g).

FIELD STRENGTH/SEQUENCE

7.0 T scanner. Fat rapid acquisition relaxation enhancement sequence for GluCEST, and echo planner imaging sequence for resting-state functional magnetic resonance imaging (rs_fMRI).

ASSESSMENT

Rats were divided into two groups: CUMS group (N = 10) and control group (CTRL, N = 10). The magnetization transfer ratio asymmetry analysis was used to quantify the GluCEST data, and evaluate the rs_fMRI data through the amplitude of low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) analysis.

STATISTICAL TESTS

A t-test was used to compare the difference in GluCEST or rs_fMRI between CUMS and CTRL groups. Spearman's correlation was applied to explore the correlation between GluCEST values and abnormal fMRI values in hippocampus. Statistical significance was set at P < 0.05.

RESULTS

The GluCEST value in the left hippocampus has changed significantly (3.3 ± 0.3 [CUMS] vs. 3.9 ± 0.4 [CTRL], P < 0.05). In addition, the GluCEST value was significantly positively correlated with the ALFF values (r = 0.5, P < 0. 05, df = 7) and negatively correlated with the ReHo values (r = -0.6, P < 0.05, df = 7).

DATA CONCLUSION

GluCEST technique has the feasibility of mapping glutamate changes in rat depression. Glutamate neurotransmitters are important factors affecting the abnormal function of neural activity.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 1.

Glutamate connectivity associations converge upon the salience network in schizophrenia and healthy controls

Alterations in cortical inter-areal functional connectivity, and aberrant glutamatergic signalling are implicated in the pathophysiology of schizophrenia but the relationship between the two is unclear. We used multimodal imaging to identify areas of convergence between the two systems. Two separate cohorts were examined, comprising 195 participants in total. All participants received resting state functional MRI to characterise functional brain networks and proton magnetic resonance spectroscopy (1H-MRS) to measure glutamate concentrations in the frontal cortex. Study A investigated the relationship between frontal cortex glutamate concentrations and network connectivity in individuals with schizophrenia and healthy controls. Study B also used 1H-MRS, and scanned individuals with schizophrenia and healthy controls before and after a challenge with the glutamatergic modulator riluzole, to investigate the relationship between changes in glutamate concentrations and changes in network connectivity. In both studies the network based statistic was used to probe associations between glutamate and connectivity, and glutamate associated networks were then characterised in terms of their overlap with canonical functional networks. Study A involved 76 individuals with schizophrenia and 82 controls, and identified a functional network negatively associated with glutamate concentrations that was concentrated within the salience network (p < 0.05) and did not differ significantly between patients and controls (p > 0.85). Study B involved 19 individuals with schizophrenia and 17 controls and found that increases in glutamate concentrations induced by riluzole were linked to increases in connectivity localised to the salience network (p < 0.05), and the relationship did not differ between patients and controls (p > 0.4). Frontal cortex glutamate concentrations are associated with inter-areal functional connectivity of a network that localises to the salience network. Changes in network connectivity in response to glutamate modulation show an opposite effect compared to the relationship observed at baseline, which may complicate pharmacological attempts to simultaneously correct glutamatergic and connectivity aberrations.

Chemical exchange rotation transfer imaging of phosphocreatine in muscle

In chemical exchange saturation transfer (CEST) imaging, the signal at 2.6 ppm from the water resonance in muscle has been assigned to phosphocreatine (PCr). However, this signal has limited specificity for PCr since the signal is also sensitive to exchange with protein and macromolecular protons when using some conventional quantification methods, and will vary with changes in the water longitudinal relaxation rate. Correcting for these effects while maintaining reasonable acquisition times is challenging. As an alternative approach to overcome these problems, here we evaluate chemical exchange rotation transfer (CERT) imaging of PCr in muscle at 9.4 T. Specifically, the CERT metric, AREXdouble,cpw at 2.6 ppm, was measured in solutions containing the main muscle metabolites, in tissue homogenates with controlled PCr content, and in vivo in rat leg muscles. PCr dominates CERT metrics around 2.6 ppm (although with nontrivial confounding baseline contributions), indicating that CERT is well-suited to PCr specific imaging, and has the added benefit of requiring a relatively small number of acquisitions.

On the interference from agar in chemical exchange saturation transfer MRI parameter optimization in model solutions

Chemical exchange saturation transfer (CEST) MRI is currently set to become part of clinical routine as it enables indirect detection of low concentrated molecules and proteins. Recently, intermediate to fast exchanging functional groups of glucose and its derivatives, glutamate and dextran, have gained attention as promising CEST contrast agents. To increase the specificity of CEST MRI for certain functional groups, the presaturation module is commonly optimized. At an early stage, this is performed in well-defined model solutions, in which, for instance, the relaxation times are adjusted to mimic in vivo conditions. This often involves agar, assuming the substance would not yield significant CEST effects by itself, which the current study proves to be an invalid assumption. Model solutions at different pH values and concentrations of agar were investigated at different temperatures at a 9.4 T human whole body MR scanner. High power presaturation of around 4 μT, optimal for investigating intermediate to fast exchanging groups, was applied. Postprocessing included spatiotemporal corrections for B₀ and spatial corrections for B₁⁺ . CEST effects of up to 3 % of the bulk water signal were observed. From pH, concentration and temperature dependency, it was concluded that the observed behavior reflects a CEST effect of agar. It was also shown how to remove this undesirable contribution from CEST MRI data. It was concluded that if agar is involved in the CEST MRI parameter optimization process, its contribution to the observed effects has to be taken into account. CEST agent concentration must be sufficiently high to be able to neglect the contribution of agar, or a control sample at matched pH is necessary for correction. Experiments on pure agarose showed reduced CEST effects compared with agar but did not provide a neutral baseline either.

Regional Mapping of Brain Glutamate Distributions Using Glutamate-Weighted Chemical Exchange Saturation Transfer Imaging

PURPOSE

To investigate glutamate signal distributions in multiple brain regions of a healthy rat brain using glutamate-weighted chemical exchange saturation transfer (GluCEST) imaging.

METHOD

The GluCEST data were obtained using a 7.0 T magnetic resonance imaging (MRI) scanner, and all data were analyzed using conventional magnetization transfer ratio asymmetry in eight brain regions (cortex, hippocampus, corpus callosum, and rest of midbrain in each hemisphere). GluCEST data acquisition was performed again one month later in five randomly selected rats to evaluate the stability of the GluCEST signal. To evaluate glutamate level changes calculated by GluCEST data, we compared the results with the concentration of glutamate acquired from 1H magnetic resonance spectroscopy (1H MRS) data in the cortex and hippocampus.

RESULTS

GluCEST signals showed significant differences (all p ≤ 0.001) between the corpus callosum (-1.71 ± 1.04%; white matter) and other brain regions (3.59 ± 0.41%, cortex; 5.47 ± 0.61%, hippocampus; 4.49 ± 1.11%, rest of midbrain; gray matter). The stability test of GluCEST findings for each brain region was not significantly different (all p ≥ 0.263). In line with the GluCEST results, glutamate concentrations measured by 1H MRS also appeared higher in the hippocampus (7.30 ± 0.16 μmol/g) than the cortex (6.89 ± 0.72 μmol/g).

CONCLUSION

Mapping of GluCEST signals in the healthy rat brain clearly visualize glutamate distributions. These findings may yield a valuable database and insights for comparing glutamate signal changes in pre-clinical brain diseases.

In vivo MRI Successfully Reveals the Malformation of Cortical Development in Infant Rats

Objective: Malformations of cortical development (MCDs) are major causes of intractable epilepsies. To characterize the early neuroimaging findings of MCDs, we tried to identify the MRI features consistent with pathological findings in an infant rat MCD model, prenatally exposed to methylazoxymethanol (MAM), by using newly developed MRI techniques. Methods: At gestational day 15, two doses of MAM (15 mg/kg intraperitoneally) or normal saline were injected into pregnant rats. The offspring underwent in vivo MRI, including glutamate chemical exchange saturation transfer (GluCEST), ¹H-MR spectroscopy, and diffusion tensor imaging, at postnatal day (P) 15 using a 7T small-animal imaging system. Another set of prenatally MAM-exposed rats were sacrificed for histological staining. Results: At P15, the retrosplenial cortex (RSC) of rats with MCDs showed decreased neuronal nuclei, parvalbumin, and reelin expressions. Moreover, dendritic arborization of pyramidal cells in the RSC significantly decreased in infant rats with MCDs. In vivo MRI showed significantly decreased GluCEST (%) in the RSC of rats with MCDs (p = 0.000) and a significant correlation between GluCEST (%) and RSC thickness (r = 0.685, p = 0.003). The rats with MCDs showed reduced glutamate (p = 0.002), N-acetylaspartate (p = 0.002), and macromolecule and lipid levels (p = 0.027) and significantly reduced fractional anisotropy values in the RSC. Conclusion: In vivo MRI revealed reduced neuronal population and dendritic arborization in the RSC of infant rats with MCDs during the early postnatal period. These pathological changes of the cortex could serve as clinical imaging biomarkers of MCDs in infants.