CEST imaging of fast exchanging amine pools with corrections for competing effects at 9.4 T

B1 inhomogeneity corrected CEST MRI based on direct saturation removed omega plot model at 5T

PURPOSE

CEST can image macromolecules/compounds via detecting chemical exchange between labile protons and bulk water. B1 field inhomogeneity impairs CEST quantification. Conventional B1 inhomogeneity correction methods depend on interpolation algorithms, B1 choices, acquisition number or calibration curves, making reliable correction challenging. This study proposed a novel B1 inhomogeneity correction method based on a direct saturation (DS) removed omega plot model.

METHODS

Four healthy volunteers underwent B1 field mapping and CEST imaging under four nominal B1 levels of 0.75, 1.0, 1.5, and 2.0 μT at 5T. DS was resolved using a multi-pool Lorentzian model and removed from respective Z spectrum. Residual spectral signals were used to construct the omega plot as a linear function of 1/B 1 2 $$ {B}_1^2 $$ , from which corrected signals at nominal B1 levels were calculated. Routine asymmetry analysis was conducted to quantify amide proton transfer (APT) effect. Its distribution across white matter was compared before and after B1 inhomogeneity correction and also with the conventional interpolation approach.

RESULTS

B1 inhomogeneity yielded conspicuous artifact on APT images. Such artifact was mitigated by the proposed method. Homogeneous APT maps were shown with SD consistently smaller than that before B1 inhomogeneity correction and the interpolation method. Moreover, B1 inhomogeneity correction from two and four CEST acquisitions yielded similar results, superior over the interpolation method that derived inconsistent APT contrasts among different B1 choices.

CONCLUSION

The proposed method enables reliable B1 inhomogeneity correction from at least two CEST acquisitions, providing an effective way to improve quantitative CEST MRI.

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.

Specific and rapid guanidinium CEST imaging using double saturation power and QUASS analysis in a rodent model of global ischemia

PURPOSE

Guanidinium CEST is sensitive to metabolic changes and pH variation in ischemia, and it can offer advantages over conventional pH-sensitive amide proton transfer (APT) imaging by providing hyperintense contrast in stroke lesions. However, quantifying guanidinium CEST is challenging due to multiple overlapping components and a close frequency offset from water. This study aims to evaluate the applicability of a new rapid and model-free CEST quantification method using double saturation power, termed DSP-CEST, for isolating the guanidinium CEST effect from confounding factors in ischemia. To further reduce acquisition time, the DSP-CEST was combined with a quasi-steady state (QUASS) CEST technique to process non-steady-state CEST signals.

METHODS

The specificity and accuracy of the DSP-CEST method in quantifying the guanidinium CEST effect were assessed by comparing simulated CEST signals with/without the contribution from confounding factors. The feasibility of this method for quantifying guanidinium CEST was evaluated in a rat model of global ischemia induced by cardiac arrest and compared to a conventional multiple-pool Lorentzian fit method.

RESULTS

The DSP-CEST method was successful in removing all confounding components and quantifying the guanidinium CEST signal increase in ischemia. This suggests that the DSP-CEST has the potential to provide hyperintense contrast in stroke lesions. Additionally, the DSP-CEST was shown to be a rapid method that does not require the acquisition of the entire or a portion of the CEST Z-spectrum that is required in conventional model-based fitting approaches.

CONCLUSION

This study highlights the potential of DSP-CEST as a valuable tool for rapid and specific detection of viable tissues.

Amide Proton Transfer (APT) imaging in tumor with a machine learning approach using partially synthetic data

Purpose

Machine learning (ML) has been increasingly used to quantify chemical exchange saturation transfer (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, while training with fully simulated data may introduce bias due to 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 9L 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.

Noninvasive Characterization of Metabolic Changes in Ischemic Stroke Using Z-spectrum-fitted Multiparametric Chemical Exchange Saturation Transfer-weighted Magnetic Resonance Imaging

OBJECTIVE

This study aimed to noninvasively characterize the metabolic alterations in ischemic brain tissues using Z-spectrum-fitted multiparametric chemical exchange saturation transfer-weighted magnetic resonance imaging (CEST-MRI).

METHODS

Three sets of Z-spectrum data with saturation power (B1) values of 1.5, 2.5, and 3.5 µT, respectively, were acquired from 17 patients with ischemic stroke. Multiple contrasts contributing to the Z-spectrum, including fitted amide proton transfer (APTfitted), +2 ppm peak (CEST@2ppm), concomitantly fitted APTfitted and CEST@2ppm (APT&CEST@2ppm), semisolid magnetization transfer contrast (MT), aliphatic nuclear Overhauser effect (NOE), and direct saturation of water (DSW), were fitted with 4 and 5 Lorentzian functions, respectively. The CEST metrics were compared between ischemic lesions and contralateral normal white matter (CNWM), and the correlation between the CEST metrics and the apparent diffusion coefficient (ADC) was assessed. The differences in the Z-spectrum metrics under varied B1 values were also investigated.

RESULTS

Ischemic lesions showed increased APTfitted, CEST@2ppm, APT&CEST@2ppm, NOE, and DSW as well as decreased MT. APT&CEST@2ppm, MT, and DSW showed a significant correlation with ADC [APT&CEST@2ppm at the 3 B1 values: R=0.584/0.467/0.551; MT at the 3 B1 values: R=-0.717/-0.695/-0.762 (4-parameter fitting), R=-0.734/-0.711/-0.785 (5-parameter fitting); DSW of 4-/5-parameter fitting: R=0.794/0.811 (2.5 µT), R=0.800/0.790 (3.5 µT)]. However, the asymmetric analysis of amide proton transfer (APTasym) could not differentiate the lesions from CNWM and showed no correlation with ADC. Furthermore, the Z-spectrum contrasts varied with B1.

CONCLUSION

The Z-spectrum-fitted multiparametric CEST-MRI can comprehensively detect metabolic alterations in ischemic brain tissues.

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.

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.

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.

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.

Molecular Imaging of Brain Tumors and Drug Delivery Using CEST MRI: Promises and Challenges

Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) detects molecules in their natural forms in a sensitive and non-invasive manner. This makes it a robust approach to assess brain tumors and related molecular alterations using endogenous molecules, such as proteins/peptides, and drugs approved for clinical use. In this review, we will discuss the promises of CEST MRI in the identification of tumors, tumor grading, detecting molecular alterations related to isocitrate dehydrogenase (IDH) and O-6-methylguanine-DNA methyltransferase (MGMT), assessment of treatment effects, and using multiple contrasts of CEST to develop theranostic approaches for cancer treatments. Promising applications include (i) using the CEST contrast of amide protons of proteins/peptides to detect brain tumors, such as glioblastoma multiforme (GBM) and low-grade gliomas; (ii) using multiple CEST contrasts for tumor stratification, and (iii) evaluation of the efficacy of drug delivery without the need of metallic or radioactive labels. These promising applications have raised enthusiasm, however, the use of CEST MRI is not trivial. CEST contrast depends on the pulse sequences, saturation parameters, methods used to analyze the CEST spectrum (i.e., Z-spectrum), and, importantly, how to interpret changes in CEST contrast and related molecular alterations in the brain. Emerging pulse sequence designs and data analysis approaches, including those assisted with deep learning, have enhanced the capability of CEST MRI in detecting molecules in brain tumors. CEST has become a specific marker for tumor grading and has the potential for prognosis and theranostics in brain tumors. With increasing understanding of the technical aspects and associated molecular alterations detected by CEST MRI, this young field is expected to have wide clinical applications in the near future.

Contribution of blood to nuclear Overhauser effect at -1.6 ppm

PURPOSE

A relayed nuclear Overhauser enhancement (rNOE) saturation transfer effect at around -1.6 ppm from water, termed NOE(-1.6), was previously reported in rat and human brain, and some publications suggest that it may be related to blood. Here, we studied whether the NOE(-1.6) arises from blood through in vivo and ex vivo experiments.

METHODS

To evaluate the contribution from in vivo blood to NOE(-1.6), intravascular signals in rat brain were suppressed by two approaches: (1) signal acquisition with a diffusion-weighting of b = 400 s/mm2 ; (2) intravascular injection of 5 mg/kg monocrystalline iron oxide nanoparticle (MION). Ex vivo blood sample was also prepared. The signals were acquired using a chemical exchange saturation transfer (CEST) pulse sequence. Multiple-pool Lorentzian fitting of CEST Z-spectra was performed to quantify the NOE(-1.6) signal.

RESULTS

There are no significant variations in the fitted in vivo NOE(-1.6) signals when measured with or without diffusion-weighting, but significant signal decease does occur after injection of MION. The NOE(-1.6) signal from ex vivo blood is weaker than that from in vivo tissues.

CONCLUSION

Considering the relatively small volume of blood in brain, the in vivo experiments with diffusion weighting and the ex vivo experiments both suggest that the NOE(-1.6) is not mainly from blood. The mechanism for the in vivo experiments with MION are less clear. MION not only suppresses MR signals from intravascular space, but changes the susceptibility in the perivascular space. This result suggests that although the NOE(-1.6) is not mainly from blood, it may be vasculature dependent.

Brain pH Imaging and its Applications

Acid-base homeostasis and pH regulation are critical for normal tissue metabolism and physiology, and brain tissue pH alters in many diseased states. Several noninvasive tissue pH Magnetic Resonance (MR) techniques have been developed over the past few decades to shed light on pH change during tissue function and dysfunction. Nevertheless, there are still challenges for mapping brain pH noninvasively at high spatiotemporal resolution. To address this unmet biomedical need, chemical exchange saturation transfer (CEST) MR techniques have been developed as a sensitive means for non-invasive pH mapping. This article briefly reviews the basic principles of different pH measurement techniques with a focus on CEST imaging of pH. Emerging pH imaging applications in the tumor are provided as examples throughout the narrative, and CEST pH imaging in acute stroke is discussed in the final section.

The role of APT imaging in gliomas grading: A systematic review and meta-analysis

PURPOSE

Gliomas are diagnosed and staged by conventional MRI. Although non-conventional sequences such as perfusion-weighted MRI may differentiate low-grade from high-grade gliomas, they are not reliable enough yet. The latter is of paramount importance for patient management. In this regard, we aim to evaluate the role of Amide Proton Transfer (APT) imaging in grading gliomas as a non-invasive tool to provide reliable differentiation across tumour grades.

METHODS

A systematic search of PubMed, Medline and Embase was conducted to identify relevant publications between 01/01/2008 and 15/09/2020. Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) was used to assess studies' quality. A random-effects model standardized mean difference meta-analysis was performed to assess APT's ability to differentiate low-grade gliomas (LGGs) from high-grade gliomas (HGGs), WHO 2-4 grades, wild-type from mutated isocitrate dehydrogenase (IDH) gliomas, methylated from unmethylated O6-methylguanine-DNA methyltransferase (MGMT) gliomas. Area under the curve (AUC) of the Receiver Operating Characteristic (ROC) meta-analysis was employed to assess the diagnostic performance of APT.

RESULTS

23 manuscripts met the inclusion criteria and reported the use of APT to differentiate glioma grades with histopathology as reference standard. APT-weighted signal intensity can differentiate LGGs from HGGs with an estimated size effect of (-1.61 standard deviations (SDs), p < 0.0001), grade 2 from grade 3 (-1.83 SDs, p = 0.005), grade 2 from grade 4 (-2.34 SDs, p < 0.0001) and IDH wild-type from IDH mutated (0.94 SDs, p = 0.003) gliomas. The combined AUC of 0.84 highlights the good diagnostic performance of APT-weighted imaging in differentiating LGGs from HGGs.

CONCLUSIONS

APT imaging is an exciting prospect in differentiating LGGs from HGGs and with potential to predict the histopathological grade. However, more studies are required to optimize and improve its reliability.

Role of Chemical Exchange Saturation Transfer and Magnetization Transfer MRI in Detecting Metabolic and Structural Changes of Renal Fibrosis in an Animal Model at 3T

Objective

To investigate the value of combined chemical exchange saturation transfer (CEST) and conventional magnetization transfer imaging (MT) in detecting metabolic and structural changes of renal fibrosis in rats with unilateral ureteral obstruction (UUO) at 3T MRI.

Materials and Methods

Thirty-five Sprague-Dawley rats underwent UUO surgery (n = 25) or sham surgery (n = 10). The obstructed and contralateral kidneys were evaluated on days 1, 3, 5, and 7 after surgery. After CEST and MT examinations, ¹⁸F-labeled fluoro-2-deoxyglucose positron emission tomography was performed to quantify glucose metabolism. Fibrosis was measured by histology and western blots. Correlations were compared between asymmetrical magnetization transfer ratio at 1.2 ppm (MTR_asym(1.2ppm)) derived from CEST and maximum standard uptake value (SUV_max) and between magnetization transfer ratio (MTR) derived from MT and alpha-smooth muscle actin (α-SMA).

Results

On days 3 and 7, MTR_asym(1.2ppm) and MTR of UUO renal cortex and medulla were significantly different from those of contralateral kidneys (p < 0.05). On day 7, MTR_asym(1.2ppm) and MTR of UUO renal cortex and medulla were significantly different from those of sham-operated kidneys (p < 0.05). The MTR_asym(1.2ppm) of UUO renal medulla was fairly negatively correlated with SUV_max (r = −0.350, p = 0.021), whereas MTR of UUO renal medulla was strongly negatively correlated with α-SMA (r = −0.744, p < 0.001).

Conclusion

CEST and MT could provide metabolic and structural information for comprehensive assessment of renal fibrosis in UUO rats in 3T MRI and may aid in clinical monitoring of renal fibrosis in patients with chronic kidney disease.

Glutamate Chemical Exchange Saturation Transfer (GluCEST) Magnetic Resonance Imaging in Pre-clinical and Clinical Applications for Encephalitis

BACKGROUND

Encephalitis is a common central nervous system inflammatory disease that seriously endangers human health owing to the lack of effective diagnostic methods, which leads to a high rate of misdiagnosis and mortality. Glutamate is implicated closely in microglial activation, and activated microglia are key players in encephalitis. Hence, using glutamate chemical exchange saturation transfer (GluCEST) imaging for the early diagnosis of encephalitis holds promise.

METHODS

The sensitivity of GluCEST imaging with different concentrations of glutamate and other major metabolites in the brain was validated in phantoms. Twenty-seven Sprague-Dawley (SD) rats with encephalitis induced by Staphylococcus aureus infection were used for preclinical research of GluCEST imaging in a 7.0-Tesla scanner. For the clinical study, six patients with encephalitis, six patients with lacunar infarction, and six healthy volunteers underwent GluCEST imaging in a 3.0-Tesla scanner.

RESULTS

The number of amine protons on glutamate that had a chemical shift of 3.0 ppm away from bulk water and the signal intensity of GluCEST were concentration-dependent. Under physiological conditions, glutamate is the main contributor to the GluCEST signal. Compared with normal tissue, in both rats and patients with encephalitis, the encephalitis areas demonstrated a hyper-intense GluCEST signal, while the lacunar infarction had a decreased GluCEST signal intensity. After intravenous immunoglobulin therapy, patients with encephalitis lesions showed a decrease in GluCEST signal, and the results were significantly different from the pre-treatment signal (1.34 ± 0.31 vs 5.0 ± 0.27%, respectively; p = 0.000).

CONCLUSION

Glutamate plays a role in encephalitis, and the GluCEST imaging signal has potential as an in vivo imaging biomarker for the early diagnosis of encephalitis. GluCEST will provide new insight into encephalitis and help improve the differential diagnosis of brain disorders.

Approximated analytical characterization of the steady-state chemical exchange saturation transfer (CEST) signals

PURPOSE

CEST MRI can indirectly detect low-concentrated molecules via their proton exchange with the bulk water and is widely measured by a sensitivity index, the asymmetry of magnetization transfer ratio (MTRasym ). Because CEST applications are often limited by their low sensitivity or specificity, it is important to characterize MTRasym analytically to optimize its sensitivity or specifity.

METHODS

Approximated analytical solutions of the MTRasym spectrum were derived based on a 2-pool chemical exchange model for slow-to-intermediate exchanges. The optimal saturation pulse power for maximizing the MTRasym or tuning MTRasym to a specific exchange rate and the peak position and linewidth of a MTRasym spectrum were also derived. These approximated analytical solutions were compared with the solutions from the Bloch-McConnell equations using computer simulations.

RESULTS

The approximated analytical solutions of the MTRasym spectra, the optimizing parameters, and the peak and linewidth of MTRasym matched well with the solutions of Bloch-McConnell equations in the slow or slow-to-intermediate exchange regimes.

CONCLUSION

These approximate analytical solutions can provide insights to the understanding of CEST signal property and help the optimization of saturation parameters and the interpretation of CEST data.

Voxel-wise Optimization of Pseudo Voigt Profile (VOPVP) for Z-spectra fitting in chemical exchange saturation transfer (CEST) MRI

BACKGROUND

Chemical exchange saturation transfer (CEST) MRI is a promising approach for detecting biochemical alterations in cancers and neurological diseases, but the quantification can be challenging. Among numerous quantification methods, Lorentzian difference (LD) is relatively simple and widely used, which employs Lorentzian line-shape as a reference to describe the direct saturation (DS) of water and takes account of difference against experimental CEST spectra data. However, LD often overestimates CEST and nuclear overhauser enhancement (NOE) effects. Specifically, for fast-exchanging CEST species require higher saturation power (B1_sat) or in the presence of strong magnetization transfer (MT) contrast, Z-spectrum appears more like a Gaussian line-shape rather than a Lorentzian line-shape.

METHODS

To improve the conventional LD analysis, the present study developed and validated a novel fitting algorithm through a linear combination of Gaussian and Lorentzian function as the reference spectra, namely, Voxel-wise Optimization of Pseudo Voigt Profile (VOPVP). The experimental Z-spectra were pre-fitted with Gaussian and Lorentzian method independently, in order to determine Lorentzian proportionality coefficient (a). To further compensate for the line-shape changes under different B1_sat's, a B1-dependent adjustment was applied to the experimental Z-spectra (Z_exp) according to the prior knowledge learned from 5-pool Bloch equation-based simulations at a range of B1_sat's. Then, the obtained Z-spectra (Z_B1adj) was fitted by the previously defined VOPVP function. Considering the asymmetric component of MT, the positive- and negative-side of Z-spectra were fitted separately, while the middle part (-0.6 to 0.6 ppm, consisted primarily of DS) was fitted using Lorentzian function. Finally, the difference between Z_VOPVP and Z_exp was defined as the CEST and NOE contrast. To validate our VOPVP method, an extensive simulation of CEST Z-spectra was performed using 5-pool model and 6-pool model with greater MT component.

RESULTS

In comparison with LD approach, VOPVP exhibited lower sum of squares due to error (SSE) and higher goodness of fit (R-square) for the experimental Z-spectra at all B1_sat. Moreover, the results indicated that VOPVP fitting improved the overestimated contributions from amide proton transfer (APT) and NOE through LD at all B1_sat. Despite that the relationship for B1-dependent adjustment was pre-determined using a single 5-pool model, the VOPVP fittings obtained accurate quantification for multiple 6-pool models with a range of T1w's and T2w's. The robustness of VOPVP fitting was also proved by simulations using 3T parameters. Furthermore, we assessed VOPVP in vivo in a glioblastoma-bearing mouse. Compared to LD maps, VOPVP quantification maps displayed higher contrast-to-noise ratio between tumor and normal contralateral tissue for APT, glutamate and nuclear overhauser effect (NOE), when B1_sat >1 µT.

CONCLUSIONS

As an improvement of LD method, VOPVP fitting can serve as a simple, robust and more accurate approach for quantifying CEST and NOE contrast.

Quantification of hydroxyl exchange of D-Glucose at physiological conditions for optimization of glucoCEST MRI at 3, 7 and 9.4 Tesla

AIMS

To determine individual glucose hydroxyl exchange rates at physiological conditions and use this information for numerical optimization of glucoCEST/CESL preparation. To give guidelines for in vivo glucoCEST/CESL measurement parameters at clinical and ultra-high field strengths.

METHODS

Five glucose solution samples at different pH values were measured at 14.1 T at various B1 power levels. Multi-B1 -Z-spectra Bloch-McConnell fits at physiological pH were further improved by the fitting of Z-spectra of five pH values simultaneously. The obtained exchange rates were used in a six-pool Bloch-McConnell simulation including a tissue-like water pool and semi-solid MT pool with different CEST and CESL presaturation pulse trains. In vivo glucose injection experiments were performed in a tumor mouse model at 7 T.

RESULTS AND DISCUSSION

Glucose Z-spectra could be fitted with four exchanging pools at 0.66, 1.28, 2.08 and 2.88 ppm. Corresponding hydroxyl exchange rates could be determined at pH = 7.2, T = 37°C and 1X PBS. Simulation of saturation transfer for this glucose system in a gray matter-like and a tumor-like system revealed optimal pulses at different field strengths of 9.4, 7 and 3 T. Different existing sequences and approaches are simulated and discussed. The optima found could be experimentally verified in an animal model at 7 T.

CONCLUSION

For the determined fast exchange regime, presaturation pulses in the spin-lock regime (long recover time, short yet strong saturation) were found to be optimal. This study gives an estimation for optimization of the glucoCEST signal in vivo on the basis of glucose exchange rate at physiological conditions.

Ratiometric NOE(-1.6) contrast in brain tumors

Recently, a new nuclear Overhauser enhancement (NOE)-mediated saturation transfer effect at around -1.6 ppm from water, termed NOE(-1.6), was reported to show hypointense signals in brain tumors. Similar to chemical exchange saturation transfer or magnetization transfer (MT) effects, which depend on the solute pool concentration, the exchange/coupling rate, the solute transverse relaxation rate, etc., the NOE(-1.6) effect should also depend on these factors. Since the exchange rate is relevant to tissue pH, and the coupling rate and the solute transverse relaxation rate are relevant to the motional property of the coupled molecules, further studies to quantify the contribution from only the exchange/coupling rate and the solute transverse relaxation rate are always interesting. The purpose of this paper is to apply a ratiometric approach to the NOE(-1.6) effect to obtain a metric that is more specific to the NOE coupling rate and the solute transverse relaxation rate than the NOE(-1.6) signal amplitude. Simulations indicate that the ratiometric approach allows us to rule out nearly all of the non-specific factors including the solute pool concentration, solute and water longitudinal relaxation rates, direct water saturation, and semi-solid MT effects, and provides a more specific NOE coupling rate- and solute transverse relaxation rate-weighted signal. Animal studies show that the ratiometric NOE(-1.6) decreases dramatically in brain tumors, which suggests that the change in the NOE(-1.6) coupling rate and/or the solute transverse relaxation rate are major contributors to the previously observed hypointense NOE(-1.6) signal in tumors.

GlucoCEST imaging with on-resonance variable delay multiple pulse (onVDMP) MRI

PURPOSE

To examine the detection sensitivity for the rapidly exchanging hydroxyl protons of D-glucose using the recently developed on-resonance variable delay multi-pulse (onVDMP) chemical exchange saturation transfer (CEST) technique.

METHODS

The onVDMP method was applied for the detection of water signal changes upon venous D-glucose infusion in mice with 9L glioma xenografts. The effect size of onVDMP MRI during infusion was compared with that of conventional continuous wave (CW) CEST MRI.

RESULTS

Both methods highlighted the tumor and the blood vessels on D-glucose infusion. In interleaved studies, the mean signal changes detected by onVDMP were found to be 1.8 times higher than those by CW-CEST, attributed to its high labeling efficiency for fast exchanging protons and the labeling of the OH protons over a larger frequency range.

CONCLUSIONS

The onVDMP method is a more sensitive technique for the detection of exogenous CEST agents with fast-exchanging protons compared to CW-CEST MRI.

Spin-lock imaging of early tissue pH changes in ischemic rat brain

We have previously reported that the dispersion of spin-lattice relaxation rates in the rotating frame (R_1ρ ) of tissue water protons at high field can be dominated by chemical exchange contributions. Ischemia in brain causes changes in tissue pH, which in turn may affect proton exchange rates. Amide proton transfer (APT, a form of chemical exchange saturation transfer) has been shown to be sensitive to chemical exchange rates and able to detect pH changes non-invasively following ischemic stroke. However, the specificity of APT to pH changes is decreased because of the influence of several other factors that affect magnetization transfer. R_1ρ is less influenced by such confounding factors and thus may be more specific for detecting variations in pH. Here, we applied a spin-locking sequence to detect ischemic stroke in animal models. Although R_1ρ images acquired with a single spin-locking amplitude (ω₁ ) have previously been used to assess stroke, here we use ΔR_1ρ , which is the difference in R_1ρ values acquired with two different locking fields to emphasize selectively the contribution of chemical exchange effects. Numerical simulations with different exchange rates and measurements of tissue homogenates with different pH were performed to evaluate the specificity of ΔR_1ρ to detect tissue acidosis. Spin-lock and APT data were acquired on five rat brains after ischemic strokes induced via middle cerebral artery occlusions. Correlations between these data were analyzed at different time points after the onset of stroke. The results show that ΔR_1ρ (but not R_1ρ acquired with a single ω₁ ) was significantly correlated with APT metrics consistent with ΔR_1ρ varying with pH.

Separating fast and slow exchange transfer and magnetization transfer using off-resonance variable-delay multiple-pulse (VDMP) MRI

PURPOSE

To develop a method that can separate and quantify the fast (>1 kHz) and slow exchange transfer and magnetization transfer components in Z-spectra.

METHODS

Z-spectra were recorded as a function of mixing time using a train of selective pulses providing variable-delay multipulse build-up curves. Fast and slow transfer components in the Z-spectra were separated and quantified on a voxel-by-voxel basis by fitting the mixing time-dependent CEST signal using a 3-pool model.

RESULTS

Phantom studies of glutamate solution, bovine serum albumin solution, and hair conditioner showed the capability of the proposed method to separate fast and slow transfer components. In vivo mouse brain studies showed a strong contrast between white matter and gray matter in the slow-transferring map, corresponding to an asymmetric component of the conventional semisolid magnetization transfer contrast. In addition, a fast-transferring proton map was found that was homogeneous across the brain and attributed to the total contributions of the fast-exchanging protons from proteins, metabolites, and a symmetric magnetization transfer contrast component.

CONCLUSIONS

This new method provides a simple way to extract fast and slow transfer components from the Z-spectrum, leading to novel MRI contrasts, and providing insight into the different magnetization transfer contrast contributions.

Increased CEST specificity for amide and fast-exchanging amine protons using exchange-dependent relaxation rate

Chemical exchange saturation transfer (CEST) imaging of amides at 3.5 ppm and fast-exchanging amines at 3 ppm provides a unique means to enhance the sensitivity of detection of, for example, proteins/peptides and neurotransmitters, respectively, and hence can provide important information on molecular composition. However, despite the high sensitivity relative to conventional magnetic resonance spectroscopy (MRS), in practice, CEST often has relatively poor specificity. For example, CEST signals are typically influenced by several confounding effects, including direct water saturation (DS), semi-solid non-specific magnetization transfer (MT), the influence of water relaxation times (T_1w ) and nearby overlapping CEST signals. Although several editing techniques have been developed to increase the specificity by removing DS, semi-solid MT and T_1w influences, it is still challenging to remove overlapping CEST signals from different exchanging sites. For instance, the amide proton transfer (APT) signal could be contaminated by CEST effects from fast-exchanging amines at 3 ppm and intermediate-exchanging amines at 2 ppm. The current work applies an exchange-dependent relaxation rate (R_ex ) to address this problem. Simulations demonstrate that: (1) slowly exchanging amides and fast-exchanging amines have distinct dependences on irradiation powers; and (2) R_ex serves as a resonance frequency high-pass filter to selectively reduce CEST signals with resonance frequencies closer to water. These characteristics of R_ex provide a means to isolate the APT signal from amines. In addition, previous studies have shown that CEST signals from fast-exchanging amines have no distinct features around their resonance frequencies. However, R_ex gives Lorentzian lineshapes centered at their resonance frequencies for fast-exchanging amines and thus can significantly increase the specificity of CEST imaging for amides and fast-exchanging amines.

The z-spectrum from human blood at 7T

Chemical Exchange Saturation Transfer (CEST) has been used to assess healthy and pathological tissue in both animals and humans. However, the CEST signal from blood has not been fully assessed. This paper presents the CEST and nuclear Overhauser enhancement (NOE) signals detected in human blood measured via z-spectrum analysis. We assessed the effects of blood oxygenation levels, haematocrit, cell structure and pH upon the z-spectrum in ex vivo human blood for different saturation powers at 7T. The data were analysed using Lorentzian difference (LD) model fitting and AREX (to compensate for changes in T₁), which have been successfully used to study CEST effects in vivo. Full Bloch-McConnell fitting was also performed to provide an initial estimate of exchange rates and transverse relaxation rates of the various pools. CEST and NOE signals were observed at 3.5 ppm, −1.7 ppm and −3.5 ppm and were found to originate primarily from the red blood cells (RBCs), although the amide proton transfer (APT) CEST effect, and NOEs showed no dependence upon oxygenation levels. Upon lysing, the APT and NOE signals fell significantly. Different pH levels in blood resulted in changes in both the APT and NOE (at −3.5 ppm), which suggests that this NOE signal is in part an exchange relayed process. These results will be important for assessing in vivo z-spectra.

Chemical exchange rotation transfer imaging of intermediate-exchanging amines at 2 ppm

Chemical exchange saturation transfer (CEST) imaging of amine protons exchanging at intermediate rates and whose chemical shift is around 2 ppm may provide a means of mapping creatine. However, the quantification of this effect may be compromised by the influence of overlapping CEST signals from fast-exchanging amines and hydroxyls. We aimed to investigate the exchange rate filtering effect of a variation of CEST, named chemical exchange rotation transfer (CERT), as a means of isolating creatine contributions at around 2 ppm from other overlapping signals. Simulations were performed to study the filtering effects of CERT for the selection of transfer effects from protons of specific exchange rates. Control samples containing the main metabolites in brain, bovine serum albumin (BSA) and egg white albumen (EWA) at their physiological concentrations and pH were used to study the ability of CERT to isolate molecules with amines at 2 ppm that exchange at intermediate rates, and corresponding methods were used for in vivo rat brain imaging. Simulations showed that exchange rate filtering can be combined with conventional filtering based on chemical shift. Studies on samples showed that signal contributions from creatine can be separated from those of other metabolites using this combined filter, but contributions from protein amines may still be significant. This exchange filtering can also be used for in vivo imaging. CERT provides more specific quantification of amines at 2 ppm that exchange at intermediate rates compared with conventional CEST imaging.

Assignment of the molecular origins of CEST signals at 2 ppm in rat brain

PURPOSE

Chemical exchange saturation transfer effects at 2 ppm (CEST@2ppm) in brain have previously been interpreted as originating from creatine. However, protein guanidino amine protons may also contribute to CEST@2ppm. This study aims to investigate the molecular origins and specificity of CEST@2ppm in brain.

METHODS

Two experiments were performed: (i) samples containing egg white albumin and creatine were dialyzed using a semipermeable membrane to demonstrate that proteins and creatine can be separated by this method; and (ii) tissue homogenates of rat brain with and without dialysis to remove creatine were studied to measure the relative contributions of proteins and creatine to CEST@2ppm.

RESULTS

The experiments indicate that dialysis can successfully remove creatine from proteins. Measurements on tissue homogenates show that, with the removal of creatine via dialysis, CEST@2ppm decreases to approximately 34% of its value before dialysis, which indicates that proteins and creatine have comparable contribution to the CEST@2ppm in brain. However, considering the contribution from peptides and amino acids to CEST@2ppm, creatine may have much less contribution to CEST@2ppm.

CONCLUSIONS

The contribution of proteins, peptides, and amino acids to CEST@2ppm cannot be neglected. The CEST@2ppm measurements of creatine in rat brain should be interpreted with caution. Magn Reson Med 78:881-887, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

Improving the detection sensitivity of pH-weighted amide proton transfer MRI in acute stroke patients using extrapolated semisolid magnetization transfer reference signals

PURPOSE

To quantify amide protein transfer (APT) effects in acidic ischemic lesions and assess the spatial-temporal relationship among diffusion, perfusion, and pH deficits in acute stroke patients.

METHODS

Thirty acute stroke patients were scanned at 3 T. Quantitative APT (APT^# ) effects in acidic ischemic lesions were measured using an extrapolated semisolid magnetization transfer reference signal technique and compared with commonly used MTR_asym (3.5ppm) or APT-weighted parameters.

RESULTS

The APT^# images showed clear pH deficits in the ischemic lesion, whereas the MTR_asym (3.5ppm) signals were slightly hypointense. The APT^# contrast between acidic ischemic lesions and normal tissue in acute stroke patients was more than three times larger than MTR_asym (3.5ppm) contrast (-1.45 ± 0.40% for APT^# versus -0.39 ± 0.52% for MTR_asym (3.5ppm), P < 4.6 × 10^-4 ). Hypoperfused and acidic areas without an apparent diffusion coefficient abnormality were observed and assigned to an ischemic acidosis penumbra. Hypoperfused areas at normal pH were also observed and assigned to benign oligemia. Hyperintense APT signals were observed in a hemorrhage area in one case.

CONCLUSIONS

The quantitative APT study using the extrapolated semisolid magnetization transfer reference signal approach enhances APT MRI sensitivity to pH compared with conventional APT-weighted MRI, allowing more reliable delineation of an ischemic acidosis in the penumbra. Magn Reson Med 78:871-880, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

Magnetization Transfer Contrast and Chemical Exchange Saturation Transfer MRI. Features and analysis of the field-dependent saturation spectrum

Magnetization Transfer Contrast (MTC) and Chemical Exchange Saturation Transfer (CEST) experiments measure the transfer of magnetization from molecular protons to the solvent water protons, an effect that becomes apparent as an MRI signal loss ("saturation"). This allows molecular information to be accessed with the enhanced sensitivity of MRI. In analogy to Magnetic Resonance Spectroscopy (MRS), these saturation data are presented as a function of the chemical shift of participating proton groups, e.g. OH, NH, NH₂, which is called a Z-spectrum. In tissue, these Z-spectra contain the convolution of multiple saturation transfer effects, including nuclear Overhauser enhancements (NOEs) and chemical exchange contributions from protons in semi-solid and mobile macromolecules or tissue metabolites. As a consequence, their appearance depends on the magnetic field strength (B₀) and pulse sequence parameters such as B₁ strength, pulse shape and length, and interpulse delay, which presents a major problem for quantification and reproducibility of MTC and CEST effects. The use of higher B₀ can bring several advantages. In addition to higher detection sensitivity (signal-to-noise ratio, SNR), both MTC and CEST studies benefit from longer water T₁ allowing the saturation transferred to water to be retained longer. While MTC studies are non-specific at any field strength, CEST specificity is expected to increase at higher field because of a larger chemical shift dispersion of the resonances of interest (similar to MRS). In addition, shifting to a slower exchange regime at higher B₀ facilitates improved detection of the guanidinium protons of creatine and the inherently broad resonances of the amine protons in glutamate and the hydroxyl protons in myoinositol, glycogen, and glucosaminoglycans. Finally, due to the higher mobility of the contributing protons in CEST versus MTC, many new pulse sequences can be designed to more specifically edit for CEST signals and to remove MTC contributions.