Exploiting conformational dynamics to modulate the function of designed proteins.

With the recent success in calculating protein structures from amino acid sequences using artificial intelligence-based algorithms, an important next step is to decipher how dynamics is encoded by the primary protein sequence so as to better predict function. Such dynamics information is critical for protein design, where strategies could then focus not only on sequences that fold into particular structures that perform a given task, but would also include low-lying excited protein states that could influence the function of the designed protein. Herein, we illustrate the importance of dynamics in modulating the function of C34, a designed α/ß protein that captures ß-strands of target ligands and is a member of a family of proteins designed to sequester ß-strands and ß hairpins of aggregation-prone molecules that lead to a variety of pathologies. Using a strategy to "see" regions of apo C34 that are invisible to NMR spectroscopy as a result of pervasive conformational exchange, as well as a mutagenesis approach whereby C34 molecules are stabilized into a single conformer, we determine the structures of the predominant conformations that are sampled by C34 and show that these attenuate the affinity for cognate peptide. Subsequently, the observed motion is exploited to develop an allosterically regulated peptide binder whose binding affinity can be controlled through the addition of a second molecule. Our study emphasizes the unique role that NMR can play in directing the design process and in the construction of new molecules with more complex functionality.

Transient excited states of the metamorphic protein Mad2 and their implications for function.

The spindle checkpoint complex is a key surveillance mechanism in cell division that prevents premature separation of sister chromatids. Mad2 is an integral component of this spindle checkpoint complex that recognizes cognate substrates such as Mad1 and Cdc20 in its closed (C-Mad2) conformation by fastening a "seatbelt" around short peptide regions that bind to the substrate recognition site. Mad2 is also a metamorphic protein that adopts not only the fold found in C-Mad2, but also a structurally distinct open conformation (O-Mad2) which is incapable of binding substrates. Here, we show using chemical exchange saturation transfer (CEST) and relaxation dispersion (CPMG) NMR experiments that Mad2 transiently populates three other higher free energy states with millisecond lifetimes, two in equilibrium with C-Mad2 (E1 and E2) and one with O-Mad2 (E3). E1 is a mimic of substrate-bound C-Mad2 in which the N-terminus of one C-Mad2 molecule inserts into the seatbelt region of a second molecule of C-Mad2, providing a potential pathway for autoinhibition of C-Mad2. E2 is the "unbuckled" conformation of C-Mad2 that facilitates the triage of molecules along competing fold-switching and substrate binding pathways. The E3 conformation that coexists with O-Mad2 shows fluctuations at a hydrophobic lock that is required for stabilizing the O-Mad2 fold and we hypothesize that E3 represents an early intermediate on-pathway towards conversion to C-Mad2. Collectively, the NMR data highlight the rugged free energy landscape of Mad2 with multiple low-lying intermediates that interlink substrate-binding and fold-switching, and also emphasize the role of molecular dynamics in its function.

Effect of reducing isoflurane level on glucosamine uptake in the mouse brain during magnetic resonance imaging studies.

Anesthesia is often required during magnetic resonance imaging (MRI) examinations in animal studies. Anesthetic drugs differ in their capacity to interfere with homeostatic mechanisms responsible for glucose metabolism in the brain, which may create a constraint in the study design. Recent studies suggest that the chemical exchange saturation transfer (CEST) MRI scanning technique can detect localized metabolic changes in rodent brains induced by the uptake of glucose or its analogs; however, most of these studies do not account for the impact of anesthesia type on the brain metabolism. Herein, we aimed to evaluate the effect of reduced isoflurane levels on the preclinical imaging of glucosamine (GlcN) uptake in healthy mouse brains to establish optimal conditions for future brain imaging studies using the CEST MRI technique. The commonly used anesthesia protocol for longitudinal MRI examinations using 1.5% isoflurane level was compared to that using a mixture of low isoflurane (0.8%) level combined with midazolam (2 mg/kg, SC). Magnetization transfer ratio asymmetry (MTRasym) and area under the curve (AUC) analyses were used to characterize GlcN signals in the brain. The results indicated that mice injected with GlcN and anesthetized with 1.5% isoflurane exhibited low and insignificant changes in the MTRasym and AUC signals in the frontal cortex, whereas mice administered with 0.8% isoflurane combined with midazolam demonstrated a significant increase in these signals in the frontal cortex. This study highlights the diverse GlcN metabolic changes observed in mouse brains under variable levels of isoflurane anesthesia using the CEST MRI method. The results suggest that it is feasible to maintain anesthesia with low-dose isoflurane by integrating midazolam, which may enable the investigation of GlcN uptake in the brain. Thus, reducing isoflurane levels may support studies into mouse brain metabolism using the CEST MRI method and should be considered in future studies.

Quantitative analysis of the slow exchange process by 19F NMR in the presence of scalar and dipolar couplings: applications to the ribose 2'-19F probe in nucleic acids.

Solution NMR spectroscopy is a particularly powerful technique for characterizing the functional dynamics of biomolecules, which is typically achieved through the quantitative characterization of chemical exchange processes via the measurement of spin relaxation rates. In addition to the conventional nuclei such as 15N and 13C, which are abundant in biomolecules, fluorine-19 (19F) has recently garnered attention and is being widely used as a site-specific spin probe. While 19F offers the advantages of high sensitivity and low background, it can be susceptible to artifacts in quantitative relaxation analyses due to a multitude of dipolar and scalar coupling interactions with nearby 1H spins. In this study, we focused on the ribose 2'-19F spin probe in nucleic acids and investigated the effects of 1H-19F spin interactions on the quantitative characterization of slow exchange processes on the millisecond time scale. We demonstrated that the 1H-19F dipolar coupling can significantly affect the interpretation of 19F chemical exchange saturation transfer (CEST) experiments when 1H decoupling is applied, while the 1H-19F interactions have a lesser impact on Carr-Purcell-Meiboom-Gill relaxation dispersion applications. We also proposed a modified CEST scheme to alleviate these artifacts along with experimental verifications on self-complementary RNA systems. The theoretical framework presented in this study can be widely applied to various 19F spin systems where 1H-19F interactions are operative, further expanding the utility of 19F relaxation-based NMR experiments.

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.

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.

Improving standardization and accuracy of in vivo omega plot exchange parameter determination using rotating-frame model-based fitting of quasi-steady-state Z-spectra.

PURPOSE: Although Ω-plot-driven quantification of in vivo amide exchange properties has been demonstrated, differences in scan parameters may complicate the fidelity of determination. This work systematically evaluated the use of quasi-steady-state (QUASS) Z-spectra reconstruction to standardize in vivo amide exchange quantification across acquisition conditions and further determined it in vivo. METHODS: Simulation and in vivo rodent brain chemical exchange saturation transfer (CEST) data at 4.7 T were fit with and without QUASS reconstruction using both multi-Lorentzian and model-based fitting approaches. pH modulation was accomplished both in simulation and in vivo by inducing global ischemia via cardiac arrest. Amide parameters were determined via Ω-plots and compared across methods. RESULTS: Simulation showed that Ω-plots using multi-Lorentzian fitting could underestimate the exchange rate, with error increasing as conditions diverged from the steady state. In comparison, model-based fitting using QUASS estimated the same exchange rate within 2%. These results aligned with in vivo findings where multi-Lorentzian fitting of native Z-spectra resulted in an exchange rate of 64 ± 13 s-1 (38 ± 16 s-1 after cardiac arrest), whereas model-based fitting of QUASS Z-spectra yielded an exchange rate of 126 ± 25 s-1 (49 ± 13 s-1). CONCLUSION: The model-based fitting of QUASS CEST Z-spectra enables consistent and accurate quantification of exchange parameters through Ω-plot construction by reducing error due to signal overlap and nonequilibrium CEST effects.

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.

Simultaneous creatine and phosphocreatine mapping of skeletal muscle by CEST MRI at 3T.

PURPOSE: To confirm that CrCEST in muscle exhibits a slow-exchanging process, and to obtain high-resolution amide, creatine (Cr), and phosphocreatine (PCr) maps of skeletal muscle using a POlynomial and Lorentzian Line-shape Fitting (PLOF) CEST at 3T. METHODS: We used dynamic changes in PCr/CrCEST of mouse hindlimb before and after euthanasia to assign the Cr and PCr CEST peaks in the Z-spectrum at 3T and to obtain the optimum saturation parameters. Segmented 3D EPI was employed to obtain multi-slice amide, PCr, and Cr CEST maps of human skeletal muscle. Subsequently, the PCrCEST maps were calibrated using the PCr concentrations determined by 31 P MRS. RESULTS: A comparison of the Z-spectra in mouse hindlimb before and after euthanasia indicated that CrCEST is a slow-exchanging process in muscle (<150.7 s-1 ). This allowed us to simultaneously extract PCr/CrCEST signals at 3T using the PLOF method. We determined optimal B1 values ranging from 0.3 to 0.6 µT for CrCEST in muscle and 0.3-1.2 µT for PCrCEST. For the study on human calf muscle, we determined an optimum saturation time of 2 s for both PCr/CrCEST (B1 = 0.6 µT). The PCr/CrCEST using 3D EPI were found to be comparable to those obtained using turbo spin echo (TSE). (3D EPI/TSE PCr: (2.6 ± 0.3) %/(2.3 ± 0.1) %; Cr: (1.3 ± 0.1) %/(1.4 ± 0.07) %). CONCLUSIONS: Our study showed that in vivo CrCEST is a slow-exchanging process. Hence, amide, Cr, and PCr CEST in the skeletal muscle can be mapped simultaneously at 3T by PLOF CEST.

Accelerated CEST imaging through deep learning quantification from reduced frequency offsets.

PURPOSE: To shorten CEST acquisition time by leveraging Z-spectrum undersampling combined with deep learning for CEST map construction from undersampled Z-spectra. METHODS: Fisher information gain analysis identified optimal frequency offsets (termed "Fisher offsets") for the multi-pool fitting model, maximizing information gain for the amplitude and the FWHM parameters. These offsets guided initial subsampling levels. A U-NET, trained on undersampled brain CEST images from 18 volunteers, produced CEST maps at 3 T with varied undersampling levels. Feasibility was first tested using retrospective undersampling at three levels, followed by prospective in vivo undersampling (15 of 53 offsets), reducing scan time significantly. Additionally, glioblastoma grade IV pathology was simulated to evaluate network performance in patient-like cases. RESULTS: Traditional multi-pool models failed to quantify CEST maps from undersampled images (structural similarity index [SSIM] <0.2, peak SNR <20, Pearson r <0.1). Conversely, U-NET fitting successfully addressed undersampled data challenges. The study suggests CEST scan time reduction is feasible by undersampling 15, 25, or 35 of 53 Z-spectrum offsets. Prospective undersampling cut scan time by 3.5 times, with a maximum mean squared error of 4.4e-4, r = 0.82, and SSIM = 0.84, compared to the ground truth. The network also reliably predicted CEST values for simulated glioblastoma pathology. CONCLUSION: The U-NET architecture effectively quantifies CEST maps from undersampled Z-spectra at various undersampling levels.

Accelerating multipool CEST MRI of Parkinson's disease using deep learning-based Z-spectral compressed sensing.

PURPOSE: To develop a deep learning-based approach to reduce the scan time of multipool CEST MRI for Parkinson's disease (PD) while maintaining sufficient prediction accuracy. METHOD: A deep learning approach based on a modified one-dimensional U-Net, termed Z-spectral compressed sensing (CS), was proposed to recover dense Z-spectra from sparse ones. The neural network was trained using simulated Z-spectra generated by the Bloch equation with various parameter settings. Its feasibility and effectiveness were validated through numerical simulations and in vivo rat brain experiments, compared with commonly used linear, pchip, and Lorentzian interpolation methods. The proposed method was applied to detect metabolism-related changes in the 6-hydroxydopamine PD model with multipool CEST MRI, including APT, CEST@2 ppm, nuclear Overhauser enhancement, direct saturation, and magnetization transfer, and the prediction performance was evaluated by area under the curve. RESULTS: The numerical simulations and in vivo rat-brain experiments demonstrated that the proposed method could yield superior fidelity in retrieving dense Z-spectra compared with existing methods. Significant differences were observed in APT, CEST@2 ppm, nuclear Overhauser enhancement, and direct saturation between the striatum regions of wild-type and PD models, whereas magnetization transfer exhibited no significant difference. Receiver operating characteristic analysis demonstrated that multipool CEST achieved better predictive performance compared with individual pools. Combined with Z-spectral CS, the scan time of multipool CEST MRI can be reduced to 33% without distinctly compromising prediction accuracy. CONCLUSION: The integration of Z-spectral CS with multipool CEST MRI can enhance the prediction accuracy of PD and maintain the scan time within a reasonable range.

Highly-accelerated CEST MRI using frequency-offset-dependent k-space sampling and deep-learning reconstruction.

PURPOSE: To develop a highly accelerated CEST Z-spectral acquisition method using a specifically-designed k-space sampling pattern and corresponding deep-learning-based reconstruction. METHODS: For k-space down-sampling, a customized pattern was proposed for CEST, with the randomized probability following a frequency-offset-dependent (FOD) function in the direction of saturation offset. For reconstruction, the convolution network (CNN) was enhanced with a Partially Separable (PS) function to optimize the spatial domain and frequency domain separately. Retrospective experiments on a self-acquired human brain dataset (13 healthy adults and 15 brain tumor patients) were conducted using k-space resampling. The prospective performance was also assessed on six healthy subjects. RESULTS: In retrospective experiments, the combination of FOD sampling and PS network (FOD + PSN) showed the best quantitative metrics for reconstruction, outperforming three other combinations of conventional sampling with varying density and a regular CNN (nMSE and SSIM, p < 0.001 for healthy subjects). Across all acceleration factors from 4 to 14, the FOD + PSN approach consistently outperformed the comparative methods in four contrast maps including MTRasym, MTRrex, as well as the Lorentzian Difference maps of amide and nuclear Overhauser effect (NOE). In the subspace replacement experiment, the error distribution demonstrated the denoising benefits achieved in the spatial subspace. Finally, our prospective results obtained from healthy adults and brain tumor patients (14×) exhibited the initial feasibility of our method, albeit with less accurate reconstruction than retrospective ones. CONCLUSION: The combination of FOD sampling and PSN reconstruction enabled highly accelerated CEST MRI acquisition, which may facilitate CEST metabolic MRI for brain tumor patients.

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.

Multiparametric exchange protons using Z-spectrum analysis proton (ZAP) and CEST on phantoms and human abdomen.

PURPOSE: This study aims to investigate a multiparametric exchange proton approach using CEST and Z-spectrum analysis protons (ZAP) in human abdominal organs, focusing on tissue differentiation for a potential early biomarker of abnormality. Prior to human studies, CEST and ZAP effects were studied in phantoms containing exchange protons. METHODS: Phantoms composed of iopamidol and iohexol solutions with varying pH levels, along with 12 human subjects, were scanned on a clinical 3T MR scanner. Subsequent ZAP analyses employed a two-Lorentzian pool model to provide free and restricted apparent T 2 f , r ex $$ {\mathrm{T}}_{2\ \mathrm{f},\mathrm{r}}^{\mathrm{ex}} $$ , and their fractions for data acquired across a wide range of offset frequencies (±100 kHz or ± 800 ppm), while a narrower range (±7 ppm or ± 900 Hz) was used for CEST analysis to estimate magnetization transfer ratio asymmetry (MTRAsym) for exchange protons like hydroxyl (-OH), amine (-NH2), and amide (-NH), resonating ˜1, 2, and 3.5 ppm, respectively. Differences in ZAP metrics across various organs were statistically analyzed using one-way analysis of variance (ANOVA). RESULTS: The phantom study differentiated contrast agents based on resonance peaks detected from CEST analysis, while ZAP metrics showed sensitivity to pH variations. In human, ZAP metrics revealed significant differences in abdominal organs, with a subgroup study indicating changes in ZAP metrics due to the presence of gallstones. CONCLUSION: CEST and ZAP techniques demonstrated promise in specific CEST protons and wide range ZAP protons and identifying tissue-specific characteristics. The preliminary findings underscore the necessity for more extensive study involving a broader subject pool to potentially establish biomarkers for diseased states.

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.

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.

Quasi-steady-state (QUASS) reconstruction enhances T1 normalization in apparent exchange-dependent relaxation (AREX) analysis: A reevaluation of T1 correction in quantitative CEST MRI of rodent brain tumor models.

PURPOSE: The apparent exchange-dependent relaxation (AREX) analysis has been proposed as an effective means to correct T1 contribution in CEST quantification. However, it has been recognized that AREX T1 correction is not straightforward if CEST scans are not performed under the equilibrium condition. Our study aimed to test if quasi-steady-state (QUASS) reconstruction could boost the accuracy of the AREX metric under common non-equilibrium scan conditions. THEORY AND METHODS: Numerical simulation and in vivo scans were performed to assess the AREX metric accuracy. The CEST signal was simulated under different relaxation delays, RF saturation amplitudes, and durations. The AREX was evaluated as a function of the bulk water T1 and labile proton concentration using the multiple linear regression model. AREX MRI was also assessed in brain tumor rodent models, with both apparent CEST scans and QUASS reconstruction. RESULTS: Simulation showed that the AREX calculation from apparent CEST scans, under non-equilibrium conditions, had significant dependence on labile proton fraction ratio, RF saturation time, and T1. In comparison, QUASS-boosted AREX depended on the labile proton fraction ratio without significant dependence on T1 and RF saturation time. Whereas the apparent (2.7 ± 0.8%) and QUASS MTR asymmetry (2.8 ± 0.8%) contrast between normal and tumor regions of interest (ROIs) were significant, the difference was small. In comparison, AREX contrast between normal and tumor ROIs calculated from the apparent CEST scan and QUASS reconstruction was 3.8 ± 1.1%/s and 4.4 ± 1.2%/s, respectively, statistically different from each other. CONCLUSIONS: AREX analysis benefits from the QUASS-reconstructed equilibrium CEST effect for improved T1 correction and quantitative CEST analysis.

Mitochondrial oxidative phosphorylation capacity in skeletal muscle measured by ultrafast Z-spectroscopy (UFZ) MRI at 3T.

PURPOSE: To investigate the feasibility of rapid CEST MRI acquisition for evaluating oxidative phosphorylation (OXPHOS) in human skeletal muscle at 3T, utilizing ultrafast Z-spectroscopy (UFZ) combined with MRI and the Polynomial and Lorentzian line-shape Fitting (PLOF) technique. METHODS: UFZ MRI on muscle was evaluated with turbo spin echo (TSE) and 3D EPI readouts. Five healthy subjects performed in-magnet plantar flexion exercise (PFE) and subsequent changes of amide, PCr, and partial PCr mixed Cr (Cr+) CEST dynamic signals post-exercise were enabled by PLOF fitting. PCr/Cr CEST signal was further refined through pH correction by using the ratios between PCr/Cr and amide signals, named PCAR/CAR, respectively. RESULTS: UFZ MRI with TSE readout significantly reduces acquisition time, achieving a temporal resolution of <50 s for collecting high-resolution Z-spectra. Following PFE, the recovery/decay times (τ) for both PCr and Cr in the gastrocnemius muscle of the calf were notably longer when determined using PCr/Cr CEST compared to those after pH correction with amideCEST, namely τ Cr + $$ {\tau}_{Cr^{+}} $$ = 87.1 ± 15.8 s and τ PCr $$ {\tau}_{PCr} $$ = 98.1 ± 20.4 s versus τ CAR $$ {\tau}_{CAR} $$ = 32.9 ± 19.7 s and τ PCAR $$ {\tau}_{PCAR} $$ = 43.0 ± 13.0 s, respectively. τ PCr $$ {\tau}_{PCr} $$ obtained via 31P MRS ( τ PCr $$ {\tau}_{PCr} $$ = 50.3 ± 6.2 s) closely resemble those obtained from pH-corrected PCr/Cr CEST signals. CONCLUSION: The outcomes suggest potential of UFZ MRI as a robust tool for non-invasive assessment of mitochondrial function in skeletal muscles. pH correction is critical for the reliable OXPHOS measurement by CEST.

Whole-cerebrum guanidino and amide CEST mapping at 3 T by a 3D stack-of-spirals gradient echo acquisition.

PURPOSE: To develop a 3D, high-sensitivity CEST mapping technique based on the 3D stack-of-spirals (SOS) gradient echo readout, the proposed approach was compared with conventional acquisition techniques and evaluated for its efficacy in concurrently mapping of guanidino (Guan) and amide CEST in human brain at 3 T, leveraging the polynomial Lorentzian line-shape fitting (PLOF) method. METHODS: Saturation time and recovery delay were optimized to achieve maximum CEST time efficiency. The 3DSOS method was compared with segmented 3D EPI (3DEPI), turbo spin echo, and gradient- and spin-echo techniques. Image quality, temporal SNR (tSNR), and test-retest reliability were assessed. Maps of Guan and amide CEST derived from 3DSOS were demonstrated on a low-grade glioma patient. RESULTS: The optimized recovery delay/saturation time was determined to be 1.4/2 s for Guan and amide CEST. In addition to nearly doubling the slice number, the gradient echo techniques also outperformed spin echo sequences in tSNR: 3DEPI (193.8 ± 6.6), 3DSOS (173.9 ± 5.6), and GRASE (141.0 ± 2.7). 3DSOS, compared with 3DEPI, demonstrated comparable GuanCEST signal in gray matter (GM) (3DSOS: [2.14%-2.59%] vs. 3DEPI: [2.15%-2.61%]), and white matter (WM) (3DSOS: [1.49%-2.11%] vs. 3DEPI: [1.64%-2.09%]). 3DSOS also achieves significantly higher amideCEST in both GM (3DSOS: [2.29%-3.00%] vs. 3DEPI: [2.06%-2.92%]) and WM (3DSOS: [2.23%-2.66%] vs. 3DEPI: [1.95%-2.57%]). 3DSOS outperforms 3DEPI in terms of scan-rescan reliability (correlation coefficient: 3DSOS: 0.58-0.96 vs. 3DEPI: -0.02 to 0.75) and robustness to motion as well. CONCLUSION: The 3DSOS CEST technique shows promise for whole-cerebrum CEST imaging, offering uniform contrast and robustness against motion artifacts.

Creatine mapping of the brain at 3T by CEST MRI.

PURPOSE: To assess the feasibility of CEST-based creatine (Cr) mapping in brain at 3T using the guanidino (Guan) proton resonance. METHODS: Wild type and knockout mice with guanidinoacetate N-methyltransferase deficiency and low Cr and phosphocreatine (PCr) concentrations in the brain were used to assign the Cr and protein-based arginine contributions to the GuanCEST signal at 2.0 ppm. To quantify the Cr proton exchange rate, two-step Bloch-McConnell fitting was used to fit the extracted CrCEST line-shape and multi-B1 Z-spectral data. The pH response of GuanCEST was simulated to demonstrate its potential for pH mapping. RESULTS: Brain Z-spectra of wild type and guanidinoacetate N-methyltransferase deficiency mice show a clear Guan proton peak at 2.0 ppm at 3T. The CrCEST signal contributes ∼23% to the GuanCEST signal at B1 = 0.8 µT, where a maximum CrCEST effect of 0.007 was detected. An exchange rate range of 200-300 s-1 was estimated for the Cr Guan protons. As revealed by the simulation, an elevated GuanCEST in the brain is observed when B1 is less than 0.4 µT at 3T, when intracellular pH reduces by 0.2. Conversely, the GuanCEST decreases when B1 is greater than 0.4 µT with the same pH drop. CONCLUSIONS: CrCEST mapping is possible at 3T, which has potential for detecting intracellular pH and Cr concentration in brain.