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

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, namelyτ Cr + $$ {\tau}_{Cr^{+}} $$ = 87.1 ± 15.8 s andτ PCr $$ {\tau}_{PCr} $$ = 98.1 ± 20.4 s versusτ CAR $$ {\tau}_{CAR} $$ = 32.9 ± 19.7 s andτ 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.

Elucidating metabolite and pH variations in stroke through guanidino, amine and amide CEST MRI: A comparative multi-field study at 9.4T and 3T

This study aims to investigate the variations in guanidino (Guan), amine and amide chemical exchange saturation transfer (CEST) contrasts in ischemic stroke using permanent middle cerebral artery occlusion (pMCAO) and transient MCAO (tMCAO) models at high (9.4T) and clinical (3T) MRI fields. CEST contrasts were extracted using the Polynomial and Lorentzian Line-shape Fitting (PLOF) method. Both pMCAO and tMCAO models were utilized to examine the B1-dependence patterns and pH sensitivity of the different CEST contrasts in ischemic lesions compared to contralateral region. At 9.4T, GuanCEST showed the highest signal in the contralateral hemisphere for both stroke models, followed by lower signals from amideCEST and amineCEST, with maximum signals at B1=1.2 μT for all CEST contrasts. In both stroke models, GuanCEST exhibited a significant decrease of 1.15-1.5 % in stroke lesions compared to the contralateral hemisphere (ΔGuanCEST) at an optimal B1 range of 1.2-1.6 μT at 9.4T. This represents more than double the pH sensitivity compared to amideCEST, which showed a reduction of 0.5-0.62 % under the same B1 conditions. In the tMCAO model, amineCEST increased by 3.85 % in the stroke lesion compared to the contralateral hemisphere at an optima B1 range of 1.6-2.5 μT. In contrast, for the pMCAO model, amineCEST increased by 0.87-1.0 % in the stroke lesion. At lower B1 values (<0.8 μT at 9.4T and <0.4 μT at 3T), the GuanCEST changes in the stroke lesion were dominated by creatine concentration changes, which increased in the pMCAO and remained stable in the tMCAO. While GuanCEST and amineCEST are highly sensitive for delineating stroke lesions, amideCEST is more suitable for precise pH mapping as it is not influenced by metabolite changes within the stroke lesion. Additionally, at low B1 values, amideCEST and GuanCEST can be used to map protein and creatine concentrations separately, since they are independent of pH changes at these lower B1 values. Lastly, amineCEST serves as a highly sensitive MRI contrast for detecting reperfusion damage at high MRI fields.

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.

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.

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.

Ungated, plug-and-play preclinical cardiac CEST-MRI using radial FLASH with segmented saturation

PURPOSE

Electrocardiography (ECG) and respiratory-gated preclinical cardiac CEST-MRI acquisitions are difficult because of variable saturation recovery with T1, RF interference in the ECG signal, and offset-to-offset variation in Z-magnetization and cardiac phase introduced by changes in cardiac frequency and trigger delays.

METHODS

The proposed method consists of segmented saturation modules with radial FLASH readouts and golden angle progression. The segmented saturation blocks drive the system to steady-state, and because center k-space is sampled repeatedly, steady-state saturation dominates contrast during gridding and reconstruction. Ten complete Z-spectra were acquired in healthy mice using both ECG and respiratory-gated and ungated methods. Z-spectra were also acquired at multiple saturation B1 values to optimize for amide and Cr contrasts.

RESULTS

There was no significant difference between CEST contrasts (amide, Cr, magnetization transfer) calculated from images acquired using ECG and respiratory-gated and ungated methods (p = 0.27, 0.11, 0.47). A saturation power of 1.8μT provides optimal contrast amplitudes for both amide and total Cr contrast without significantly complicating CEST contrast quantification because of water direct saturation, magnetization transfer, and RF spillover between amide and Cr pools. Further, variability in CEST contrast measurements was significantly reduced using the ungated radial FLASH acquisition (p = 0.002, 0.006 for amide and Cr, respectively).

CONCLUSION

This method enables CEST mapping in the murine myocardium without the need for cardiac or respiratory gating. Quantitative CEST contrasts are consistent with those obtained using gated sequences, and per-contrast variance is significantly reduced. This approach makes preclinical cardiac CEST-MRI easily accessible, even for investigators without prior experience in cardiac imaging.

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.

Quantitative separation of CEST effect by Rex-line-fit analysis of Z-spectra

The process of chemical exchange saturation transfer (CEST) is quantified by evaluating a Z-spectra, where CEST signal quantification and Z-spectra fitting have been widely used to distinguish the contributions from multiple origins. Based on the exchange-dependent relaxation rate in the rotating frame (Rex), this paper introduces an additional pathway to quantitative separation of CEST effect. The proposed Rex-line-fit method is solved by a multi-pool model and presents the advantage of only being dependent of the specific parameters (solute concentration, solute-water exchange rate, solute transverse relaxation, and irradiation power). Herein we show that both solute-water exchange rate and solute concentration monotonously vary with Rex for Amide, Guanidino, NOE and MT, which has the potential to assist in solving quantitative separation of CEST effect. Furthermore, we achieve Rex imaging of Amide, Guanidino, NOE and MT, which may provide direct insight into the dependency of measurable CEST effects on underlying parameters such as the exchange rate and solute concentration, as well as the solute transverse relaxation.

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.

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.

Deep learning for dense Z-spectra reconstruction from CEST images at sparse frequency offsets

A direct way to reduce scan time for chemical exchange saturation transfer (CEST)-magnetic resonance imaging (MRI) is to reduce the number of CEST images acquired in experiments. In some scenarios, a sufficient number of CEST images acquired in experiments was needed to estimate parameters for quantitative analysis, and this prolonged the scan time. For that, we aim to develop a general deep-learning framework to reconstruct dense CEST Z-spectra from experimentally acquired images at sparse frequency offsets so as to reduce the number of experimentally acquired CEST images and achieve scan time reduction. The main innovation works are outlined as follows: (1) a general sequence-to-sequence (seq2seq) framework is proposed to reconstruct dense CEST Z-spectra from experimentally acquired images at sparse frequency offsets; (2) we create a training set from wide-ranging simulated Z-spectra instead of experimentally acquired CEST data, overcoming the limitation of the time and labor consumption in manual annotation; (3) a new seq2seq network that is capable of utilizing information from both short-range and long-range is developed to improve reconstruction ability. One of our intentions is to establish a simple and efficient framework, i.e., traditional seq2seq can solve the reconstruction task and obtain satisfactory results. In addition, we propose a new seq2seq network that includes the short- and long-range ability to boost dense CEST Z-spectra reconstruction. The experimental results demonstrate that the considered seq2seq models can accurately reconstruct dense CEST images from experimentally acquired images at 11 frequency offsets so as to reduce the scan time by at least 2/3, and our new seq2seq network contributes to competitive advantage.

Boosting quantification accuracy of chemical exchange saturation transfer MRI with a spatial-spectral redundancy-based denoising method

Chemical exchange saturation transfer (CEST) is a versatile technique that enables noninvasive detections of endogenous metabolites present in low concentrations in living tissue. However, CEST imaging suffers from an inherently low signal-to-noise ratio (SNR) due to the decreased water signal caused by the transfer of saturated spins. This limitation challenges the accuracy and reliability of quantification in CEST imaging. In this study, a novel spatial-spectral denoising method, called BOOST (suBspace denoising with nOnlocal lOw-rank constraint and Spectral local-smooThness regularization), was proposed to enhance the SNR of CEST images and boost quantification accuracy. More precisely, our method initially decomposes the noisy CEST images into a low-dimensional subspace by leveraging the global spectral low-rank prior. Subsequently, a spatial nonlocal self-similarity prior is applied to the subspace-based images. Simultaneously, the spectral local-smoothness property of Z-spectra is incorporated by imposing a weighted spectral total variation constraint. The efficiency and robustness of BOOST were validated in various scenarios, including numerical simulations and preclinical and clinical conditions, spanning magnetic field strengths from 3.0 to 11.7 T. The results demonstrated that BOOST outperforms state-of-the-art algorithms in terms of noise elimination. As a cost-effective and widely available post-processing method, BOOST can be easily integrated into existing CEST protocols, consequently promoting accuracy and reliability in detecting subtle CEST effects.

Comparison of model-free Lorentzian and spinlock model-based fittings in quantitative CEST imaging of acute stroke

PURPOSE

CEST MRI detects complex tissue changes following acute stroke. Our study aimed to test if spinlock model-based fitting of the quasi-steady-state (QUASS)-reconstructed equilibrium CEST MRI improves the determination of multi-pool signal changes over the commonly-used model-free Lorentzian fitting in acute stroke.

THEORY AND METHODS

Multiple three-pool CEST Z-spectra were simulated using Bloch-McConnell equations for a range of T1 , relaxation delay, and saturation times. The multi-pool CEST signals were solved from the simulated Z-spectra to test the accuracy of routine Lorentzian (model-free) and spinlock (model-based) fittings without and with QUASS reconstruction. In addition, multiparametric MRI scans were obtained in rat models of acute stroke, including relaxation, diffusion, and CEST Z-spectrum. Finally, we compared model-free and model-based per-pixel CEST quantification in vivo.

RESULTS

The spinlock model-based fitting of QUASS CEST MRI provided a nearly T1 -independent determination of multi-pool CEST signals, advantageous over the fittings of apparent CEST MRI (model-free and model-based). In vivo data also demonstrated that the spinlock model-based QUASS fitting captured significantly different changes in semisolid magnetization transfer (-0.9 ± 0.8 vs. 0.3 ± 0.8%), amide (-1.1 ± 0.4 vs. -0.5 ± 0.2%), and guanidyl (1.0 ± 0.4 vs. 0.7 ± 0.3%) signals over the model-free Lorentzian analysis.

CONCLUSION

Our study demonstrated that spinlock model-based fitting of QUASS CEST MRI improved the determination of the underlying tissue changes following acute stroke, promising further clinical translation of quantitative CEST imaging.

Multi-parametric MRI assessment of melatonin regulating the polarization of microglia in rats after cerebral ischemia/reperfusion injury

OBJECTIVES

Multi-parametric magnetic resonance imaging (MRI) can provide comprehensive and valuable information for precise diagnosis and treatment evaluation of a number of diseases. In this study, the neuroprotective effects of melatonin (Mel) on a rat model of cerebral ischemia/reperfusion injury (CIRI) were assessed by multi-parametric MRI combined with histopathological techniques for longitudinal monitoring of the lesion microenvironment.

METHODS

Sixty Sprague Dawley (SD) rats were randomly divided into three groups: the Sham, CIRI and CIRI + Mel groups. At multiple time points after ischemia, MRI scanning was performed on a 7.0 Tesla MRI scanner. Multi-parametric MRI includes T2-weighted imaging (T2WI), diffusion weighted imaging (DWI), and chemical exchange saturation transfer (CEST)-MRI. CEST effects were calculated by the Lorentzian difference method, 3.5 ppm indicates amide protons of mobile proteins/peptide (Amide-CEST) and 2.0 ppm indicates amine protons (Guan-CEST). Multiple histopathological techniques were used to examine the histopathological changes and explore the therapeutic effects of Mel.

RESULTS

T2WI and DWI-MRI could localize the infarct foci and areas in CIRI rats, which was further validated by staining, 2, 3, 5-triphenyl tetrazolium chloride (TTC) staining, hematoxylin and eosin (H&E) staining, and terminal deoxynucleotidyl transferase-mediated deoxyuridine triphosphate-biotin nick end labelling (TUNEL) staining. After Mel treatment, T2WI and DWI-MRI showed smaller infarct volume, and neurons displayed improved morphology with less apoptosis rates. Notably, Amide-CEST and Guan-CEST signal decreased as early as 2 h after CIRI (all P <0.001), reflecting the change of pH after ischemia. After Mel treatment, both Amide-CEST and Guan-CEST signal increased in ischemic cortex and striatum compared with control group (all P < 0.001). The immunofluorescence staining and western blotting analysis suggested the expression of M2 microglia increased after Mel treatment; While，after Mel treatment the inflammatory factor interleukin-1β (IL-1β) decreased compared with control CIRI rats.

CONCLUSIONS

Multi-parametric MRI was shown to be an effective method to monitor the brain damage in a rat model of CIRI and assess the therapeutic effects of Mel treatment. Amide-CEST and Guan-CEST were especially sensitive to the changes in brain microenvironment during the early stage after CIRI. Furthermore, the neuroprotective effect of Mel treatment is associated with its promotion of the microglia polarized to M2 type in CIRI rats.

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.

Numerical fitting of Extrapolated semisolid Magnetization transfer Reference signals: Improved detection of ischemic stroke

PURPOSE

To propose a novel Numerical fitting method of the Extrapolated semisolid Magnetization transfer Reference (NEMR) signal for quantifying the CEST effect.

THEORY AND METHODS

Modified two-pool Bloch-McConnell equations were used to numerically fit the magnetization transfer (MT) and direct water saturation (DS) signals at far off-resonance frequencies, which was subsequently extrapolated into the frequency range of amide proton transfer (APT) and nuclear Overhauser enhancement (NOE) pools. Then the subtraction of the fitted two-pool z-spectrum and the experimentally acquired z-spectrum yielded APT^# and NOE^# signals mostly free of MT and DS contamination. Several strategies were used to accelerate the NEMR fitting. Furthermore, the proposed NEMR method was compared with the conventional extrapolated semisolid magnetization transfer reference (EMR) and magnetization transfer ratio asymmetry (MTR_asym ) methods in simulations and stroke patients.

RESULTS

The combination of RF downsampling, MT lineshape look-up table, and conversion of MATLAB code to C code accelerated the NEMR fitting by over 2700-fold. Monte-Carlo simulations showed that NEMR had higher accuracy than EMR and eliminated the requirement of the steady-state condition. In ischemic stroke patients, the NEMR maps at 1 μT removed hypointense artifacts seen on EMR and MTR_asym images, and better depicted stroke lesions than EMR. For NEMR, NOE^# yielded significantly (p < 0.05) stronger signal contrast between stroke and normal tissues than APT^# at 1 μT.

CONCLUSION

The proposed NEMR method is suitable for arbitrary saturation settings and can remove MT and DS contamination from the CEST signal for improved detection of ischemic stroke.

Dual-Peak Lorentzian CEST MRI for antiretroviral drug brain distribution

Objectives

Spatial-temporal biodistribution of antiretroviral drugs (ARVs) can now be achieved using MRI by utilizing chemical exchange saturation transfer (CEST) contrasts. However, the presence of biomolecules in tissue limits the specificity of current CEST methods. To overcome this limitation, a Lorentzian line-shape fitting algorithm was developed that simultaneously fits CEST peaks of ARV protons on its Z-spectrum.

Case presentation

This algorithm was tested on the common first line ARV, lamivudine (3TC), that has two peaks resulting from amino (-NH2) and hydroxyl (-OH) protons in 3TC. The developed dual-peak Lorentzian function fitted these two peaks simultaneously, and used the ratio of -NH2 and -OH CEST contrasts as a constraint parameter to measure 3TC presence in brains of drug-treated mice. 3TC biodistribution calculated using the new algorithm was compared against actual drug levels measured using UPLC-MS/MS. In comparison to the method that employs the -NH2 CEST peak only, the dual-peak Lorentzian fitting algorithm showed stronger correlation with brain tissue 3TC levels, signifying estimation of actual drug levels.

Conclusions

We concluded that 3TC levels can be extracted from confounding CEST effects of tissue biomolecules resulting in improved specificity for drug mapping. This algorithm can be expanded to measure a variety of ARVs using CEST MRI.

Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) quantification of transient ischemia using a combination method of 5-pool Lorentzian fitting and inverse Z-spectrum analysis

Background

Chemical exchange saturation transfer (CEST) is a promising method for the detection of biochemical alterations in cancers and neurological diseases. However, the sensitivity of the currently existing quantitative method for detecting ischemia needs further improvement.

Methods

To further improve the quantification of the CEST signal and enhance the CEST detection for ischemia, we used a quantitative analysis method that combines an inverse Z-spectrum analysis and a 5-pool Lorentzian fitting. Specifically, a 5-pool Lorentzian simulation was conducted with the following brain tissue parameters: water, amide (3.5 ppm), amine (2.2 ppm), magnetization transfer (MT), and nuclear Overhauser enhancement (NOE; -3.5 ppm). The parameters were first calculated offline and stored as the initial value of the Z-spectrum fitting. Then, the measured Z-spectrum with the peak value set to 0 was fitted via the stored initial value, which yielded the reference Z-spectrum. Finally, the difference between the inverse of the Z-spectrum and the inverse of the reference Z-spectrum was used as the CEST definite spectrum.

Results

The simulation results demonstrated that the Z-spectra of the rat brain were well simulated by a 5-pool Lorentzian fitting. Further, the proposed method detected a larger difference than did either the saturation transfer difference or the 5-pool Lorentzian fitting, as demonstrated by simulations. According to the results of the cerebral ischemia rat model, the proposed method provided the highest contrast-to-noise ratio (CNR) between the contralateral and the ipsilateral striatum under various acquisition conditions. The results indicated that the difference of fitted amplitudes generated with a 5-pool Lorentzian fitting in amide at 3.5 ppm (6.04%±0.39%; 6.86%±0.39%) was decreased in a stroke lesion compared to the contralateral normal tissue. Moreover, the difference of the residual of inversed Z-spectra in which 5-pool Lorentzian fitting was used to calculate the reference Z-spectra ( M T R R e x 5 L ) amplitudes in amide at 3.5 ppm (13.83%±2.20%, 15.69%±1.99%) was reduced in a stroke lesion compared to the contralateral normal tissue.

Conclusions

M T R R e x 5 L is predominantly pH-sensitive and is suitable for detecting tissue acidosis following an acute stroke.

Reassembled saturation transfer (REST) MR images at 2 B1 values for in vivo exchange-dependent imaging of amide and nuclear Overhauser enhancement

PURPOSE

Design an efficient CEST scheme for exchange-dependent images with high contrast-to-noise ratio.

THEORY

Reassembled saturation transfer (REST) signals were defined as Δ $$ \Delta $$ r.Z = r.Z_ref - r.Z_CEST and the reassembled exchange-dependen magnetization transfer ratio r.MTR_Rex  = r.1/Z_ref - r.1/Z_CEST , utilizing the averages over loosely sampled reference frequency offsets as Z_ref and over densely sampled target offsets as Z_CEST . Using r.MTR_Rex measured under 2 B_1,sat values, exchange rate could be estimated.

METHODS

The REST approach was optimized and assessed quantitatively by simulations for various exchange rates, pool concentration, and water T₁ . In vivo evaluation was performed on ischemic rat brains at 7 Tesla and human brains at 3 Tesla, in comparison with conventional asymmetrical analysis, Lorentzian difference (LD), an MTR_{Rex_} LD.

RESULTS

For a broad choice of Δ ω ref $$ \Delta {\omega}_{ref} $$ ranges and numbers, Δr.Z and r.MTR_Rex exhibited comparable quantification features with conventional LD and MTR_Rex _LD, respectively, when B_1,sat  ≤ 1 μT. The subtraction of 2 REST values under distinct B_1,sat values showed linear relationships with exchange rate and obtained immunity to field inhomogeneity and variation in MT and water T₁ . For both rat and human studies, REST images exhibited similar contrast distribution to MTR_Rex _LD, with superiority in contrast-to-noise ratio and acquisition efficiency. Compared with MTR_Rex _LD, 2-B_1,sat subtraction REST images displayed better resistance to B₁ inhomogeneity, with more specific enhanced regions. They also showed higher signals for amide than for nuclear Overhauser enhancement effect in human brain, presumably reflecting the higher increment from faster-exchanging species as B_1,sat increased.

CONCLUSION

Featuring high contrast-to-noise ratio efficiency, REST could be a practical exchange-dependent approach readily applicable to either retrospective Z-spectra analysis or perspective 6-offset acquisition.

Guanidinium and amide CEST mapping of human brain by high spectral resolution CEST at 3 T

PURPOSE

To extract guanidinium (Guan) and amide CEST on the human brain at 3 T MRI with the high spectral resolution (HSR) CEST combined with the polynomial Lorentzian line-shape fitting (PLOF).

METHODS

Continuous wave (cw) turbo spin-echo (TSE) CEST was implemented to obtain the optimum saturation parameters. Both Guan and amide CEST peaks were extracted and quantified using the PLOF method. The NMR spectra on the egg white phantoms were acquired to reveal the fitting range and the contributions to the amide and GuanCEST. Two types of CEST approaches, including cw gradient- and spin-echo (cwGRASE) and steady state EPI (ssEPI), were implemented to acquire multi-slice HSR-CEST.

RESULTS

GuanCEST can be extracted with the PLOF method at 3 T, and the optimumB 1 = 0.6 μ T $$ {\mathrm{B}}_1=0.6\kern0.2em \upmu \mathrm{T} $$ was determined for GuanCEST in white matter (WM) and 1.0 μT in gray matter (GM). The optimum B1  = 0.8-1 μT was found for amideCEST. AmideCEST is lower in both WM and GM collected with ssEPI compared to those by cwGRASE (ssEPI = [1.27-1.63]%; cwGRASE = [2.19-2.25]%). The coefficients of variation (COV) of the amide and Guan CEST in both WM and GM for ssEPI (COV: 28.6-33.4%) are significantly higher than those of cwGRASE (COV: 8.6-18.8%). Completely different WM/GM contrasts for Guan and amide CEST were observed between ssEPI and cwGRASE. The amideCEST was found to have originated from the unstructured amide protons as suggested by the NMR spectrum of the unfolded proteins in egg white.

CONCLUSION

Guan and amide CEST mapping can be achieved by the HSR-CEST at 3 T combing with the PLOF method.

Quasi-steady-state amide proton transfer (QUASS APT) MRI enhances pH-weighted imaging of acute stroke

PURPOSE

Chemical exchange saturation transfer (CEST) imaging measurement depends not only on the labile proton concentration and pH-dependent exchange rate but also on experimental conditions, including the relaxation delay and radiofrequency (RF) saturation time. Our study aimed to extend a quasi-steady-state (QUASS) solution to a modified multi-slice CEST MRI sequence and test if it provides enhanced pH imaging after acute stroke.

METHODS

Our study derived the QUASS solution for a modified multislice CEST MRI sequence with an unevenly segmented RF saturation between image readout and signal averaging. Numerical simulation was performed to test if the generalized QUASS solution corrects the impact of insufficiently long relaxation delay, primary and secondary saturation times, and multi-slice readout. In addition, multiparametric MRI scans were obtained after middle cerebral artery occlusion, including relaxation and CEST Z-spectrum, to evaluate the performance of QUASS CEST MRI in a rodent acute stroke model. We also performed Lorentzian fitting to isolate multi-pool CEST contributions.

RESULTS

The QUASS analysis enhanced pH-weighted magnetization transfer asymmetry contrast over the routine apparent CEST measurements in both contralateral normal (-3.46% ± 0.62% (apparent) vs. -3.67% ± 0.66% (QUASS), P < 0.05) and ischemic tissue (-5.53% ± 0.68% (apparent) vs. -5.94% ± 0.73% (QUASS), P < 0.05). Lorentzian fitting also showed significant differences between routine and QUASS analysis of ischemia-induced changes in magnetization transfer, amide, amine, guanidyl CEST, and nuclear Overhauser enhancement (-1.6 parts per million) effects.

CONCLUSION

Our study demonstrated that generalized QUASS analysis enhanced pH MRI contrast and improved quantification of the underlying CEST contrast mechanism, promising for further in vivo applications.

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.