Ultrafast CEST line scanning as a method to quantify mutarotation kinetics.

The process of mutarotation of sugars caused by a balanced reaction between their corresponding α and ß isomers, has been known for almost 200 years. Still, it remains essential in modern biochemical research, as enzymatic reactions catalyzed by mutarotases are crucial for various pathways in the energy metabolism. In our study a fast magnetic resonance technique based on chemical exchange saturation transfer (CEST) line scanning (LS) was implemented as a method to measure mutarotation kinetics on a 9.4 T small animal MRI scanner. As proof of concept, the isomeric conversion of two hexoses (glucose and galactose) and pentoses (xylose and arabinose) was investigated in an aqueous solution over time. The technique allowed for ultrafast data acquisition without the implementation of complicated encoding schemes and acceleration procedures. Thus, CEST LS provided complete CEST spectra with a frequency step size of 19.6 Hz in less than one minute. For the mutarotation analysis, CEST spectra were acquired over a time duration of four hours and analyzed with four established CEST quantification approaches - based on either asymmetry of CEST spectra or a multi-pool Lorentzian fit. The isomer ratios of the different sugars at equilibrium were determined with an overall accuracy of 94 %, using an adapted 2-side chemical exchange (CE) model. The estimated mutarotation rate constants at 22 °C were in good agreement with conventionally measured reference values, derived from optical and spectroscopic techniques.

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

PURPOSE: Chemical exchange saturation transfer signals from amines are sensitive to pH, and detection of these signals can serve as an alternative pH imaging method to amide proton transfer (APT). However, conflicting results regarding amine CEST imaging at 2 ppm in ischemic stroke have been reported. Here, we correlated amine CEST with APT in animal stroke models to evaluate its specificity to pH, and investigated the reason for the different results through simulations and sample studies. METHODS: A three-point quantification method was used to quantify APT. A polynomial fit method and a multiple-pool Lorentzian fit method were used to quantify amine CEST. Samples of creatine and glutamate were prepared to study the different CEST effects from arginine amine and fast exchanging pools. Samples of tissue homogenates with different pH were prepared to study the variation in CEST signals due only to changes in pH. RESULTS: The polynomial fit of amine CEST at 2 ppm had a significant correlation with APT, whereas the Lorentzian fit did not. Further studies showed that arginine amine contributed to the polynomial fit, whereas both the arginine amine and the fast exchanging pools contributed to the Lorentzian fit with their CEST effects varying in opposite directions after stroke. The CEST signal from the fast exchanging pool decreased, probably due to the reduced pool concentration but not pH. CONCLUSION: The variation in opposite directions led to an insignificant correlation of the Lorentzian fit of amine CEST with APT and the different results in different experimental conditions.

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.

Accuracy in the quantification of chemical exchange saturation transfer (CEST) and relayed nuclear Overhauser enhancement (rNOE) saturation transfer effects.

Accurate quantification of chemical exchange saturation transfer (CEST) effects, including dipole-dipole mediated relayed nuclear Overhauser enhancement (rNOE) saturation transfer, is important for applications and studies of molecular concentration and transfer rate (and thereby pH or temperature). Although several quantification methods, such as Lorentzian difference (LD) analysis, multiple-pool Lorentzian fits, and the three-point method, have been extensively used in several preclinical and clinical applications, the accuracy of these methods has not been evaluated. Here we simulated multiple-pool Z spectra containing the pools that contribute to the main CEST and rNOE saturation transfer signals in the brain, numerically fit them using the different methods, and then compared their derived CEST metrics with the known solute concentrations and exchange rates. Our results show that the LD analysis overestimates contributions from amide proton transfer (APT) and intermediate exchanging amine protons; the three-point method significantly underestimates both APT and rNOE saturation transfer at -3.5 ppm (NOE(-3.5)). The multiple-pool Lorentzian fit is more accurate than the other two methods, but only at lower irradiation powers (≤1 µT at 9.4 T) within the range of our simulations. At higher irradiation powers, this method is also inaccurate because of the presence of a fast exchanging CEST signal that has a non-Lorentzian lineshape. Quantitative parameters derived from in vivo images of rodent brain tumor obtained using an irradiation power of 1 µT were also compared. Our results demonstrate that all three quantification methods show similar contrasts between tumor and contralateral normal tissue for both APT and the NOE(-3.5). However, the quantified values of the three methods are significantly different. Our work provides insight into the fitting accuracy obtainable in a complex tissue model and provides guidelines for evaluating other newly developed quantification methods.

Correction of B1-inhomogeneities for relaxation-compensated CEST imaging at 7 T.

Chemical exchange saturation transfer (CEST) imaging of endogenous agents in vivo is influenced by direct water proton saturation (spillover) and semi-solid macromolecular magnetization transfer (MT). Lorentzian fit isolation and application of the inverse metric yields the pure CEST contrast AREX, which is less affected by these processes, but still depends on the measurement technique, in particular on the irradiation amplitude B1 of the saturation pulses. This study focuses on two well-known CEST effects in the slow exchange regime originating from amide and aliphatic protons resonating at 3.5 ppm or -3.5 ppm from water protons, respectively. A B1-correction of CEST contrasts is crucial for the evaluation of data obtained in clinical studies at high field strengths with strong B1-inhomogeneities. Herein two approaches for B1-inhomogeneity correction, based on either CEST contrasts or Z-spectra, are investigated. Both rely on multiple acquisitions with different B1-values. One volunteer was examined with eight different B1-values to optimize the saturation field strength and the correction algorithm. Histogram evaluation allowed quantification of the quality of the B1-correction. Finally, the correction was applied to CEST images of a patient with oligodendroglioma WHO grade 2, and showed improvement of the image quality compared with the non-corrected CEST images, especially in the tumor region.