Effect of offset-frequency step size and interpolation methods on chemical exchange saturation transfer MRI computation in human brain.

Chemical exchange saturation transfer (CEST) MRI is a non-invasive molecular imaging technique with potential applications in pre-clinical and clinical studies. Applications of amide proton transfer-weighted (APT-w), glutamate-weighted (Glu-w) and creatine-weighted (Cr-w) CEST, among others, have been reported. In general, CEST data are acquired at multiple offset-frequencies. In reported studies, different offset-frequency step sizes and interpolation methods have been used during B0 inhomogeneity correction of data. The objective of the current study was to evaluate the effects of different step sizes and interpolation methods on CEST value computation. In the current study, simulation (Glu-w, Cr-w and APT-w) and experimental data from the brain were used. Experimental CEST data (Glu-w) were acquired from human volunteers at 7 T and brain tumor patients (APT-w) at 3 T. During B0 inhomogeneity correction, different interpolation methods (polynomial [degree-1, 2 and 3], cubic-Hermite, cubic-spline and smoothing-spline) were compared. CEST values were computed using asymmetry analysis. The effects of different step sizes and interpolation methods were evaluated using coefficient of variation (CV), normalized mean square error (nMSE) and coefficient of correlation parameters. Additionally, an optimum interpolation method for APT-w values was selected based upon fitting accuracy, T-test, receiver operating characteristic analysis, and its diagnostic performance in differentiating low-grade and high-grade tumors. CV and nMSE increase with an increase in step size irrespective of the interpolation method (except for cubic-Hermite and cubic-spline). The nMSE of Cr-w and Glu-w CEST values were least for polynomial (degree-2 and 3). The quality of Glu-w CEST maps became coarse with the increase in step size. There was a significant difference (P < .05) between low-grade and high-grade tumors using polynomial interpolation (degree-1, 2 and 3); however, linear interpolation outperforms other methods for APT-w data, providing the highest sensitivity and specificity. In conclusion, depending upon the saturation parameters and field strength, optimization of step size and interpolation should be carried out for different CEST metabolites/molecules. Glu-w, Cr-w and APT-w CEST data should be acquired with a step size of between 0.2 and 0.3 ppm. For B0 inhomogeneity correction, polynomial (degree-2) should be used for Glu-w and Cr-w CEST data at 7 T and linear interpolation should be used for APT-w data at 3 T for a limited frequency range.

Glutamate-Weighted CEST Contrast After Removal of Magnetization Transfer Effect in Human Brain and Rat Brain with Tumor.

PURPOSE: To mitigate the effect of magnetization transfer (MT) from glutamate-weighted chemical exchange saturation transfer (GluCEST) contrast in healthy human brain and its demonstration in a rat brain tumor model. PROCEDURES: GluCEST data was acquired from six healthy human volunteers at 7T and on a rat brain with tumor at 9.4 T. Single voxel proton magnetic resonance spectroscopy (1HMRS) data was acquired from three human volunteers. The magnetic resonance imaging protocol included CEST data acquisition at multiple frequencies for generating Z-spectra, B0 and B1 map. Partial Z-spectra at offset frequencies from ± 100 to ± 14 ppm were fitted to model semi-solid MT component by Lorentzian, Gaussian, super-Lorentzian, and 6th degree polynomial function lineshapes. Average residual errors per pixel was calculated. The MT effect of the Z-spectra was removed by subtracting fitted MT component from Z-spectra. GluCEST was computed as GluCESTNeg (normalized with signal at - 3 ppm) and GluCESTM0 (normalized with unsaturated signal). The difference between GluCEST maps before and after MT removal was compared using T test. RESULTS: Better accuracy of fitting off-resonance Z-spectra was achieved with super-Lorentzian (σ = 0.0009) and Lorentzian (σ = 0.0017) compared to other lineshapes. There was significant (p < 0.01) increase in GluCESTM0 and decrease in GluCESTNeg contrast after MT removal. GluCESTNeg and GluCESTM0 maps after MT removal using Lorentzian lineshape showed gray matter (GM) to white matter (WM) contrast ratio of 1.47 and 1.52 respectively. These ratios are close to glutamate concentration ratio in GM/WM as observed from 1HMRS data. Thus, the quantity of the MT removed from Z-spectra is appropriate using Lorentzian lineshape due to preservation of GluCEST contrast-ratio in GM/WM. The amount of MT removed from Z-spectra is overestimated using super-Lorentzian and underestimated using Gaussian and polynomial lineshapes. Tumor tissue showed unexpected increase in GluCEST contrast compared to contra-lesional tissue, which represents normal appearing tissue in the brain on contra-lateral side of tumor region, due to decrease in MT component. CONCLUSIONS: Removal of MT effect from Z-spectra using Lorentzian lineshape increased the specificity of GluCEST contrast to glutamate in healthy human brain and was demonstrated in rat brain tumor model.

Evaluating the Role of Amide Proton Transfer (APT)-Weighted Contrast, Optimized for Normalization and Region of Interest Selection, in Differentiation of Neoplastic and Infective Mass Lesions on 3T MRI.

PURPOSE: To evaluate the role of amide proton transfer-weighted (APT-w) magnetic resonance imaging (MRI) in differentiating neoplastic and infective mass lesions using different contrast normalizations, region of interest (ROI) selection, and histogram analysis. PROCEDURES: Retrospective study included 32 treatment-naive patients having intracranial mass lesions (ICMLs): low-grade glioma (LGG) = 14, high-grade glioma (HGG) = 10, and infective mass lesions = 8. APT-w MRI images were acquired along with conventional MRI images at 3 T. APT-w contrast, corrected for B0-field inhomogeneity, was computed and optimized with respect to different types of normalizations. Different ROIs on lesion region were selected followed by ROI analysis and histogram analysis. Statistical analysis was performed using Shapiro-Wilk's test, t tests, ANOVA with Tukey's post hoc test, and receiver operation characteristic (ROC) analysis. RESULTS: ICMLs showed significantly (p < 0.01) higher APT-w contrast in lesion compared with contralateral side. There was a substantial overlap between mean APT-w contrast of neoplastic and infective mass lesions as well as among different groups of ICMLs irrespective of ROI selection and normalizations. APT-w contrast (using type 4 normalization: normalized with reference signal at negative offset frequency and APT-w contrast in normal-appearing white matter) reduced variability of APT-w contrast across different subjects, and overlap was less compared with other types of normalizations. There was a significant difference (p < 0.05) between neoplastic and infective mass lesions using t test for different histogram parameters of type 4 normalized APT-w contrast. ANOVA with post hoc showed significant difference (p < 0.05) for different histogram parameters of APT-w contrast (Type 4 normalization) between LGG and HGG, LGG, and infective mass lesion. Histogram parameters such as standard deviation, mean of top percentiles, and median provided improved differentiation between neoplastic and infective mass lesions compared with mean APT-w contrast. A greater number of histogram parameters of type 4 normalized APT-w contrast corresponding to active lesion region can significantly differentiate between ICMLs than other types of normalizations and ROIs. CONCLUSIONS: APT-w contrast using type 4 normalization and active lesion region (ROI-2) should be used for studying APT. APT-MRI should be combined with other MRI techniques to further improve the differential diagnosis of ICMLs.

Evaluating the feasibility of creatine-weighted CEST MRI in human brain at 7 T using a Z-spectral fitting approach.

The current study aims to evaluate the feasibility of creatine (Cr) chemical exchange saturation transfer (CEST)-weighted MRI at 7 T in the human brain by optimizing the saturation pulse parameters and computing contrast using a Z-spectral fitting approach. The Cr-weighted (Cr-w) CEST contrast was computed from phantoms data. Simulations were carried out to obtain the optimum saturation parameters for Cr-w CEST with lower contribution from other brain metabolites. CEST-w images were acquired from the brains of four human subjects at different saturation parameters. The Cr-w CEST contrast was computed using both asymmetry analysis and Z-spectra fitting approaches (models 1 and 2, respectively) based on Lorentzian functions. For broad magnetization transfer (MT) effect, Gaussian and Super-Lorentzian line shapes were also evaluated. In the phantom study, the Cr-w CEST contrast showed a linear dependence on concentration in physiological range and a nonlinear dependence on saturation parameters. The in vivo Cr-w CEST map generated using asymmetry analysis from the brain represents mixed contrast with contribution from other metabolites as well and relayed nuclear Overhauser effect (rNOE). Simulations provided an estimate for the optimum range of saturation parameters to be used for acquiring brain CEST data. The optimum saturation parameters for Cr-w CEST to be used for brain data were around B1rms  = 1.45 µT and duration = 2 seconds. The Z-spectral fitting approach enabled computation of individual components. This also resulted in mitigating the contribution from MT and rNOE to Cr-w CEST contrast, which is a major source of underestimation in asymmetry analysis. The proposed modified z-spectra fitting approach (model 2) is more stable to noise compared with model 1. Cr-w CEST contrast obtained using fitting was 6.98 ± 0.31% in gray matter and 5.45 ± 0.16% in white matter. Optimal saturation parameters reduced the contribution from other CEST effects to Cr-w CEST contrast, and the proposed Z-spectral fitting approach enabled computation of individual components in Z-spectra of the brain. Therefore, it is feasible to compute Cr-w CEST contrast with a lower contribution from other CEST and rNOE.