Dataset Information

Effectiveness of fat suppression using a water-selective binomial-pulse excitation in chemical exchange saturation transfer (CEST) magnetic resonance imaging.

ABSTRACT:

Purpose

The purpose of this study was to characterize the individual contribution of multiple fat peaks to the measured chemical exchange saturation transfer (CEST) signal when using water-selective binomial-pulse excitation and to determine the effects of multiple fat peaks in the presence of B₀ inhomogeneity.

Methods

The excitation profiles of multiple binomial pulses were simulated. A CEST sequence with binomial-pulse excitation and modified point-resolved spectroscopy localization was then applied to the in vivo lumbar spinal vertebrae to determine the signal contributions of three distinct groups of lipid resonances. These confounding signal contributions were measured as a function of the irradiation frequency offset to determine the effect of the multi-peak nature of the fat signal on CEST imaging of exchange sites (at 1.0, 2.0 and 3.5 ppm) and robustness in the presence of B₀ inhomogeneity.

Results

Numerical simulations and in vivo experiments showed that water excitation (WE) using a 1-3-3-1 (WE-4) pulse provided the broadest signal suppression, which provided partial robustness against B₀ inhomogeneity effects. Confounding fat signal contributions to the CEST contrasts at 1.0, 2.0 and 3.5 ppm were unavoidable due to the multi-peak nature of the fat signal. However, these CEST sites only suffer from small lipid artifacts with ∆B₀ spanning roughly from - 50 to 50 Hz. Especially for the CEST site at 3.5 ppm, the lipid artifacts are smaller than 1% with ∆B₀ in this range.

Conclusion

In WE-4-based CEST magnetic resonance imaging, B₀ inhomogeneity is the limiting factor for fat suppression. The CEST sites at 1.0, 2.0 ppm and 3.5 ppm unavoidably suffer from lipid artifacts. However, when the ∆B₀ is confined to a limited range, these CEST sites are only affected by small lipid artifacts, which may be ignorable in some cases of clinical applications.

SUBMITTER: Zhao Y

PROVIDER: S-EPMC8592310 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description: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 ?T 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 ?T 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.