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Approximated analytical characterization of the steady‐state chemical exchange saturation transfer (CEST) signals
Author(s) -
Jin Tao,
Kim SeongGi
Publication year - 2019
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.27864
Subject(s) - laser linewidth , magnetization transfer , chemistry , sensitivity (control systems) , saturation (graph theory) , asymmetry , bloch equations , spectral line , nuclear magnetic resonance , characterization (materials science) , position (finance) , statistical physics , physics , quantum mechanics , mathematics , optics , finance , electronic engineering , magnetic resonance imaging , engineering , economics , radiology , medicine , laser , combinatorics
Purpose CEST MRI can indirectly detect low‐concentrated molecules via their proton exchange with the bulk water and is widely measured by a sensitivity index, the asymmetry of magnetization transfer ratio (MTR asym ). Because CEST applications are often limited by their low sensitivity or specificity, it is important to characterize MTR asym analytically to optimize its sensitivity or specifity. Methods Approximated analytical solutions of the MTR asym spectrum were derived based on a 2‐pool chemical exchange model for slow‐to‐intermediate exchanges. The optimal saturation pulse power for maximizing the MTR asym or tuning MTR asym to a specific exchange rate and the peak position and linewidth of a MTR asym spectrum were also derived. These approximated analytical solutions were compared with the solutions from the Bloch‐McConnell equations using computer simulations. Results The approximated analytical solutions of the MTR asym spectra, the optimizing parameters, and the peak and linewidth of MTR asym matched well with the solutions of Bloch‐McConnell equations in the slow or slow‐to‐intermediate exchange regimes. Conclusion These approximate analytical solutions can provide insights to the understanding of CEST signal property and help the optimization of saturation parameters and the interpretation of CEST data.