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Many potential clinical applications of chemical exchange saturation transfer (CEST) have been studied in recent years. However, due to various limitations such as specific absorption rate guidelines and scanner hardware constraints, most of the proposed applications have yet to be translated into routine diagnostic tools. Currently, pulsed CEST which uses multiple short pulses to perform the saturation is the only viable irradiation scheme for clinical translation. However, performing quantitative model-based analysis on pulsed CEST is time consuming because it is necessary to account for the time dependent amplitude of the saturation pulses. As a result, pulsed CEST is generally treated as continuous CEST by finding its equivalent average field or power. Nevertheless, theoretical analysis and simulations reveal that the resulting magnetization is different when the different irradiation schemes are applied. In this study, the quantification of important model parameters such as the amine proton exchange rate from a pulsed CEST experiment using quantitative model-based analyses were examined. Two model-based approaches were considered - discretized and continuous approximation to the time dependent RF irradiation pulses. The results showed that the discretized method was able to fit the experimental data substantially better than its continuous counterpart, but the smaller fitted error of the former did not translate to significantly better fit for the important model parameters. For quantification of the endogenous CEST effect, such as in amide proton transfer imaging, a model-based approach using the average power equivalent saturation can thus be used in place of the discretized approximation.

Original publication

DOI

10.1016/j.jmr.2012.07.003

Type

Journal article

Journal

J Magn Reson

Publication Date

09/2012

Volume

222

Pages

88 - 95

Keywords

Algorithms, Amines, Computer Simulation, Data Interpretation, Statistical, Electromagnetic Fields, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Models, Statistical, Phantoms, Imaging, Protons, Water