Quantitative magnetization transfer experiments require extensive sampling of the off-resonance spectrum to obtain information of the relaxation properties of non-water protons. To reduce the acquisition times, the off-resonance sampling has been optimized in previous works based on the stability of approximate biophysical model fits. Here, we use a singular value decomposition approach for the analysis of the principal components. In particular we propose a data-driven optimization method for the acquisition scheme and we discuss the potential impact of applying this analysis for parameter estimations, including potential extensions of the classical biophysical models.
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