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• W2017995976 abstract "In (1)H magnetic resonance spectroscopy, macromolecule signals underlay metabolite signals, and knowing their contribution is necessary for reliable metabolite quantification. When macromolecule signals are measured using an inversion-recovery pulse sequence, special care needs to be taken to correctly remove residual metabolite signals to obtain a pure macromolecule spectrum. Furthermore, since a single spectrum is commonly used for quantification in multiple experiments, the impact of potential macromolecule signal variability, because of regional differences or pathologies, on metabolite quantification has to be assessed. In this study, we introduced a novel method to post-process measured macromolecule signals that offers a flexible and robust way of removing residual metabolite signals. This method was applied to investigate regional differences in the mouse brain macromolecule signals that may affect metabolite quantification when not taken into account. However, since no significant differences in metabolite quantification were detected, it was concluded that a single macromolecule spectrum can be generally used for the quantification of healthy mouse brain spectra. Alternatively, the study of a mouse model of human glioma showed several alterations of the macromolecule spectrum, including, but not limited to, increased mobile lipid signals, which had to be taken into account to avoid significant metabolite quantification errors." @default.
• W2017995976 created "2016-06-24" @default.
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• W2017995976 date "2014-02-26" @default.
• W2017995976 modified "2023-10-17" @default.
• W2017995976 title "<i>In vivo</i>brain macromolecule signals in healthy and glioblastoma mouse models:¹H magnetic resonance spectroscopy, post-processing and metabolite quantification at 14.1 T" @default.
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• W2017995976 doi "https://doi.org/10.1111/jnc.12673" @default.
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