Laboratory for Functional and Metabolic Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
J Neurochem. 2014 Jun;129(5):806-15. doi: 10.1111/jnc.12673. Epub 2014 Feb 26.
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.
在(1)H 磁共振波谱中,大分子信号位于代谢物信号之下,了解它们的贡献对于可靠的代谢物定量是必要的。当使用反转恢复脉冲序列测量大分子信号时,需要特别注意正确去除残留的代谢物信号,以获得纯大分子谱。此外,由于单个光谱通常用于多个实验中的定量,因此必须评估由于区域差异或病理变化导致的潜在大分子信号可变性对代谢物定量的影响。在这项研究中,我们引入了一种新的后处理测量大分子信号的方法,提供了一种灵活且稳健的去除残留代谢物信号的方法。该方法应用于研究小鼠大脑大分子信号的区域差异,当不考虑这些差异时,可能会影响代谢物的定量。然而,由于未检测到代谢物定量的显著差异,因此得出结论,单个大分子光谱通常可用于健康小鼠大脑光谱的定量。或者,对人类神经胶质瘤小鼠模型的研究显示,大分子谱发生了多种改变,包括但不限于移动脂质信号增加,为避免显著的代谢物定量误差,必须考虑这些改变。