Cabanes E, Confort-Gouny S, Le Fur Y, Simond G, Cozzone P J
Centre de Résonance Magnétique Biologique et Médicale, UMR CNRS 6612, Faculté de Médecine de Marseille, 27 Boulevard Jean Moulin, 13005 Marseille, France.
J Magn Reson. 2001 Jun;150(2):116-25. doi: 10.1006/jmre.2001.2318.
Suppression of the residual water signal from proton magnetic resonance (MR) spectra recorded in human brain is a prerequisite to an accurate quantification of cerebral metabolites. Several postacquisition methods of residual water signal suppression have been reported but none of them provide a complete elimination of the residual water signal, thereby preventing reliable quantification of brain metabolites. In the present study, the elimination of the residual water signal by the Hankel Lanczos singular value decomposition method has been evaluated and optimized to provide fast automated processing of spectra. Model free induction decays, reproducing the proton signal acquired in human brain localized MR spectroscopy at short echo times (e.g., 20 ms), have been generated. The optimal parameters in terms of number of components and dimension of the Hankel data matrix allowing complete elimination of the residual water signal are reported.
抑制人脑质子磁共振(MR)谱中残留水信号是准确量化脑代谢物的前提条件。已经报道了几种采集后抑制残留水信号的方法,但没有一种能完全消除残留水信号,从而妨碍了脑代谢物的可靠量化。在本研究中,对通过汉克尔·兰索斯奇异值分解方法消除残留水信号进行了评估和优化,以实现光谱的快速自动化处理。已经生成了自由感应衰减模型,该模型再现了在短回波时间(例如20毫秒)下人脑局部磁共振波谱中采集的质子信号。报告了在汉克尔数据矩阵的分量数量和维度方面允许完全消除残留水信号的最佳参数。