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大脑中含磷代谢物光谱相关性的磁场依赖性

Magnetic Field Dependence of Spectral Correlations between P-Containing Metabolites in Brain.

作者信息

Hong Sungtak, Shen Jun

机构信息

Section on Magnetic Resonance Spectroscopy, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA.

出版信息

Metabolites. 2023 Jan 31;13(2):211. doi: 10.3390/metabo13020211.

Abstract

Spectral correlations between metabolites in P magnetic resonance spectroscopy (MRS) spectra of human brain were compared at 3 and 7 Tesla, the two commonly used magnetic field strengths for clinical research. It was found that at both field strengths, there are significant correlations between P-containing metabolites arising from spectral overlap, and their downfield correlations are markedly altered by the background spectral baseline. Overall, the spectral correlations between P-containing metabolites are markedly reduced at 7 Tesla with the increased chemical shift dispersion and the decreased membrane phospholipid signal. The findings provide the quantitative landscape of pre-existing correlations in P MRS spectra due to overlapping signals. Detailed procedures for quantifying the pre-existing correlations between P-containing metabolites are presented to facilitate incorporation of spectral correlations into statistical modeling in clinical correlation studies.

摘要

在3特斯拉和7特斯拉这两种临床研究常用的磁场强度下,对人脑磷磁共振波谱(MRS)谱中代谢物之间的光谱相关性进行了比较。结果发现,在这两种场强下,由于光谱重叠,含磷代谢物之间存在显著相关性,并且它们的低场相关性会因背景光谱基线而明显改变。总体而言,在7特斯拉时,随着化学位移分散度增加和膜磷脂信号降低,含磷代谢物之间的光谱相关性显著降低。这些发现提供了由于信号重叠而在磷MRS谱中预先存在的相关性的定量情况。本文还介绍了量化含磷代谢物之间预先存在的相关性的详细程序,以促进在临床相关性研究中将光谱相关性纳入统计建模。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cc94/9967573/0b24e3f3595d/metabolites-13-00211-g001.jpg

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