Methodology for improved detection of low concentration metabolites in MRS: Optimised combination of signals from multi-element coil arrays

Methodology for improved detection of low concentration metabolites in MRS: Optimised combination of signals from multi-element coil arrays
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DOI:
10.1016/j.neuroimage.2013.04.077
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发表时间:
2014-02-01
期刊:
影响因子:
5.7
通讯作者:
Morris, Peter G.
Morris, Peter G.
中科院分区:
医学1区
文献类型:
--
作者:
Hall, Emma L.;Stephenson, Mary C.;Morris, Peter G.

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现有技术的磁共振成像(MRI)扫描仪通常配备有多元件接收线圈; 16或32通道线圈是常见的。它们的发展主要用于并行成像,以实现更快的扫描。很少考虑到局部磁共振波谱(MRS)。多核研究,例如P-31或C-13 MRS,通常使用位于感兴趣区域上方的单元件线圈进行。H-1 MRS研究通常采用与MRI相同的多元件线圈,但很少考虑如何将来自不同通道的光谱数据组合起来。在许多情况下,它只是简单地共同添加,对信噪比有不利影响。在这项研究中,我们得出的最佳方法,结合多线圈的数据,即加权与信号的噪声的平方比。我们表明,只要噪声是不相关的,这是理论上的最佳组合。该方法被证明在体内质子MRS数据采集使用32通道接收线圈在7 T在四个不同的大脑区域,左电机和右电机,枕叶皮质和内侧额叶皮质。(C)2013 Elsevier Inc. All rights reserved.
State of the art magnetic resonance imaging (MRI) scanners are generally equipped with multi-element receive coils; 16 or 32 channel coils are common. Their development has been predominant for parallel imaging to enable faster scanning. Less consideration has been given to localized magnetic resonance spectroscopy (MRS). Multinuclear studies, for example P-31 or C-13 MRS, are often conducted with a single element coil located over the region of interest. H-1 MRS studies have generally employed the same multi-element coils used for MRI, but little consideration has been given as to how the spectroscopic data from the different channels are combined. In many cases it is simply co-added with detrimental effect on the signal to noise ratio. In this study, we derive the optimum method for combining multi-coil data, namely weighting with the ratio of signal to the square of the noise. We show that provided that the noise is uncorrelated, this is the theoretical optimal combination. The method is demonstrated for in vivo proton MRS data acquired using a 32 channel receive coil at 7 T in four different brain areas; left motor and right motor, occipital cortex and medial frontal cortex. (C) 2013 Elsevier Inc. All rights reserved.