Iqbal Zohaib, Wilson Neil E, Thomas M Albert
Department of Radiological Sciences, University of California Los Angeles, USA.
NMR Biomed. 2016 Mar;29(3):329-39. doi: 10.1002/nbm.3469. Epub 2016 Jan 8.
Several different pathologies, including many neurodegenerative disorders, affect the energy metabolism of the brain. Glutamate, a neurotransmitter in the brain, can be used as a biomarker to monitor these metabolic processes. One method that is capable of quantifying glutamate concentration reliably in several regions of the brain is TE-averaged (1) H spectroscopic imaging. However, this type of method requires the acquisition of multiple TE lines, resulting in long scan durations. The goal of this experiment was to use non-uniform sampling, compressed sensing reconstruction and an echo planar readout gradient to reduce the scan time by a factor of eight to acquire TE-averaged spectra in three spatial dimensions. Simulation of glutamate and glutamine showed that the 2.2-2.4 ppm spectral region contained 95% glutamate signal using the TE-averaged method. Peak integration of this spectral range and home-developed, prior-knowledge-based fitting were used for quantitation. Gray matter brain phantom measurements were acquired on a Siemens 3 T Trio scanner. Non-uniform sampling was applied retrospectively to these phantom measurements and quantitative results of glutamate with respect to creatine 3.0 (Glu/Cr) ratios showed a coefficient of variance of 16% for peak integration and 9% for peak fitting using eight-fold acceleration. In vivo scans of the human brain were acquired as well and five different brain regions were quantified using the prior-knowledge-based algorithm. Glu/Cr ratios from these regions agreed with previously reported results in the literature. The method described here, called accelerated TE-averaged echo planar spectroscopic imaging (TEA-EPSI), is a significant methodological advancement and may be a useful tool for categorizing glutamate changes in pathologies where affected brain regions are not known a priori. Copyright © 2016 John Wiley & Sons, Ltd.
包括许多神经退行性疾病在内的几种不同病理状况会影响大脑的能量代谢。谷氨酸是大脑中的一种神经递质，可用作监测这些代谢过程的生物标志物。一种能够在大脑多个区域可靠地定量谷氨酸浓度的方法是TE平均（1）H光谱成像。然而，这种类型的方法需要采集多条TE线，导致扫描时间较长。本实验的目的是使用非均匀采样、压缩感知重建和回波平面读出梯度将扫描时间缩短八倍，以在三个空间维度上获取TE平均光谱。谷氨酸和谷氨酰胺的模拟显示，使用TE平均方法，2.2 - 2.4 ppm光谱区域包含95%的谷氨酸信号。该光谱范围的峰值积分和自主开发的基于先验知识的拟合用于定量分析。在西门子3T Trio扫描仪上进行了灰质脑模型测量。对这些模型测量结果进行了回顾性非均匀采样，谷氨酸相对于肌酸3.0（Glu/Cr）比值的定量结果显示，使用八倍加速时，峰值积分的变异系数为16%，峰值拟合的变异系数为9%。还对人脑进行了活体扫描，并使用基于先验知识的算法对五个不同的脑区进行了定量分析。这些区域的Glu/Cr比值与文献中先前报道的结果一致。这里描述的方法称为加速TE平均回波平面光谱成像（TEA - EPSI），是一项重大的方法学进步，可能是一种有用的工具，用于对事先未知受影响脑区的病理状况中的谷氨酸变化进行分类。版权所有© 2016约翰威立父子有限公司。
