Quantitative lactate-specific MR imaging and 1H spectroscopy of skeletal muscle at macroscopic and microscopic resolutions using a zero-quantum/double-quantum coherence filter and SLIM/GSLIM localization.
Quantitative lactate-specific MR imaging and 1H spectroscopy of skeletal muscle at macroscopic and microscopic resolutions using a zero-quantum/double-quantum coherence filter and SLIM/GSLIM localization.
复制标题
使用零量子/双量子相干滤波器和 SLIM/GSLIM 定位，以宏观和微观分辨率对骨骼肌进行定量乳酸特异性 MR 成像和 1H 光谱。
DOI：
10.1002/mrm.1910370607
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发表时间：
1997
影响因子：
3.3
通讯作者：
Dawson,MJ
中科院分区：
文献类型：
--
作者：
Kmiecik,JA;Gregory,CD;Liang,ZP;Hrad,DE;Lauterbur,PC;Dawson,MJ
在体模和电刺激的青蛙骨骼肌上进行了宏观和微观分辨率的定量乳酸成像和光谱分析。乳酸选择性是通过使用零量子/双量子相干(ZQC/DQC)乳酸过滤器实现的，该过滤器将除乳酸以外的所有信号(包括水和脂肪)抑制到低于噪声水平。在1-3h内获得三维乳酸数据集；其中一个空间维度是频率编码的，另外两个维度是相位编码的。使用光谱成像局部化(SLIM)和广义SLIM(GSLIM)技术重建高分辨率图像。乳酸的定量是通过使用外部乳酸浓度标准来实现的，并通过与使用总肌酸作为内部浓度参考的定量蒸汽定域和非定域光谱进行比较来验证。此外，应用于低信噪比数据集和宏观异质对象的SLIM和GSLIM技术的定量准确行为被使用模拟和具有已知异质性的真实肌肉乳酸数据集来验证。
Quantitative lactate imaging and spectroscopy were performed on phantoms and on electrically stimulated, excised frog skeletal muscle at macroscopic and microscopic resolutions. Lactate selectivity was achieved by use of a zero‐quantum/double‐quantum coherence (ZQC/DQC) lactate filter, which suppressed all signals besides lactate, including water and lipid, to below noise level. Three‐dimensional lactate data sets were acquired in 1–3 h; one of these spatial dimensions was frequency‐encoded and the other two were phase‐encoded. High‐resolution images were reconstructed using the spectral localization by imaging (SLIM) and generalized SLIM (GSLIM) techniques. Lactate quantitation was achieved by employing an external lactate concentration standard and was verified by comparison to quantitative STEAM‐localized and nonlocalized spectra that used total creatine as an internal concentration reference. Additionally, quantitatively accurate behavior of the SLIM and GSLIM techniques as applied to data sets of low signal‐to‐noise ratio and to macroscopically heterogeneous objects was verified using simulations and real muscle lactate data sets with known heterogeneity.