Quantitation of simulated short echo time 1H human brain spectra by LCModel and AMARES
Quantitation of simulated short echo time 1H human brain spectra by LCModel and AMARES
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DOI：
10.1002/mrm.20063
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发表时间：
2004-05-01
影响因子：
3.3
通讯作者：
Tempelmann, C
中科院分区：
文献类型：
--
作者：
Kanowski, M;Kaufmann, J;Tempelmann, C
利用LC Model和Amares这两个广泛使用的磁共振波谱数据量化工具，分析了与1.5T下人脑短回声时间(TES)相似的模拟光谱。研究主要集中在信噪比(SNR)和不同线宽对量化结果的准确性和精密度的影响，以及它们在解释大分子和脂类(通常称为活体MRS基线)广泛信号贡献方面的有效性。当应用于它们的标准配置(即，将样条线作为LC模型的基线，并对Amares的第一个数据点进行加权)时，这两种方法的表现相似，但具有各自的特点。LC模型和Amares量化从将基线信息纳入先验知识中获益良多。然而，对谷氨酸和谷氨酰胺总和(GIX)的更准确的定量支持使用LC模型。由扩展先验知识的LC模型估计的代谢物与肌酸的比率比绝对浓度更准确，并且几乎与SNR和线宽无关。《医学评论》51：904-912,2004。(C)2004年Wiley-Liss公司
LCModel and AMARES, two widely used quantitation tools for magnetic resonance spectroscopy (MRS) data, were employed to analyze simulated spectra similar to those typically obtained at short echo times (TEs) in the human brain at 1.5 T. The study focused mainly on the influence of signal-to-noise ratios (SNRs) and different linewidths on the accuracy and precision of the quantification results, and their effectiveness in accounting for the broad signal contribution of macromolecules and lipids (often called the baseline in in vivo MRS). When applied in their standard configuration (i.e., fitting a spline as a baseline for LCModel, and weighting the first data points for AMARES), both methods performed comparably but with their own characteristics. LCModel and AMARES quantitation benefited considerably from the incorporation of baseline information into the prior knowledge. However, the more accurate quantitation of the sum of glutamate and glutamine (GIx) favored the use of LCModel. Metabolite-to-creatine ratios estimated by LCModel with extended prior knowledge are more accurate than absolute concentrations, and are nearly independent of SNR and line broadening. Magn Reson Med 51: 904-912, 2004. (C) 2004 Wiley-Liss, Inc.