Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Joint Graduate Program in Biomedical Engineering at University of Texas Arlington and University of Texas Southwestern Medical Center, Texas, USA.
Magn Reson Med. 2021 Oct;86(4):1818-1828. doi: 10.1002/mrm.28829. Epub 2021 May 12.
H MRS provides a noninvasive tool for identifying mutations in isocitrate dehydrogenase (IDH). Quantification of the prominent 2-hydroxyglutarate (2HG) resonance at 2.25 ppm is often confounded by the lipid resonance at the same frequency in tumors with elevated lipids. We propose a new spectral fitting approach to separate these overlapped signals, therefore, improving 2HG evaluation.
TE 97 ms PRESS was acquired at 3T from 42 glioma patients. New lipid basis sets were created, in which the small lipid 2.25-ppm signal strength was preset with reference to the lipid signal at 0.9 ppm, incorporating published fat relaxation data. LCModel fitting using the new lipid bases (Fitting method 2) was conducted along with fitting using the LCModel built-in lipid basis set (Fitting method 1), in which the lipid 2.25-ppm signal is assessed with reference to the lipid 1.3-ppm signal. In-house basis spectra of low-molecular-weight metabolites were used in both fitting methods.
Fitting method 2 showed marked improvement in identifying IDH mutational status compared with Fitting method 1. 2HG estimates from Fitting method 2 were overall smaller than those from Fitting method 1, which was because of differential assignment of the signal at 2.25 ppm to lipids. In receiver operating characteristic analysis, Fitting method 2 provided a complete distinction between IDH mutation and wild-type whereas Fitting method 1 did not.
The data suggest that H MR spectral fitting using the new lipid basis set provides a robust fitting strategy that improves 2HG evaluation in brain tumors with elevated lipids.
H MRS 提供了一种非侵入性的工具,用于识别异柠檬酸脱氢酶(IDH)突变。在脂质水平升高的肿瘤中,2-羟基戊二酸(2HG)共振峰在 2.25ppm 处的定量分析常受到相同频率脂质共振的干扰。我们提出了一种新的谱拟合方法来分离这些重叠信号,从而改善 2HG 的评估。
在 3T 上从 42 例胶质瘤患者中采集 TE 97ms PRESS。创建了新的脂质基线集,其中预设了小脂质 2.25ppm 信号强度,参考了 0.9ppm 处的脂质信号,并结合了已发表的脂肪弛豫数据。使用新的脂质基线(拟合方法 2)和 LCModel 内置的脂质基线(拟合方法 1)进行 LCModel 拟合,其中脂质 2.25ppm 信号是参考脂质 1.3ppm 信号进行评估的。两种拟合方法均使用内部低分子代谢物的基线谱。
与拟合方法 1 相比,拟合方法 2 在识别 IDH 突变状态方面有明显改善。拟合方法 2 的 2HG 估计值总体上小于拟合方法 1,这是因为信号在 2.25ppm 处的分配不同。在受试者工作特征分析中,拟合方法 2 提供了 IDH 突变和野生型之间的完全区分,而拟合方法 1 则没有。
数据表明,使用新的脂质基线集进行 H MR 谱拟合提供了一种稳健的拟合策略,可以改善脂质水平升高的脑肿瘤中 2HG 的评估。