Difference optimization: Automatic correction of relative frequency and phase for mean non-edited and edited GABA 1H MEGA-PRESS spectra
Difference optimization: Automatic correction of relative frequency and phase for mean non-edited and edited GABA 1H MEGA-PRESS spectra
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DOI：
10.1016/j.jmr.2017.04.004
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发表时间：
2017-06-01
影响因子：
2.2
通讯作者：
Reichenbach, Juergen R.
中科院分区：
文献类型：
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作者：
Cleve, Marianne;Kraemer, Martin;Reichenbach, Juergen R.
磁共振光谱数据的相位和频率校正对于获得可靠和明确的代谢物估计是非常重要的，这在最近的具有相同光谱指纹的单次扫描研究中得到了验证。然而，当使用J-差异编辑技术H-1 MEGA-PRESS时，即使在校正相应的单个单次扫描后，平均编辑（（ON）在条上）和未编辑（（OFF）在条上）光谱之间可能仍然存在不对齐，导致减法伪影损害可靠的GABA定量。我们提出了一个全自动的程序，迭代优化同时相对频率和相位之间的平均值（ON）酒吧和（OFF）酒吧H-1 MEGA-PRESS频谱，同时最大限度地减少差异频谱（L-1范数）的幅度之和。所提出的方法被施加到模拟频谱在不同的信噪比水平与故意预设的频率和相位误差。差异优化被证明是更敏感的小信号波动，例如所产生的减法伪影，并优于替代的光谱配准方法，这与我们提出的线性方法，使用非线性最小二乘最小化（L-2范数），在所有调查的SNR水平。此外，所提出的方法被应用到47 MEGA-PRESS数据集在体内采集在3 T。通过应用（a）无校正，（B）差异优化或（c）光谱配准，比较了条形图上平均值（OFF）和条形图上平均值（ON）之间的对齐结果。由于体内数据的真实频率和相位误差未知，因此将手动校正的光谱用作金标准参考（d）。应用方法（B）或方法（c）两者的自动校正数据显示光谱质量的明显改善，如由在棒光谱上的相应真实的部分平均值（DIFF）之间的平均皮尔逊相关系数R-bd = 0.997 ± 0.003所揭示的（方法（B）对（d）），与R-ad = 0.764 +/- 0.220（方法（a）对（d））相比，在条上的（OFF）和条上的（ON）之间没有对齐。方法（c）显示，与R-bd相比，R-cd = 0.972 +/- 0.028的相关系数略低，这可归因于在条形光谱上的最终（DIFF）中存在少量剩余减法伪影。总之，差分优化稳健地执行，没有关于输入数据范围或用户干预的限制，并且代表了在平均之前在单个ON和OFF扫描的强制频率和相位校正之后优化最终（DIFF）的条形频谱的补充工具。(C)2017爱思唯尔公司All rights reserved.
Phase and frequency corrections of magnetic resonance spectroscopic data are of major importance to obtain reliable and unambiguous metabolite estimates as validated in recent research for single-shot scans with the same spectral fingerprint. However, when using the J-difference editing technique H-1 MEGA-PRESS, misalignment between mean edited ((ON) over bar) and non-edited ((OFF) over bar) spectra that may remain even after correction of the corresponding individual single-shot scans results in subtraction artefacts compromising reliable GABA quantitation. We present a fully automatic routine that iteratively optimizes simultaneously relative frequencies and phases between the mean (ON) over bar and (OFF) over bar H-1 MEGA-PRESS spectra while minimizing the sum of the magnitude of the difference spectrum (L-1 norm). The proposed method was applied to simulated spectra at different SNR levels with deliberately preset frequency and phase errors. Difference optimization proved to be more sensitive to small signal fluctuations, as e.g. arising from subtraction artefacts, and outperformed the alternative spectral registration approach, that, in contrast to our proposed linear approach, uses a nonlinear least squares minimization (L-2 norm), at all investigated levels of SNR. Moreover, the proposed method was applied to 47 MEGA-PRESS datasets acquired in vivo at 3 T. The results of the alignment between the mean (OFF) over bar and (ON) over bar spectra were compared by applying (a) no correction, (b) difference optimization or (c) spectral registration. Since the true frequency and phase errors are not known for in vivo data, manually corrected spectra were used as the gold standard reference (d). Automatically corrected data applying both, method (b) or method (c), showed distinct improvements of spectra quality as revealed by the mean Pearson correlation coefficient between corresponding real part mean (DIFF) over bar spectra of R-bd = 0.997 0.003 (method (b) vs. (d)), compared to R-ad = 0.764 +/- 0.220 (method (a) vs. (d)) with no alignment between (OFF) over bar and (ON) over bar. Method (c) revealed a slightly lower correlation coefficient of R-cd = 0.972 +/- 0.028 compared to R-bd, that can be ascribed to small remaining subtraction artefacts in the final (DIFF) over bar spectrum. In conclusion, difference optimization performs robustly with no restrictions regarding the input data range or user intervention and represents a complementary tool to optimize the final (DIFF) over bar spectrum following the mandatory frequency and phase corrections of single ON and OFF scans prior to averaging. (C) 2017 Elsevier Inc. All rights reserved.