Zhang Yan, Shen Jun
MR Spectroscopy Core Facility, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland, USA.
Magn Reson Med. 2014 Oct;72(4):913-22. doi: 10.1002/mrm.25013. Epub 2013 Nov 20.
A nonparametric smooth line is usually added to the spectral model to account for background signals in vivo magnetic resonance spectroscopy (MRS). The assumed smoothness of the baseline significantly influences quantitative spectral fitting. In this paper, a method is proposed to minimize baseline influences on the estimated spectral parameters.
The nonparametric baseline function with a given smoothness was treated as a function of spectral parameters. Its uncertainty was measured by root-mean-square error (RMSE). The proposed method was demonstrated with a simulated spectrum and in vivo spectra of both short echo time and averaged echo times. The estimated in vivo baselines were compared with the metabolite-nulled spectra and the LCModel-estimated baselines. The accuracies of estimated baseline and metabolite concentrations were further verified via cross-validation.
An optimal smoothness condition was found that led to the minimal baseline RMSE. In this condition, the best fit was balanced against minimal baseline influences on metabolite concentration estimates.
Baseline RMSE can be used to indicate estimated baseline uncertainties and serve as the criterion for determining the baseline smoothness of in vivo MRS.
在活体磁共振波谱(MRS)中,通常会在光谱模型中添加一条非参数平滑线来解释背景信号。基线的假定平滑度会显著影响定量光谱拟合。本文提出了一种方法,以尽量减少基线对估计光谱参数的影响。
将具有给定平滑度的非参数基线函数视为光谱参数的函数。其不确定性通过均方根误差(RMSE)来衡量。该方法通过模拟光谱以及短回波时间和平均回波时间的活体光谱进行了验证。将估计的活体基线与代谢物归零光谱和LCModel估计的基线进行了比较。通过交叉验证进一步验证了估计基线和代谢物浓度的准确性。
发现了一个导致基线RMSE最小的最佳平滑度条件。在此条件下,最佳拟合与对代谢物浓度估计的最小基线影响达到平衡。
基线RMSE可用于指示估计的基线不确定性,并作为确定活体MRS基线平滑度的标准。