Abdoli Abas, Maudsley Andrew A
Department of Radiology, University of Miami School of Medicine, Miami, Florida, USA.
Magn Reson Med. 2016 Sep;76(3):733-41. doi: 10.1002/mrm.25992. Epub 2015 Sep 28.
To evaluate methods for multichannel combination of three-dimensional MR spectroscopic imaging (MRSI) data with a focus on using information from a water-reference spectroscopic image.
Volumetric MRSI data were acquired for a phantom and for human brain using 8- and 32-channel detection. Acquisition included a water-reference dataset that was used to determine the weights for several multichannel combination methods. Results were compared using the signal-to-noise ratio (SNR) of the N-acetylaspartate resonance.
Performance of all methods was very similar for the phantom study, with the whitened singular value decomposition (WSVD) and signal magnitude (S) weighting combination having a small advantage. For in vivo studies, the S weighting, SNR weighting and signal to noise squared (S/N(2) ) weighting were the three best methods and performed similarly. Example spectra and SNR maps indicated that the SVD and WSVD methods tend to fail for voxels at the outer edges of the brain that include strong lipid signal contributions.
For data combination of MRSI data using water-reference information, the S/N(2) weighting, SNR and S weighting were the best methods in terms of spectral quality SNR. These methods are also computationally efficient and easy to implement. Magn Reson Med 76:733-741, 2016. © 2015 Wiley Periodicals, Inc.
评估三维磁共振波谱成像（MRSI）数据的多通道组合方法，重点是利用来自水参考波谱图像的信息。
使用8通道和32通道检测，获取了体模和人脑的容积MRSI数据。采集包括一个水参考数据集，用于确定几种多通道组合方法的权重。使用N-乙酰天门冬氨酸共振的信噪比（SNR）比较结果。
在体模研究中，所有方法的性能非常相似，白化奇异值分解（WSVD）和信号幅度（S）加权组合具有微小优势。对于体内研究，S加权、SNR加权和信噪比平方（S/N(2)）加权是三种最佳方法，且性能相似。示例波谱和SNR图表明，奇异值分解（SVD）和WSVD方法对于包含强脂质信号贡献的脑外边缘体素往往失效。
对于使用水参考信息的MRSI数据组合，就波谱质量SNR而言，S/N(2)加权、SNR和S加权是最佳方法。这些方法在计算上也很高效且易于实现。《磁共振医学》76:733 - 741, 2016。© 2015威利期刊公司。
