• Donghyun Hong, van AstenJack J AJJADepartment of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, Netherlands., Seyedmorteza Rohani Rankouhi, Jan-Willem Thielen, and David G Norris.
• Erwin L. Hahn Institute for Magnetic Resonance Imaging, University of Duisburg-Essen, Essen, Germany. Electronic address: donghyun.hong@uni-due.de.
• J. Magn. Reson. 2019 Jul 1; 304: 53-61.

AbstractGood B0 field homogeneity is considered an essential requirement to obtain high-quality MRS data. Many commonly used spectral fitting methods assume that all metabolite signals have Lorentzian or Gaussian shapes. However, B0 inhomogeneity can both broaden the linewidth and modify the lineshape. In this study, it is hypothesized that a realistic metabolite fitting model, which accounts for B0 homogeneity on the basis of the water lineshape, will improve the accuracy of estimation of metabolite concentrations. In-vivo water suppressed/unsuppressed single voxel spectroscopy signals were acquired under three different B0 field homogeneity regimes. Individual realistic basis sets were created for each acquisition. Frequency-domain spectral fitting with LCModel was used to quantify the metabolite concentrations with fitting uncertainties given in terms of the Cramer-Rao lower bound. The quantification results obtained using the water lineshape basis set yielded similar concentrations independent of linewidth and showed a larger fitting error as the linewidth increased. The conventional approach, however quantifies metabolite concentrations with greater variations despite showing a supposedly improved fitting quality. The water lineshape basis set achieved single voxel spectroscopy accuracy that is less sensitive to the linewidth compared to the conventional spectral fitting method for the range of linewidths used in this study, but the precision deteriorated with worsening B0 field inhomogeneity. The beneficial effect was ascribed to a reduction in the number of degrees of freedom when using the water lineshape to generate the basis set.Copyright © 2019 Elsevier Inc. All rights reserved.

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