title: Quantitative analysis of the z-spectrum using a numerically simulated look-up table: Application to the healthy human brain at 7T.
abstract: To develop a method that fits a multipool model to z-spectra acquired from non-steady state sequences, taking into account the effects of variations in T1 or B1 amplitude and the results estimating the parameters for a four-pool model to describe the z-spectrum from the healthy brain.
  
  
  
  We compared measured spectra with a look-up table (LUT) of possible spectra and investigated the potential advantages of simultaneously considering spectra acquired at different saturation powers (coupled spectra) to provide sensitivity to a range of different physicochemical phenomena.
  
  
  
  The LUT method provided reproducible results in healthy controls. The average values of the macromolecular pool sizes measured in white matter (WM) and gray matter (GM) of 10 healthy volunteers were 8.9% ± 0.3% (intersubject standard deviation) and 4.4% ± 0.4%, respectively, whereas the average nuclear Overhauser effect pool sizes in WM and GM were 5% ± 0.1% and 3% ± 0.1%, respectively, and average amide proton transfer pool sizes in WM and GM were 0.21% ± 0.03% and 0.20% ± 0.02%, respectively.
  
  
  
  The proposed method demonstrated increased robustness when compared with existing methods (such as Lorentzian fitting and asymmetry analysis) while yielding fully quantitative results. The method can be adjusted to measure other parameters relevant to the z-spectrum. Magn Reson Med 78:645-655, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
authors.affiliation: Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom.
authors.forename: Nicolas
authors.initials: N
authors.lastname: Geades
authors.affiliation: Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom.
authors.forename: Benjamin A E
authors.initials: BAE
authors.lastname: Hunt
authors.affiliation: Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom.
authors.forename: Simon M
authors.initials: SM
authors.lastname: Shah
authors.affiliation: Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom.
authors.forename: Andrew
authors.initials: A
authors.lastname: Peters
authors.affiliation: Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom.
authors.forename: Olivier E
authors.initials: OE
authors.lastname: Mougin
authors.affiliation: Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom.
authors.forename: Penny A
authors.initials: PA
authors.lastname: Gowland
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D066128:Gray Matter / Q000000981:diagnostic imaging*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015203:Reproducibility of Results; D066127:White Matter / Q000000981:diagnostic imaging*
keywords: APT; CEST; LUT; MT; NOE; z-spectra