Use of voigt lineshape for quantification of in vivo¹H spectra

Abstract

Quantification of NMR visible metabolites by spectral modeling usually assumes a Lorentzian or Gaussian lineshape, despite the fact that experimental lineshapes are neither. To minimize systematic fitting errors, a mixed Lorentzian-Gaussian (Voigt) lineshape model was developed. When tested with synthetic FIDs, the Voigt lineshape model gave more accurate results (maximum error 2%) than either Lorentzian (maximum error 20%) or Gaussian models (maximum error 12%). The three lineshape models gave substantially different peak areas in an in vitro experiment, with the Voigt model having a much lower chi2 (2.1 compared with 5.2 for the Lorentzian model and 6.2 for the Gaussian model). In a group of 10 healthy volunteers, fitting of 1H spectra from cerebral white matter gave significantly different peak areas between the methods. Even when area ratios were taken, the Lorentzian model gave higher values (+5% for NAA/choline and +2% for NAA/creatine) than the Voigt lineshape model, whereas the Gaussian model gave lower values (-2% and -1%, respectively).

Fast quantification of proton magnetic resonance spectroscopic imaging with artificial neural networks

“…In the RBFNN method we employed Voigt lineshape. As indicated earlier, Voigt lineshape is a better approximation than Lorentzian or Gaussian alone [18]. It is also worth pointing out that Kanowski et al [46] have also observed lower Cho values with AMARES compared with the LCModel.…”

“…These assumptions are not valid. It is generally agreed that the Voigt lineshape is closer to the observed lineshapes compared to Lorentzian or Gaussian alone [18]. In these studies, we trained the network using the Voigt lineshape.…”

“…Area of peak = μA(1) + (1 − μ)A(g) [18] Simulations-Simulations were performed in the frequency domain to test the performance of the trained networks using the following equations:…”

“…The above studies also employed Lorentzian lineshapes in their analyses. It is well known that the Voigt lineshape provides a better approximation of the observed lineshapes compared to Lorentzian or Gaussian alone [18].…”

MR spectroscopy quantitation: a review of time‐domain methods

“…Usually information concerning the time evolution of some of the parameters is present. Suppose there are S signals, each of which can be modeled by eqn (1). The nth sample of signal s, y ns , is then given by y ns…”