Long echo time (TE=270 ms) in vivo proton NMR spectra resembling human brain metabolite patterns were simulated for lineshape fitting (LF) and quantitative artificial neural network (ANN) analyses. A set of experimental in vivo 1H NMR spectra were first analyzed by the LF method to match the signal-
Use of voigt lineshape for quantification of in vivo1H spectra
โ Scribed by Ian Marshall; John Higinbotham; Stephen Bruce; Andreas Freise
- Publisher
- John Wiley and Sons
- Year
- 1997
- Tongue
- English
- Weight
- 671 KB
- Volume
- 37
- Category
- Article
- ISSN
- 0740-3194
No coin nor oath required. For personal study only.
โฆ Synopsis
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 LorentzianโGaussian (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 X^2^ (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 ^1^H 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 (โ2% and โ1%, respectively).
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