Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Journal articles
  4. Which prior knowledge? Quantification of in vivo brain (13) C MR spectra following (13) C glucose infusion using AMARES
 
research article

Which prior knowledge? Quantification of in vivo brain (13) C MR spectra following (13) C glucose infusion using AMARES

Lanz, Bernard  
•
Duarte, João M. N.
•
Kunz, Nicolas  
Show more
2013
Magnetic Resonance in Medicine

The recent developments in high magnetic field (13) C magnetic resonance spectroscopy with improved localization and shimming techniques have led to important gains in sensitivity and spectral resolution of (13) C in vivo spectra in the rodent brain, enabling the separation of several (13) C isotopomers of glutamate and glutamine. In this context, the assumptions used in spectral quantification might have a significant impact on the determination of the (13) C concentrations and the related metabolic fluxes. In this study, the time domain spectral quantification algorithm AMARES (advanced method for accurate, robust and efficient spectral fitting) was applied to (13) C magnetic resonance spectroscopy spectra acquired in the rat brain at 9.4 T, following infusion of [1,6-(13) C(2) ] glucose. Using both Monte Carlo simulations and in vivo data, the goal of this work was: (1) to validate the quantification of in vivo (13) C isotopomers using AMARES; (2) to assess the impact of the prior knowledge on the quantification of in vivo (13) C isotopomers using AMARES; (3) to compare AMARES and LCModel (linear combination of model spectra) for the quantification of in vivo (13) C spectra. AMARES led to accurate and reliable (13) C spectral quantification similar to those obtained using LCModel, when the frequency shifts, J-coupling constants and phase patterns of the different (13) C isotopomers were included as prior knowledge in the analysis. Magn Reson Med, 2012. © 2012 Wiley Periodicals, Inc.

  • Files
  • Details
  • Metrics
Loading...
Thumbnail Image
Name

Lanz_Amares_2013.pdf

Type

Publisher's Version

Version

Published version

Access type

openaccess

Size

2.18 MB

Format

Adobe PDF

Checksum (MD5)

9afaf2605eee40c0ebc37da6e53597b7

Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés