Victor Adalid1,2, André Döring1,2, Sreenath Pruthviraj Kyathanahally1,2, Christine Sandra Bolliger3, Chris Boesch1, Roland Kreis4. 1. Departments of Radiology and Clinical Research, University Bern, Bern, Switzerland. 2. Graduate School for Cellular and Biomedical Sciences, University Bern, Bern, Switzerland. 3. Bruker BioSpin AG, Fällanden, Switzerland. 4. Departments of Radiology and Clinical Research, University Bern, Bern, Switzerland. roland.kreis@insel.ch.
Abstract
OBJECTIVE: Simultaneous modeling of true 2-D spectroscopy data, or more generally, interrelated spectral datasets has been described previously and is useful for quantitative magnetic resonance spectroscopy applications. In this study, a combined method of reference-lineshape enhanced model fitting and two-dimensional prior-knowledge fitting for the case of diffusion weighted MR spectroscopy is presented. MATERIALS AND METHODS: Time-dependent field distortions determined from a water reference are applied to the spectral bases used in linear-combination modeling of interrelated spectra. This was implemented together with a simultaneous spectral and diffusion model fitting in the previously described Fitting Tool for Arrays of Interrelated Datasets (FiTAID), where prior knowledge conditions and restraints can be enforced in two dimensions. RESULTS: The benefit in terms of increased accuracy and precision of parameters is illustrated with examples from Monte Carlo simulations, in vitro and in vivo human brain scans for one- and two-dimensional datasets from 2-D separation, inversion recovery and diffusion-weighted spectroscopy (DWS). For DWS, it was found that acquisitions could be substantially shortened. CONCLUSION: It is shown that inclusion of a measured lineshape into modeling of interrelated MR spectra is beneficial and can be combined also with simultaneous spectral and diffusion modeling.
OBJECTIVE: Simultaneous modeling of true 2-D spectroscopy data, or more generally, interrelated spectral datasets has been described previously and is useful for quantitative magnetic resonance spectroscopy applications. In this study, a combined method of reference-lineshape enhanced model fitting and two-dimensional prior-knowledge fitting for the case of diffusion weighted MR spectroscopy is presented. MATERIALS AND METHODS: Time-dependent field distortions determined from a water reference are applied to the spectral bases used in linear-combination modeling of interrelated spectra. This was implemented together with a simultaneous spectral and diffusion model fitting in the previously described Fitting Tool for Arrays of Interrelated Datasets (FiTAID), where prior knowledge conditions and restraints can be enforced in two dimensions. RESULTS: The benefit in terms of increased accuracy and precision of parameters is illustrated with examples from Monte Carlo simulations, in vitro and in vivo human brain scans for one- and two-dimensional datasets from 2-D separation, inversion recovery and diffusion-weighted spectroscopy (DWS). For DWS, it was found that acquisitions could be substantially shortened. CONCLUSION: It is shown that inclusion of a measured lineshape into modeling of interrelated MR spectra is beneficial and can be combined also with simultaneous spectral and diffusion modeling.
Entities:
Keywords:
Diffusion; Magnetic resonance spectroscopy; Model fitting; Quantification; Signal processing
Authors: Małgorzata Marjańska; Edward J Auerbach; Romain Valabrègue; Pierre-François Van de Moortele; Gregor Adriany; Michael Garwood Journal: NMR Biomed Date: 2011-07-27 Impact factor: 4.044
Authors: Martyna Dziadosz; Maike Hoefemann; André Döring; Malgorzata Marjańska; Edward John Auerbach; Roland Kreis Journal: Magn Reson Med Date: 2022-05-08 Impact factor: 3.737