title: Fitting interrelated datasets: metabolite diffusion and general lineshapes.
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.
  
  
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Departments of Radiology and Clinical Research, University Bern, Bern, Switzerland.|Graduate School for Cellular and Biomedical Sciences, University Bern, Bern, Switzerland.
authors.forename: Victor
authors.initials: V
authors.lastname: Adalid
authors.affiliation: Departments of Radiology and Clinical Research, University Bern, Bern, Switzerland.|Graduate School for Cellular and Biomedical Sciences, University Bern, Bern, Switzerland.
authors.forename: André
authors.initials: A
authors.lastname: Döring
authors.affiliation: Departments of Radiology and Clinical Research, University Bern, Bern, Switzerland.|Graduate School for Cellular and Biomedical Sciences, University Bern, Bern, Switzerland.
authors.forename: Sreenath Pruthviraj
authors.initials: SP
authors.lastname: Kyathanahally
authors.affiliation: Bruker BioSpin AG, Fällanden, Switzerland.
authors.forename: Christine Sandra
authors.initials: CS
authors.lastname: Bolliger
authors.affiliation: Departments of Radiology and Clinical Research, University Bern, Bern, Switzerland.
authors.forename: Chris
authors.initials: C
authors.lastname: Boesch
authors.affiliation: Departments of Radiology and Clinical Research, University Bern, Bern, Switzerland. roland.kreis@insel.ch.
authors.forename: Roland
authors.identifier: http://orcid.org/0000-0002-8618-6875
authors.initials: R
authors.lastname: Kreis
mesh_terms: D001921:Brain / Q000378:metabolism; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D006801:Humans; D009682:Magnetic Resonance Spectroscopy / Q000379:methods* / Q000706:statistics & numerical data; D008954:Models, Biological; D009010:Monte Carlo Method
keywords: Diffusion; Magnetic resonance spectroscopy; Model fitting; Quantification; Signal processing