title: A fully automatic reference deconvolution strategy to increase the accuracy of in vivo lipid signal quantification.
abstract: OBJECTIVE
  Lipid signals measured by (1)H MR spectroscopy cannot be adequately quantified by common fitting routines like VARPRO or AMARES, if lipid spectra are distorted by irregular spatial and temporal inhomogeneities of the static magnetic field during readout. A fully automatic reference deconvolution algorithm is presented that eliminates these distortions before application of fitting routines.
  
  
  METHODS
  The measured signal of the dominant methyl resonance is isolated with aid of a spectral estimator (estimation of parameters via rotational invariance techniques) and used as reference signal for estimation of distortions. A Wiener filter is applied to deconvolve those distortions in the lipid spectrum. Performance of the algorithm is assessed for different bandwidths and shapes of distortions, using artificially distorted as well as measured data.
  
  
  RESULTS
  Application of the fully automatic reference deconvolution algorithm on simulated spectra yields a distinct increase in quantification accuracy. Deconvolved in vivo spectra of subcutaneous fat indicate reduced spectral overlap after application of the proposed strategy.
  
  
  CONCLUSIONS
  The proposed method is helpful for in vivo magnetic resonance spectroscopy of adipose tissue to correct for effects of field inhomogeneities within the voxel and for inevitable eddy current effects. Quantification accuracy is improved by eliminating distortions before application of fitting routines.
authors.affiliation: Institute of Signal Processing and System Theory, Department of Electrical Engineering and Information Technology, University of Stuttgart, Stuttgart, Germany.
authors.forename: Lukas
authors.initials: L
authors.lastname: Mauch
authors.affiliation: Department of Diagnostic and Interventional Radiology, Section on Experimental Radiology, University Hospital Tübingen, Tübingen, Germany.
authors.forename: Günter
authors.initials: G
authors.lastname: Steidle
authors.affiliation: Department of Diagnostic and Interventional Radiology, Section on Experimental Radiology, University Hospital Tübingen, Tübingen, Germany.|Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich at the University of Tübingen, German Center for Diabetes Research (DZD), Tübingen, Germany.
authors.forename: Jürgen
authors.initials: J
authors.lastname: Machann
authors.affiliation: Institute of Signal Processing and System Theory, Department of Electrical Engineering and Information Technology, University of Stuttgart, Stuttgart, Germany.
authors.forename: Bin
authors.initials: B
authors.lastname: Yang
authors.affiliation: Department of Diagnostic and Interventional Radiology, Section on Experimental Radiology, University Hospital Tübingen, Tübingen, Germany.
authors.forename: Fritz
authors.initials: F
authors.lastname: Schick
mesh_terms: D000465:Algorithms; D008055:Lipids / Q000737:chemistry*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008954:Models, Biological; D057054:Molecular Imaging / Q000379:methods*; D019047:Phantoms, Imaging
chemical_list: D008055:Lipids
keywords: Wiener filter; estimation of parameters via rotational invariance techniques algorithm; reference deconvolution; spectral overlap