title: Model-based nonlinear inverse reconstruction for T2 mapping using highly undersampled spin-echo MRI.
abstract: OBJECTIVE
  To develop a model-based reconstruction technique for T2 mapping based on multi-echo spin-echo MRI sequences with highly undersampled Cartesian data encoding.
  
  
  METHODS
  The proposed technique relies on a nonlinear inverse reconstruction algorithm which directly estimates a T2 and spin-density map from a train of undersampled spin echoes. The method is applicable to acquisitions with single receiver coils but benefits from multi-element coil arrays. The algorithm is validated for trains of 16 spin echoes with a spacing of 10 to 12 ms using numerical simulations as well as human brain MRI at 3 Tesla (T).
  
  
  RESULTS
  When compared with a standard T2 fitting procedure using fully sampled T2-weighted images, and depending on the available signal-to-noise ratio and number of coil elements, model-based nonlinear inverse reconstructions for both simulated and in vivo MRI data yield accurate T2 estimates for undersampling factors of 5 to 10.
  
  
  CONCLUSIONS
  This work describes a promising strategy for T2-weighted MRI that simultaneously offers accurate T2 relaxation times and properly T2-weighted images at arbitrary echo times. For a standard spin-echo MRI sequence with Cartesian encoding, the method allows for a much higher degree of undersampling than obtainable by conventional parallel imaging.
authors.affiliation: Biomedizinische NMR Forschungs GmbH am Max-Planck-Institut für biophysikalische Chemie, Göttingen, Germany. tsumpf@gwdg.de
authors.forename: Tilman J
authors.initials: TJ
authors.lastname: Sumpf
authors.forename: Martin
authors.initials: M
authors.lastname: Uecker
authors.forename: Susann
authors.initials: S
authors.lastname: Boretius
authors.forename: Jens
authors.initials: J
authors.lastname: Frahm
mesh_terms: D000328:Adult; D001331:Automation; D001921:Brain / Q000473:pathology; D001931:Brain Mapping / Q000379:methods; D003198:Computer Simulation; D017352:Echo-Planar Imaging / Q000379:methods*; D004867:Equipment Design; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015233:Models, Statistical; D008962:Models, Theoretical; D019047:Phantoms, Imaging; D015203:Reproducibility of Results