title: SNR-optimized myocardial perfusion imaging using parallel acquisition for effective density-weighted saturation recovery imaging.
abstract: The concept of density-weighted imaging and parallel acquisition for effective density-weighted (PLANED) imaging was transferred to saturation recovery (SR) sequences, in order to increase the SNR in first-pass myocardial perfusion imaging. Filtering in combination with density-weighted imaging allows SNR-optimized data weighting and the free choice of the corresponding spatial response function (SRF) simultaneously. This method was evaluated in simulations and applied successfully to phantom and in vivo first-pass myocardial perfusion studies. Unfiltered, Cartesian sampled images were compared to images acquired with SR-PLANED, which has been adjusted to result in an identical SRF as the Cartesian imaging. SNR-optimized SR-PLANED imaging improved the SNR up to 15% without changing acquisition time, the SRF or the field of view (FOV). The presented method provides high image quality and optimized SNR for first-pass myocardial perfusion imaging.
authors.affiliation: Institut für Röntgendiagnostik, Universität Würzburg, 97080 Würzburg, Germany.
authors.forename: Marcel
authors.initials: M
authors.lastname: Gutberlet
authors.forename: Oliver
authors.initials: O
authors.lastname: Geier
authors.forename: Daniel
authors.initials: D
authors.lastname: Stäb
authors.forename: Christian
authors.initials: C
authors.lastname: Ritter
authors.forename: Meinrad
authors.initials: M
authors.lastname: Beer
authors.forename: Dietbert
authors.initials: D
authors.lastname: Hahn
authors.forename: Herbert
authors.initials: H
authors.lastname: Köstler
mesh_terms: D000465:Algorithms; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D018810:Magnetic Resonance Angiography / Q000379:methods*; D055414:Myocardial Perfusion Imaging / Q000379:methods*; D019047:Phantoms, Imaging; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity