Felix Lugauer1, Dominik Nickel2, Jens Wetzl3, Berthold Kiefer2, Joachim Hornegger3, Andreas Maier3. 1. Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, Martensstr. 3, 91058, Erlangen, Germany. felix.lugauer@fau.de. 2. Siemens Healthcare GmbH, Diagnostic Imaging, Erlangen, Germany. 3. Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, Martensstr. 3, 91058, Erlangen, Germany.
Abstract
OBJECTIVES: Our aim was to demonstrate the benefits of using locally low-rank (LLR) regularization for the compressed sensing reconstruction of highly-accelerated quantitative water-fat MRI, and to validate fat fraction (FF) and [Formula: see text] relaxation against reference parallel imaging in the abdomen. MATERIALS AND METHODS: Reconstructions using spatial sparsity regularization (SSR) were compared to reconstructions with LLR and the combination of both (LLR+SSR) for up to seven fold accelerated 3-D bipolar multi-echo GRE imaging. For ten volunteers, the agreement with the reference was assessed in FF and [Formula: see text] maps. RESULTS: LLR regularization showed superior noise and artifact suppression compared to reconstructions using SSR. Remaining residual artifacts were further reduced in combination with SSR. Correlation with the reference was excellent for FF with [Formula: see text] = 0.99 (all methods) and good for [Formula: see text] with [Formula: see text] = [0.93, 0.96, 0.95] for SSR, LLR and LLR+SSR. The linear regression gave slope and bias (%) of (0.99, 0.50), (1.01, 0.19) and (1.01, 0.10), and the hepatic FF/[Formula: see text] standard deviation was 3.5%/12.1 s[Formula: see text], 1.9%/6.4 s[Formula: see text] and 1.8%/6.3 s[Formula: see text] for SSR, LLR and LLR+SSR, indicating the least bias and highest SNR for LLR+SSR. CONCLUSION: A novel reconstruction using both spatial and spectral regularization allows obtaining accurate FF and [Formula: see text] maps for prospectively highly accelerated acquisitions.
OBJECTIVES: Our aim was to demonstrate the benefits of using locally low-rank (LLR) regularization for the compressed sensing reconstruction of highly-accelerated quantitative water-fat MRI, and to validate fat fraction (FF) and [Formula: see text] relaxation against reference parallel imaging in the abdomen. MATERIALS AND METHODS: Reconstructions using spatial sparsity regularization (SSR) were compared to reconstructions with LLR and the combination of both (LLR+SSR) for up to seven fold accelerated 3-D bipolar multi-echo GRE imaging. For ten volunteers, the agreement with the reference was assessed in FF and [Formula: see text] maps. RESULTS: LLR regularization showed superior noise and artifact suppression compared to reconstructions using SSR. Remaining residual artifacts were further reduced in combination with SSR. Correlation with the reference was excellent for FF with [Formula: see text] = 0.99 (all methods) and good for [Formula: see text] with [Formula: see text] = [0.93, 0.96, 0.95] for SSR, LLR and LLR+SSR. The linear regression gave slope and bias (%) of (0.99, 0.50), (1.01, 0.19) and (1.01, 0.10), and the hepatic FF/[Formula: see text] standard deviation was 3.5%/12.1 s[Formula: see text], 1.9%/6.4 s[Formula: see text] and 1.8%/6.3 s[Formula: see text] for SSR, LLR and LLR+SSR, indicating the least bias and highest SNR for LLR+SSR. CONCLUSION: A novel reconstruction using both spatial and spectral regularization allows obtaining accurate FF and [Formula: see text] maps for prospectively highly accelerated acquisitions.
Authors: Mariya Doneva; Peter Börnert; Holger Eggers; Alfred Mertins; John Pauly; Michael Lustig Journal: Magn Reson Med Date: 2010-09-21 Impact factor: 4.668
Authors: Nathan S Artz; William M Haufe; Catherine A Hooker; Gavin Hamilton; Tanya Wolfson; Guilherme M Campos; Anthony C Gamst; Jeffrey B Schwimmer; Claude B Sirlin; Scott B Reeder Journal: J Magn Reson Imaging Date: 2015-01-23 Impact factor: 4.813
Authors: Kieren G Hollingsworth; David M Higgins; Michelle McCallum; Louise Ward; Anna Coombs; Volker Straub Journal: Magn Reson Med Date: 2013-12-17 Impact factor: 4.668
Authors: Felix Lugauer; Jens Wetzl; Christoph Forman; Manuel Schneider; Berthold Kiefer; Joachim Hornegger; Dominik Nickel; Andreas Maier Journal: MAGMA Date: 2018-01-25 Impact factor: 2.310