Using spatial prior knowledge in the spectral fitting of MRS images

• Verfasst von: Kelm, Bernd Michael [VerfasserIn]
• Verfasst von: Kaster, Frederik Orlando [VerfasserIn]
• Verfasst von: Weber, Marc-André [VerfasserIn]
• Verfasst von: Bachert, Peter [VerfasserIn]
• Verfasst von: Hamprecht, Fred [VerfasserIn]
• Titel: Using spatial prior knowledge in the spectral fitting of MRS images
• Verf.angabe: B. Michael Kelm, Frederik O. Kaster, Anke Henning, Marc-André Weber, Peter Bachert, Peter Boesiger, Fred A. Hamprecht, Bjoern H. Menze
• Jahr: 2012
• Umfang: 13 S.
• Fussnoten: First published: 28 April 2011 ; Gesehen am 02.08.2018
• Titel Quelle: Enthalten in: NMR in biomedicine
• Ort Quelle: New York, NY : Wiley, 1988
• Jahr Quelle: 2012
• Band/Heft Quelle: 25(2012), 1, Seite 1-13
• ISSN Quelle: 1099-1492
• DOI: doi:10.1002/nbm.1704
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: MRSI
• Sach-SW: quantification
• Sach-SW: spatial prior knowledge
• Sach-SW: spectral fitting
• K10plus-PPN: 1578198267

Abstract

We propose a Bayesian smoothness prior in the spectral fitting of MRS images which can be used in addition to commonly employed prior knowledge. By combining a frequency-domain model for the free induction decay with a Gaussian Markov random field prior, a new optimization objective is derived that encourages smooth parameter maps. Using a particular parameterization of the prior, smooth damping, frequency and phase maps can be obtained whilst preserving sharp spatial features in the amplitude map. A Monte Carlo study based on two sets of simulated data demonstrates that the variance of the estimated parameter maps can be reduced considerably, even below the Cramér-Rao lower bound, when using spatial prior knowledge. Long-TE 1H MRSI at 1.5 T of a patient with a brain tumor shows that the use of the spatial prior resolves the overlapping peaks of choline and creatine when a single voxel method fails to do so. Improved and detailed metabolic maps can be derived from high-spatial-resolution, short-TE 1H MRSI at 3 T. Finally, the evaluation of four series of long-TE brain MRSI data with various signal-to-noise ratios shows the general benefit of the proposed approach. Copyright © 2011 John Wiley & Sons, Ltd.