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Quantitative susceptibility map reconstruction from MR phase data using bayesian regularization: Validation and application to brain imaging
Author(s) -
de Rochefort Ludovic,
Liu Tian,
Kressler Bryan,
Liu Jing,
Spincemaille Pascal,
Lebon Vincent,
Wu Jianlin,
Wang Yi
Publication year - 2010
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.22187
Subject(s) - quantitative susceptibility mapping , prior probability , imaging phantom , inverse problem , bayesian probability , magnetic resonance imaging , regularization (linguistics) , computer science , artificial intelligence , susceptibility weighted imaging , iterative reconstruction , nuclear magnetic resonance , pattern recognition (psychology) , physics , radiology , mathematics , medicine , mathematical analysis
The diagnosis of many neurologic diseases benefits from the ability to quantitatively assess iron in the brain. Paramagnetic iron modifies the magnetic susceptibility causing magnetic field inhomogeneity in MRI. The local field can be mapped using the MR signal phase, which is discarded in a typical image reconstruction. The calculation of the susceptibility from the measured magnetic field is an ill‐posed inverse problem. In this work, a bayesian regularization approach that adds spatial priors from the MR magnitude image is formulated for susceptibility imaging. Priors include background regions of known zero susceptibility and edge information from the magnitude image. Simulation and phantom validation experiments demonstrated accurate susceptibility maps free of artifacts. The ability to characterize iron content in brain hemorrhage was demonstrated on patients with cavernous hemangioma. Additionally, multiple structures within the brain can be clearly visualized and characterized. The technique introduces a new quantitative contrast in MRI that is directly linked to iron in the brain. Magn Reson Med, 2010. © 2009 Wiley‐Liss, Inc.