An illustrated comparison of processing methods for MR phase imaging and QSM: combining array coil signals and phase unwrapping.
Phase imaging benefits from strong susceptibility effects at very high field and the high signal-to-noise ratio (SNR) afforded by multi-channel coils. Combining the information from coils is not trivial, however, as the phase that originates in local field effects (the source of interesting contrast) is modified by the inhomogeneous sensitivity of each coil. This has historically been addressed by referencing individual coil sensitivities to that of a volume coil, but alternative approaches are required for ultra-high field systems in which no such coil is available. An additional challenge in phase imaging is that the phase that develops up to the echo time is "wrapped" into a range of 2π radians. Phase wraps need to be removed in order to reveal the underlying phase distribution of interest. Beginning with a coil combination using a homogeneous reference volume coil - the Roemer approach - which can be applied at 3 T and lower field strengths, we review alternative methods for combining single-echo and multi-echo phase images where no such reference coil is available. These are applied to high-resolution data acquired at 7 T and their effectiveness assessed via an index of agreement between phase values over channels and the contrast-to-noise ratio in combined images. The virtual receiver coil and COMPOSER approaches were both found to be computationally efficient and effective. The main features of spatial and temporal phase unwrapping methods are reviewed, placing particular emphasis on recent developments in temporal phase unwrapping and Laplacian approaches. The features and performance of these are illustrated in application to simulated and high-resolution in vivo data. Temporal unwrapping was the fastest of the methods tested and the Laplacian the most robust in images with low SNR. © 2016 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.
High Field Magnetic Resonance Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Austria.
Simon Daniel
SD
Robinson
Institute of Mathematics and Scientific Computing, University of Graz, Austria.
Kristian
K
Bredies
Laboratory for Functional and Metabolic Imaging, École Polytechnique Fédérale de Lausanne, Switzerland.|Donders Institute for Brain, Cognition and Behaviou, Radboud University Nijmegen, The Netherlands.
Diana
D
Khabipova
High Field Magnetic Resonance Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Austria.
Barbara
B
Dymerska
Laboratory for Functional and Metabolic Imaging, École Polytechnique Fédérale de Lausanne, Switzerland.|Donders Institute for Brain, Cognition and Behaviou, Radboud University Nijmegen, The Netherlands.
José P
JP
Marques
Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, New York, USA.|MRI Clinical and Translational Research Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, New York, USA.
Ferdinand
F
Schweser
D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology*; D038524:Diffusion Magnetic Resonance Imaging / Q000295:instrumentation / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000295:instrumentation / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000295:instrumentation / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation
QSM; array coils; phase; phase combination; phase unwrapping