Fast quantitative susceptibility mapping using 3D EPI and total generalized variation.
Quantitative susceptibility mapping (QSM) allows new insights into tissue composition and organization by assessing its magnetic property. Previous QSM studies have already demonstrated that magnetic susceptibility is highly sensitive to myelin density and fiber orientation as well as to para- and diamagnetic trace elements. Image resolution in QSM with current approaches is limited by the long acquisition time of 3D scans and the need for high signal to noise ratio (SNR) to solve the dipole inversion problem. We here propose a new total-generalized-variation (TGV) based method for QSM reconstruction, which incorporates individual steps of phase unwrapping, background field removal and dipole inversion in a single iteration, thus yielding a robust solution to the reconstruction problem. This approach has beneficial characteristics for low SNR data, allowing for phase data to be rapidly acquired with a 3D echo planar imaging (EPI) sequence. The proposed method was evaluated with a numerical phantom and in vivo at 3 and 7 T. Compared to total variation (TV), TGV-QSM enforced higher order smoothness which yielded solutions closer to the ground truth and prevented stair-casing artifacts. The acquisition time for images with 1mm isotropic resolution and whole brain coverage was 10s on a clinical 3 Tesla scanner. In conclusion, 3D EPI acquisition combined with single-step TGV reconstruction yields reliable QSM images of the entire brain with 1mm isotropic resolution in seconds. The short acquisition time combined with the robust reconstruction may enable new QSM applications in less compliant populations, clinical susceptibility tensor imaging, and functional resting state examinations.
MGH Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Boston, MA, USA; Department of Neurology, Medical University of Graz, Graz, Austria. Electronic address: clangkammer@mgh.harvard.edu.
Christian
C
Langkammer
Institute of Mathematics and Scientific Computing, University of Graz, Graz, Austria.
Kristian
K
Bredies
Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands.
Benedikt A
BA
Poser
Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia.
Markus
M
Barth
Department of Radiology, Division of Neuroradiology, Medical University of Graz, Graz, Austria.
Gernot
G
Reishofer
Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA; Lucas Center for Imaging, Stanford University, Stanford, CA, USA.
Audrey Peiwen
AP
Fan
MGH Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Boston, MA, USA.
Berkin
B
Bilgic
Department of Neurology, Medical University of Graz, Graz, Austria.
Franz
F
Fazekas
MGH Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Boston, MA, USA.
Caterina
C
Mainero
Department of Neurology, Medical University of Graz, Graz, Austria.
Stefan
S
Ropele
D001921:Brain / Q000033:anatomy & histology*; D055590:Electromagnetic Phenomena; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*
Dipole inversion; Iron; Myelin; Quantitative susceptibility mapping; Susceptibility tensor imaging; Total generalized variation; Total variation