Myung-Ho In1, Oleg Posnansky1, Oliver Speck1,2,3,4. 1. Department of Biomedical Magnetic Resonance, Institute for Experimental Physics, Otto-von-Guericke University Magdeburg, Germany. 2. German Centre for Neurodegenerative Diseases (DZNE), Site Magdeburg, Germany. 3. Leibniz Institute for Neurobiology, Magdeburg, Germany. 4. Center for Behavioral Brain Sciences, Magdeburg, Germany.
Abstract
PURPOSE: To accurately correct diffusion-encoding direction-dependent eddy-current-induced geometric distortions in diffusion-weighted echo-planar imaging (DW-EPI) and to minimize the calibration time at 7 Tesla (T). METHODS: A point spread function (PSF) mapping based eddy-current calibration method is newly presented to determine eddy-current-induced geometric distortions even including nonlinear eddy-current effects within the readout acquisition window. To evaluate the temporal stability of eddy-current maps, calibration was performed four times within 3 months. Furthermore, spatial variations of measured eddy-current maps versus their linear superposition were investigated to enable correction in DW-EPIs with arbitrary diffusion directions without direct calibration. For comparison, an image-based eddy-current correction method was additionally applied. Finally, this method was combined with a PSF-based susceptibility-induced distortion correction approach proposed previously to correct both susceptibility and eddy-current-induced distortions in DW-EPIs. RESULTS: Very fast eddy-current calibration in a three-dimensional volume is possible with the proposed method. The measured eddy-current maps are very stable over time and very similar maps can be obtained by linear superposition of principal-axes eddy-current maps. High resolution in vivo brain results demonstrate that the proposed method allows more efficient eddy-current correction than the image-based method. CONCLUSION: The combination of both PSF-based approaches allows distortion-free images, which permit reliable analysis in diffusion tensor imaging applications at 7T.
PURPOSE: To accurately correct diffusion-encoding direction-dependent eddy-current-induced geometric distortions in diffusion-weighted echo-planar imaging (DW-EPI) and to minimize the calibration time at 7 Tesla (T). METHODS: A point spread function (PSF) mapping based eddy-current calibration method is newly presented to determine eddy-current-induced geometric distortions even including nonlinear eddy-current effects within the readout acquisition window. To evaluate the temporal stability of eddy-current maps, calibration was performed four times within 3 months. Furthermore, spatial variations of measured eddy-current maps versus their linear superposition were investigated to enable correction in DW-EPIs with arbitrary diffusion directions without direct calibration. For comparison, an image-based eddy-current correction method was additionally applied. Finally, this method was combined with a PSF-based susceptibility-induced distortion correction approach proposed previously to correct both susceptibility and eddy-current-induced distortions in DW-EPIs. RESULTS: Very fast eddy-current calibration in a three-dimensional volume is possible with the proposed method. The measured eddy-current maps are very stable over time and very similar maps can be obtained by linear superposition of principal-axes eddy-current maps. High resolution in vivo brain results demonstrate that the proposed method allows more efficient eddy-current correction than the image-based method. CONCLUSION: The combination of both PSF-based approaches allows distortion-free images, which permit reliable analysis in diffusion tensor imaging applications at 7T.
Authors: Myung-Ho In; Ek Tsoon Tan; Joshua D Trzasko; Yunhong Shu; Daehun Kang; Uten Yarach; Shengzhen Tao; Erin M Gray; John Huston; Matt A Bernstein Journal: J Magn Reson Imaging Date: 2019-05-20 Impact factor: 4.813
Authors: Joana R Loureiro; Gisela E Hagberg; Thomas Ethofer; Michael Erb; Jonas Bause; Philipp Ehses; Klaus Scheffler; Marc Himmelbach Journal: Hum Brain Mapp Date: 2016-09-23 Impact factor: 5.038