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PURPOSE: To develop a distortion correction method for echo planar imaging (EPI) that is able to measure dynamic changes in B0 . THEORY AND METHODS: The approach we propose is based on single-echo EPI with a jittering of the echo time between two values for alternate time points. Field maps are calculated between phase images from adjacent volumes and are used to remove distortion from corresponding magnitude images. The performance of our approach was optimized using an analytical model and by comparison with field maps from dual-echo EPI. The method was tested in functional MRI experiments at 7T with motor tasks and compared with the conventional static approach. RESULTS: Unwarping using our method was accurate even for head rotations up to 8.2°, where the static approach introduced errors up to 8.2 mm. Jittering the echo time between 19 and 25 ms had no measurable effect on blood oxygenation level-dependent (BOLD) sensitivity. Our approach reduced the distortions in activated regions to <1 mm and repositioned active voxels correctly. CONCLUSION: This method yields accurate distortion correction in the presence of motion. No reduction in BOLD sensitivity was observed. As such, it is suitable for application in a wide range of functional MRI experiments. Magn Reson Med 76:1388-1399, 2016. © 2015 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Original publication




Journal article


Magn Reson Med

Publication Date





1388 - 1399


EPI, dynamic distortion correction, fMRI, field mapping, respiration effects, ultra-high field, Adult, Algorithms, Artifacts, Brain, Brain Mapping, Echo-Planar Imaging, Female, Humans, Image Enhancement, Image Interpretation, Computer-Assisted, Male, Reproducibility of Results, Sensitivity and Specificity, Signal Processing, Computer-Assisted