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Abstract #1956

Prospective motion correction in multi-inversion EPI using volumetric navigators for robust T1 map estimation

Jonathan R. Polimeni1,2,3, M. Dylan Tisdall4, Daniel J. Park1, Paul Wighton1, S. Robert Frost1,2, Christine L. Tardif5,6, and Andre J. W. van der Kouwe1,2
1Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States, 2Department of Radiology, Harvard Medical School, Boston, MA, United States, 3Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States, 4Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States, 5Department of Biomedical Engineering, Department of Neurology & Neurosurgery, McGill University, Montreal, QC, Canada, 6McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC, Canada


In multi-inversion EPI (MI-EPI), each slice samples a distinct inversion time during each inversion recovery, providing an efficient method for estimating T1. MI-EPI is vulnerable to through-plane motion, which results in slices sampling a subset of the desired inversion times and wrong TIs will be attributed to the slices. This cannot be corrected retrospectively. We introduce prospective motion correction in MI-EPI using volumetric navigators (vNavs). vNavs are acquired at the beginning of the inversion recovery thus the effects of their excitation pulses must be modeled for T1 estimation. This provides improved T1 estimation accuracy in the presence of subject motion.

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