Abstract #0462

Motion-compensated 3D radial MRI using self-encoded FID navigators

Tess E. Wallace^1,2, Davide Piccini^3,4,5, Tobias Kober^3,4,5, Simon K. Warfield^1,2, and Onur Afacan^1,2

¹Computational Radiology Laboratory, Boston Children's Hospital, Boston, MA, United States, ²Department of Radiology, Harvard Medical School, Boston, MA, United States, ³Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland, ⁴Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland, ⁵LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland

We propose a novel motion compensation strategy for 3D radial MRI that directly estimates rigid-body motion parameters from the central k-space signal, which acts as a self-encoded FID navigator. By modelling trajectory deviations as low-spatial-order field variations, motion parameters can be recovered using a model that predicts the impact of motion and field changes on the FID signal. The proposed method enabled robust compensation for deliberate head motion in volunteers, with position estimates and image quality equivalent to that obtained with electromagnetic tracking. Our approach is suitable for robust neuroanatomical imaging in subjects that exhibit patterns of large, frequent motion.

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