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Abstract #1097

B0 navigator enables respiratory motion navigation in radial stack-of-stars liver T1 mapping

Jonathan Stelter1, Kilian Weiss2, Veronika Spieker3,4, Julia A. Schnabel3,4,5, and Dimitrios C. Karampinos1
1School of Medicine and Health, Technical University of Munich, Munich, Germany, 2Philips GmbH Market DACH, Hamburg, Germany, 3Institute of Machine Learning for Biomedical Imaging, Helmholtz Munich, Neuherberg, Germany, 4School of Computation, Information and Technology, Technical University of Munich, Munich, Germany, 5School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom

Synopsis

Keywords: Motion Correction, Quantitative Imaging, Liver

Motivation: The radial stack-of-stars trajectory allows to oversample k-space center in free-breathing liver imaging, but motion navigation may be challenging in acquisitions with varying contrast weightings.

Goal(s): To develop a B0 self-navigation approach applicable for free-breathing acquisitions with varying contrasts and apply it in Look-Locker-based T1 mapping.

Approach: A methodology is developed where the B0 self-navigator is estimated from oversampled k-space, water-fat separation is applied, and normalized breathing curve and amplitude of breathing-induced B0 variation are estimated through demodulating B0 drift and contrast variations.

Results: The proposed method is successfully applied in simulations and in vivo, improving reconstructed T1 maps when used for navigation.

Impact: B0 self-navigation allows to estimate respiratory motion in acquisitions with varying contrasts and quantifies the amplitude of B0 variations, enabling self-gated reconstruction without external motion sensors. This may be useful to develop patient-specific motion correction in future studies.

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