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Abstract #4388

Free-running 3D Radial Myocardial T1 Mapping using Self-Calibrating GRAPPA Operator Gridding for Accelerated Iterative Reconstruction

Haikun Qi1, Aurelien Bustin1, Olivier Jaubert1, René Botnar1, and Claudia Prieto1

1School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom

Free-running 3D radial (kooshball) sampling is suitable for fast and self-navigated whole-heart cardiovascular imaging. However, iterative undersampled 3D radial reconstruction requires computational demanding gridding/regridding steps in each iteration, which leads to long reconstruction time and may limit the applications of this imaging strategy. In this work, we investigate the feasibility of accelerating iterative reconstruction for a free-running 3D myocardial T1 mapping sequence using GRAPPA Operator Gridding (GROG)-based pre-reconstruction interpolation. Image quality and T1 estimation accuracy of the accelerated GROG-based reconstruction were compared with conventional non-uniform FFT (NUFFT)-based reconstruction in a standardized phantom and five healthy subjects.

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