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Abstract #3568

Extended Signal Modelling and Regularization for Multi-Echo Hyperpolarized Metabolic Image Reconstruction

Julia Busch1, Valeriy Vishnevskiy1, Maximilian Fuetterer1, Claudio Santelli1, Constantin von Deuster1, Sophie Marie Peereboom1, Mareike Sauer2, Thea Fleischmann2, Nikola Cesarovic2, Christian Torben Stoeck1, and Sebastian Kozerke1

1Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland, 2Division of Surgical Research, University Hospital Zurich, Zurich, Switzerland

The IDEAL signal model for hyperpolarized metabolic imaging is extended and spatiotemporal regularization and b0-map recalibration is included. The approach is tested on simulated data and in-vivo metabolic imaging data of the heart. Allowing variable b0-fields and including sparsity regularization signal leakage and ghosting can be significantly reduced (average reduction of root-mean-square error (RMSE) by 16% and 30%). Spatial and temporal regularization of the metabolite intensities considerably improved accuracy of the estimate in terms of RMSE with additional reductions by 68% and 20%, respectively. Thus, the metabolic conversion of [1-13C]pyruvate into [1-13C]lactate and 13C-bicarbonate can be measured with improved accuracy.

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