Abstract #0998

Bayesian Intravoxel Incoherent Motion Imaging to Map Perfusion in the Human Heart

Georg Spinner¹, Constantin von Deuster^1,2, Christian Torben Stoeck¹, and Sebastian Kozerke¹

¹Institute for Biomedical Engineering, ETH Zurich, Zurich, Switzerland, ²Division of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom

In vivo cardiac Intravoxel Incoherent Motion Imaging (IVIM) is particularly challenging due to low signal-to-noise ratio, cardiac and respiratory motion. To address the limitation, a spin-echo (SE) based sequence employing motion-compensated diffusion gradients during cardiac contraction was used in combination with Bayesian Shrinkage Prior (BSP) inference. In this work, parameter maps of four volunteers (two slices) are compared to standard segmented least squares (LSQ) regression. Bayesian inferred IVIM parameter maps showed reduced intra-subject variation relative to LSQ. It is concluded that the proposed method is a promising alternative to map myocardial perfusion without the need for contrast agent administration.

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