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Abstract #4523

Prediction of the Benefit of Motion-Compensated Reconstruction for Whole-Heart Coronary MRI

Jens Wetzl 1,2 , Christoph Forman 3 , Andreas Maier 1,2 , Joachim Hornegger 1,2 , and Michael O. Zenge 3

1 Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-Universitt Erlangen-Nrnberg, Erlangen, Germany, 2 Erlangen Graduate School in Advanced Optical Technologies (SAOT), Friedrich-Alexander-Universitt Erlangen-Nrnberg, Erlangen, Germany, 3 Siemens AG, Healthcare, Imaging & Therapy Systems, Magnetic Resonance, Erlangen, Germany

Respiratory motion represents a challenge in free-breathing whole-heart coronary MR angiograpy. For respiratory motion compensation, weighted iterative reconstruction aims to reconstruct a consistent sub-set of the acquired data. However, this may lead to increased sub-sampling artifacts. Motion-compensated (MoCo) reconstruction promises to overcome this by incorporating all acquired data using a motion model. Unfortunately, computation times are longer, and the resulting signal-to-noise ratio (SNR) improvement may not always justify this effort. This work proposes a method to predict the benefit of MoCo over weighted reconstruction directly after data acquisition. This prediction method was evaluated with in-vivo experiments in 15 volunteers.

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