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Abstract #0182

CMR-footprinting: Quantifying tissue parameters with clinical pulse sequence simulations improves measurement accuracy - an example with MOLLI T1 mapping

Christos G. Xanthis 1,2 , Sebastian L. Bidhult 1 , Georgios Kantasis 1,2 , Mikael Kanski 1 , Einar Heiberg 1,3 , Hkan Arheden 1 , and Anthony H. Aletras 1,2

1 Cardiac MR group Lund, Dept. of Clinical Physiology, Lund University, Lund, Skne, Sweden, 2 Department of Computer Science and Biomedical Informatics, University of Thessaly, Lamia, Lamia, Greece, 3 Department of Biomedical Engineering, Faculty of Engineering, Lund University, Lund, Skne, Sweden

MR simulations have been used in a limited scope in the past. In this study, we propose CMR-footprinting, a new method showing how quantitative CMR with clinical pulse sequences can be improved by comparing the signals acquired from the MRI scanner to the entire pool of possible outcomes that are produced by massively parallel MRI simulations of the identical pulse sequence for different tissue types. A MOLLI example was used and CMR-footprinting demonstrated overall T1 accuracy improvement and good performance even for long T1s with a zero seconds pause.

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