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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