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Flow MR fingerprinting
Author(s) -
Flassbeck Sebastian,
Schmidt Simon,
Bachert Peter,
Ladd Mark E.,
Schmitter Sebastian
Publication year - 2019
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.27588
Subject(s) - imaging phantom , steady state free precession imaging , nuclear magnetic resonance , magnetic resonance imaging , flow (mathematics) , flow velocity , biomedical engineering , chemistry , materials science , physics , mechanics , optics , radiology , medicine
Purpose To investigate the feasibility to quantify blood velocities within the magnetic resonance fingerprinting framework, while providing relaxometric maps of static tissue. Methods Bipolar gradients are inserted into an SSFP‐based MRF sequence to achieve velocity‐dependent signal phases, allowing tri‐directional time‐resolved velocity component quantification. The accuracy of both relaxometric mapping and velocity quantification was validated in vivo and in phantom studies. Results Simulations determined that even for strong cardiac cycle length variations (700–1400 ms) Flow‐MRF determines accurate velocity maps deviating <0.1% from the ground truth on average. The cardiac cycle length variability only results in reduced velocity‐to‐noise ratios. Good agreement in the velocity quantification between a standard phase–contrast cine and the Flow‐MRF sequence was reached in phantom experiments. Relaxometric phantom experiments determined mean deviations between Flow‐MRF and spin‐echo‐based reference measurements of 89 ± 25 ms / 0.8 ± 2.5 ms over the range of 630–2630 ms / 49–145 ms for T 1 / T 2 , respectively. The in vivo study of a human knee determined mean T 1 / T 2 values of 1383 ± 75 ms / 26 ± 4 ms for the gastrocnemius muscle that agree with literature values. Conclusion Flow‐MRF presents a novel way of quantifying velocities while simultaneously providing relaxometric maps of static tissue and it can potentially be a viable method to accelerate the inherently long acquisition times of time‐resolved velocity quantification.