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Magnetic resonance fingerprinting with dictionary‐based fat and water separation (DBFW MRF): A multi‐component approach
Author(s) -
Cencini Matteo,
Biagi Laura,
Kaggie Joshua D.,
Schulte Rolf F.,
Tosetti Michela,
Buonincontri Guido
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.27628
Subject(s) - fraction (chemistry) , concordance correlation coefficient , mathematics , pattern recognition (psychology) , cartesian coordinate system , artificial intelligence , computer science , chemistry , chromatography , statistics , geometry
Purpose To obtain a fast and robust fat‐water separation with simultaneous estimation of water T 1 , fat T 1 , and fat fraction maps. Methods We modified an MR fingerprinting (MRF) framework to use a single dictionary combination of a water and fat dictionary. A variable TE acquisition pattern with maximum TE = 4.8 ms was used to increase the fat–water separability. Radiofrequency (RF) spoiling was used to reduce the size of the dictionary by reducing T 2 sensitivity. The technique was compared both in vitro and in vivo to an MRF method that incorporated 3‐point Dixon (DIXON MRF), as well as Cartesian IDEAL with different acquisition parameters. Results The proposed dictionary‐based fat–water separation technique (DBFW MRF) successfully provided fat fraction, water, and fat T 1 , B 0 , and B 1+ maps both in vitro and in vivo. The fat fraction and water T 1 values obtained with DBFW MRF show excellent agreement with DIXON MRF as well as with the reference values obtained using a Cartesian IDEAL with a long TR (concordance correlation coefficient: 0.97/0.99 for fat fraction–water T 1 ). Whereas fat fraction values with Cartesian IDEAL were degraded in the presence of T 1 saturation, MRF methods successfully estimated and accounted for T 1 in the fat fraction estimates. Conclusion The DBFW MRF technique can successfully provide T 1 and fat fraction quantification in under 20 s per slice, intrinsically correcting T 1 biases typical of fast Dixon techniques. These features could improve the diagnostic quality and use of images in presence of fat.