Speaker
Matteo Cencini
(Università di Pisa)
Description
The purpose of this work is to obtain quantitative MRI maps of fat and water with a fast acquisition for musculoskeletal imaging applications. Conventional fat separation methods are based on steady-state signal models, relying either on relaxometry or chemical shift. A recent approach for parameter mapping, called magnetic resonance fingerprinting (MRF), uses transient-state acquisitions, comparing them with pre-computed simulations in search of the best match. Here, we build on recent MRF work by including a multi-component fat and water signal model. By using a full simulation, we can combine relaxometry and chemical shift fat separation within a single acquisition. We demonstrate robust fat fraction estimation, with a simultaneous T1, B1+ and B0 map. These were in good agreement with previous approaches, but achieving a significant speedup.
Primary author
Matteo Cencini
(Università di Pisa)
Co-authors
Guido Buonincontri
(PI)
Dr
Joshua Daniel Kaggie
(University of Cambridge)
Dr
Laura Biagi
(IRCCS Stella Maris)
Michela Tosetti
(PI)
Dr
Rolf Schulte
(GE Healthcare)
