Efficient performance analysis and optimization of transient-state
sequences for multi-parametric MRI
In transient-state multi-parametric MRI sequences such as MR-STAT, MR
Fingerprinting, or Hybrid-state imaging, the flip angle pattern of the
RF excitation varies over the sequence. This gives considerable freedom
to choose an optimal pattern of flip angles. For pragmatic reasons, most
optimization methodologies choose for a single-voxel approach, i.e.
without taking the spatial encoding scheme into account.
Particularly in MR-STAT, the context of spatial encoding is important.
So we present a methodology, called BLAKJac, that is sufficiently fast
to optimize a sequence in the context of a predetermined phase-encoding
pattern. Based on MR-STAT acquisitions and reconstructions, we show that
sequences optimized using BLAKJac lead to better results than
conventional single-voxel optimized sequences. In addition, BLAKJac
provides analytical tools that give insights in the performance of the
sequence at very limited computation time.
Our experiments are based on MR-STAT, but the theory is equally valid
for other transient-state multi-parametric methods.