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.