M(RF)2 – Improving MRF encoding speed with tailored spatiotemporal excitation patterns

Motivation: Current Magnetic Resonance Fingerprinting techniques have shown promising results but have room for improvement in terms of acquisition speed and resolution. Goal(s): Explore the potential of a new spatiotemporal encoding dimension unique to MRF, leveraging tailored spatiotemporal excitation patterns. Approach: Employ spatially and temporally varying excitation patterns to create distinct signal evolution dictionaries at different spatial locations and reconstruct using multiple subspaces. To address computational challenges, we introduce a clustering method that reduces the number of subspaces, making the problem tractable. Results: 2D reconstruction experiments demonstrate the approach's potential and show enhanced accuracy, particularly in T2 reconstruction. Impact: We propose tailored spatiotemporal excitation encoding for Magnetic Resonance Fingerprinting. By leveraging controlled excitation patterns, we create spatially varying dictionaries that enhance the encoding capabilities, allowing for faster and higher-resolution imaging.