Slice-Profile-Enabled Phase Distribution Graphs for MRI Simulation

Abstract

MRI simulation often separates two descriptions that are both essential for realistic sequence analysis: Bloch dynamics for waveform-resolved radiofrequency (RF) excitation, and phase-graph methods for coherence-pathway evolution. Extended Phase Graph (EPG) models provide pathway tracking, and Phase--Distribution Graphs (PDG) extend this idea to spatially resolved $k$-space simulation, but existing PDG formulations rely on hard-pulse RF mixing that is \emph{order-local}: the RF pulse mixes $F_n^+$, $F_n^-$, and $Z_n$ at a fixed coherence order $n$, without coupling different $k_z$ orders. This work introduces a unified Bloch-resolved PDG framework for slice-profile-aware MRI simulation. A scanner-rasterized sequence is partitioned into RF-sensitive Bloch spans and non-RF phase-graph spans. For each unique RF span, Bloch dynamics are solved on a slice grid to obtain a spatially varying propagator $R(z)$. Its Fourier coefficients $\mathcal{R}_Δ$, indexed by slice-order offset $Δ$, are compiled into the PDG state graph as sparse cross-order coupling in $k_z$. Graph growth is controlled by retaining the dominant Fourier coefficients and pruning low-contribution PDG states. This retains PDG pathway history and voxel-wise image formation while incorporating shaped slice-selective and off-resonant RF behavior. Experiments show close agreement with direct one-dimensional Bloch slice-profile evolution through repeated excitations, while retaining only a few hundred active PDG states. Image simulations further illustrate slice-position dependence, fat-suppression behavior, measured three-dimensional $B_0$ field maps, and comparison with scanner data. The proposed framework enables sequence-consistent simulation and signal formation understanding in regimes where RF physics, spatial encoding, object heterogeneity, and echo-pathway formation interact.