Diffusion-relaxation scattered MR signal representation in a multi-parametric sequence

Abstract

This work focuses on obtaining a magnetic resonance imaging (MRI) signal representation that accounts for a longitudinal T₁ and transverse T₂^⋆ relaxations while at the same time integrating directional diffusion in the context of scattered multi-parametric acquisitions, where only a few diffusion gradient directions and b-values are available for each pair of echo and inversion times. The method is based on the three-dimensional simple harmonic oscillator-based reconstruction and estimation (SHORE) representation of the diffusion signal, which enables the estimation of the orientation distribution function and the retrieval of various quantitative indices such as the generalized fractional anisotropy or the return-to-the-origin probability while simultaneously resolving for T₁ and T₂^⋆ relaxation times. Our technique, the Relax-SHORE, has been tested on both in silico and in vivo diffusion-relaxation scattered MR data. The results show that Relax-SHORE is accurate in the context of scattered acquisitions while guaranteeing flexibility in the diffusion signal representation from multi-parametric sequences.

Keywords: Brain; Diffusion MRI; Diffusion-relaxation; Microstructure; Multi-parametric sequence.