Multi-compartment modelling of diffusion MRI signal shows TE-based volume fraction bias

Matteo Frigo (1, 2) , Mauro Zucchelli (1, 2) , Rutger H.J. Fick (3) , Samuel Deslauriers-Gauthier (1, 2) , Rachid Deriche (1, 2)

1 ATHENA - Computational Imaging of the Central Nervous System
2 UniCA - Université Côte d'Azur
3 TheraPanacea [Paris]

Diffusion MRI (dMRI) has been widely used to estimate brain tissue microstructure in-vivo.Two of the most widely used microstructural indices are the white matter (WM) andintra-cellular (IC) volume fractions (VF) [2012z,2019f]. In estimating these fractions, acommon assumption of dMRI-based signal modeling is to assume that the T2-relaxation foreach compartment is equal. However, it has been shown that this assumption is inaccurate[2018v]. Here, we characterize the bias introduced by this assumption using a generalmulti-compartmental model of the dMRI signal in three distinct scenarios:3-S0) the realistic-case, where each compartment has its T2-dependent signal at b-value 0(S0).2-S0) in which we consider only two separated S0, one for WM and one for CSF similarly to[2014j].1-S0) a single average S0 is considered for all the compartments, as commonly done indMRI.Our simulations and experiments on real data show fitting the WM and IC VF using the moresimplistic 2-S0 and 1-S0 model, a systematic bias appears that potentially alters theinterpretation of conclusions drawn from studies focusing on WM and IC VF.

Domaines: Imagerie médicale

Matteo Frigo, Mauro Zucchelli, Rutger H.J. Fick, Samuel Deslauriers-Gauthier, Rachid Deriche. Multi-compartment modelling of diffusion MRI signal shows TE-based volume fraction bias. OHBM 2020 - 26th meeting of the Organization of Human Brain Mapping, Jun 2020, Montreal, Canada. ⟨hal-02925963⟩