SANDI: A compartment-based model for non-invasive apparent soma and neurite imaging by diffusion MRI

Marco Palombo,Andrada Ianus,Michele Guerreri,Daniel Nunes,Daniel C Alexander,Noam Shemesh,Hui Zhang

doi:10.1016/j.neuroimage.2020.116835

Marco Palombo, Andrada Ianus + Show 5 more

Open Access

https://doi.org/10.1016/j.neuroimage.2020.116835

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Journal: NeuroImage	Publication Date: Apr 11, 2020
Citations: 166	License type: cc-by

Affiliation: University College London, Champalimaud Foundation

Abstract

This work introduces a compartment-based model for apparent cell body (namely soma) and neurite density imaging (SANDI) using non-invasive diffusion-weighted MRI (DW-MRI). The existing conjecture in brain microstructure imaging through DW-MRI presents water diffusion in white (WM) and gray (GM) matter as restricted diffusion in neurites, modelled by infinite cylinders of null radius embedded in the hindered extra-neurite water. The extra-neurite pool in WM corresponds to water in the extra-axonal space, but in GM it combines water in the extra-cellular space with water in soma. While several studies showed that this microstructure model successfully describe DW-MRI data in WM and GM at b ≤ 3,000 s/mm2 (or 3 ms/μm2), it has been also shown to fail in GM at high b values (b≫3,000 s/mm2 or 3 ms/μm2). Here we hypothesise that the unmodelled soma compartment (i.e. cell body of any brain cell type: from neuroglia to neurons) may be responsible for this failure and propose SANDI as a new model of brain microstructure where soma of any brain cell type is explicitly included. We assess the effects of size and density of soma on the direction-averaged DW-MRI signal at high b values and the regime of validity of the model using numerical simulations and comparison with experimental data from mouse (bmax = 40,000 s/mm2, or 40 ms/μm2) and human (bmax = 10,000 s/mm2, or 10 ms/μm2) brain. We show that SANDI defines new contrasts representing complementary information on the brain cyto- and myelo-architecture. Indeed, we show maps from 25 healthy human subjects of MR soma and neurite signal fractions, that remarkably mirror contrasts of histological images of brain cyto- and myelo-architecture. Although still under validation, SANDI might provide new insight into tissue architecture by introducing a new set of biomarkers of potential great value for biomedical applications and pure neuroscience.

Highlights

Mapping brain microstructure noninvasively using diffusionweighted MRI (DW-MRI) remains a formidable challenge due to the complexity of the underlying constituents and the relatively featureless diffusion-driven signal decay
These findings are in agreement with other recent works that have challenged the validity of the standard model and its derived variants (like spherical mean technique (Kaden et al, 2016)), and showed that factors not considered by the underlying microstructural models, such as intercomponent and intracompartmental kurtosis, may cause misestimation of the model parameters (Henriques et al, 2019a; Jespersen et al, 2019)
We propose a new microstructure model based on three non-exchanging compartments that explicitly includes the soma contribution to the intra-cellular signal as a pool of water diffusing in restricted geometries of non-zero size, i.e. not a dot-compartment (Panagiotaki et al, 2012; Veraart et al, 2019; Tax et al, 2019), but rather a restricted water pool, whose MR signal has a specific b and td dependence (i.e. Eq (8)) (Fig. 1b)

Summary

Introduction

Mapping brain microstructure noninvasively using diffusionweighted MRI (DW-MRI) remains a formidable challenge due to the complexity of the underlying constituents and the relatively featureless diffusion-driven signal decay. This work introduces a biophysical model incorporating for the first time soma size and density in addition to neurite density, thereby enabling their joint estimation non-invasively using DW-MRI and a model-based approach. The model is motivated by recent studies that suggest the standard model of neural tissue microstructure (Jespersen et al, 2007; Zhang et al, 2012; Fieremans et al, 2011; Kaden et al, 2016; Novikov et al, 2018a, 2019; Alexander et al, 2019) does not hold in GM at high b-values (McKinnon et al, 2017; Veraart et al, 2019, 2020; Palombo et al, 2018; Henriques et al, 2019a; Jespersen et al, 2019). The resulting biophysical model enables us to estimate apparent soma size and density non-invasively using DW-MRI

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