Estimating axial diffusivity in the NODDI model

Abstract

By analysing the diffusion MRI signal, we can infer information about the microscopic structure of the brain. Two parameters of interest - the intra-axonal axial diffusivity and fibre orientation dispersion - are potential biomarkers for very different aspects of the white matter microstructure, yet they are difficult to disentangle. The parameters covary such that, if one is not accurately accounted for, the other will be biased. In this work we use high b-value data to isolate the signal from the intra-axonal compartment and resolve any degeneracies with the extra-axonal compartment. In the high b-value regime, we then use a model of dispersed sticks to estimate the intra-axonal axial diffusivity and fibre orientation distribution on a voxelwise basis. Our results in in vivo, human data show an intra-axonal axial diffusivity of ~ 2.3 – 3 μm2/ms, where 3 μm2/ms is the diffusivity of free water at 37°C. The intra-axonal axial diffusivity is seen to vary considerably across the white matter. For example, in the corpus callosum we find high values in the genu and splenium, and lower values in the midbody. Furthermore, the axial diffusivity and orientation dispersion appear negatively correlated, behaviour which we show is consistent with the presence of fibre undulations but not consistent with a degeneracy between fanning fibres and axial diffusivity. Finally, we demonstrate that the parameter maps output from Neurite Orientation Dispersion and Density Imaging (NODDI) change substantially when the assumed axial diffusivity was increased from 1.7 to 2.5 or 3 μm2/ms.

Reproducibility of the Standard Model of diffusion in white matter on clinical MRI systems

“…The axonal water fraction f showed the largest values in regions with the most densely packed axons while f w only has large values close to the ventricles likely due to CSF partial volume. The major WM ROIs show D a values centered at ∼ 2.3µm 2 /ms for the TE=92ms data, in agreement with measurements using more extensive acquisitions involving high diffusion weighted PTE done by Dhital et al (2019), and with high b LTE (Veraart et al, 2019a), yet slightly lower than those reported by (Howard et al, 2020;Nilsson et al, 2021). Furthermore, D a > D || e in the majority of voxels, agreeing with gadolinium-based contrast experiments in the rat corpus callosum (Kunz et al, 2018), though this observation depends on the ROI and both values are generally close to each other.…”

Compartmental diffusion and microstructural properties of human brain gray and white matter studied with double diffusion encoding magnetic resonance spectroscopy of metabolites and water

“…Similar values have also been found in more model-driven analyses of conventional DWI data, which also suggest two-fold differences in axonal and dendritic intracellular diffusivities ( Novikov et al., 2018 ). A recent study that used a similar model-driven approach suggested that intra-axonal diffusivity approached the value of free diffusion, with large variations across white matter ( Howard et al., 2020 ). Estimating all contributions to the water signal from different tissue compartments provides a rather flat fitting landscape for selecting the right combination of fractions and diffusivities ( Novikov et al., 2018 , Lampinen et al., 2019 , Jelescu et al., 2016 ), making the fitting procedure for compartment-specific microscopic diffusion metrics fairly unstable.…”

Diffusion MRI Anisotropy in the Cerebral Cortex is Determined by Unmyelinated Tissue Features

“…The present results of Nissl-HA and myelin-HA in the gray matter indicate that myelinated and unmyelinated neurites affect these two components of anisotropy in different ways, consistent with recent theoretical work 11 ( Figure 6, SI Figure 11 ). Such information might potentially be used in biophysically motivated tissue models of the diffusion signal 11,59,60 . In dMRI models of white matter, it is sometimes assumed that intra-neurite axial diffusivity – i.e.…”

“…In dMRI models of white matter, it is sometimes assumed that intra-neurite axial diffusivity – i.e. the intrinsic rate of diffusion in the axoplasm parallel to the membrane - is constant 60,61 . However, in the more biologically heterogenous environment of gray matter, this assumption may not hold 11 .…”

“…The differing anatomy of particular tissue features may also hinder diffusion in specific ways, for example diffusivity in cell bodies may be low due to the high lipid content of cell organelles 62 . Recent modelling efforts in white matter have sought to simultaneously measure both variation in intra-axonal diffusivity, and variation in axon orientation dispersion 60 . Related models may prove especially important in gray matter.…”