The variability of MR axon radii estimates in the human white matter

Abstract

The noninvasive quantification of axonal morphology is an exciting avenue for gaining understanding of the function and structure of the central nervous system. Accurate non‐invasive mapping of micron‐sized axon radii using commonly applied neuroimaging techniques, that is, diffusion‐weighted MRI, has been bolstered by recent hardware developments, specifically MR gradient design. Here the whole brain characterization of the effective MR axon radius is presented and the inter‐ and intra‐scanner test–retest repeatability and reproducibility are evaluated to promote the further development of the effective MR axon radius as a neuroimaging biomarker. A coefficient‐of‐variability of approximately 10% in the voxelwise estimation of the effective MR radius is observed in the test–retest analysis, but it is shown that the performance can be improved fourfold using a customized along‐tract analysis.

Dissecting whole-brain conduction delays through MRI microstructural measures

“…The first and fundamental determinant is the axonal diameter, as in myelinated axons conduction velocity is proportional to the inner (i.e., without accounting for the myelin sheath) diameter. Using diffusion MRI and ultra-high gradients (Huang et al, 2020;Jones et al, 2018), it is possible to estimate the axonal diameter in the human brain (at least for the largest ones), and recent studies have shown measures in line with the underlying histology (Huang et al, 2020;Veraart et al, 2020) and with good scan-rescan reliability (Veraart et al, 2021). Another important determinant of conduction velocity is the myelin content.…”

Axon Diameter Measurements using Diffusion MRI are Infeasible

“…Finally, in section 2.5, we have shown how a distribution of diameters projects itself onto a single fitted effective diameter. The effective diameter can be estimated reliably using advanced hardware and dedicated sequences [52,53] but still display the same insensitivity to small and medium axons and unresolvability of distribution shape. Nevertheless, the effective diameter is correlated with the biggest axons and differences in these biggest axons might be relevant in some cases such as pathology [53].…”

“…We suspect that previous, apparently plausible results arise from some combination of effects outside of the model assumptions that are projecting themselves onto the model parameters in a complex way. Admittedly, some parameters can be reliably fitted to the data, such as the effective diameter [52,53], if an appropriate sequence and method are used to suppress the extra-axonal signal contribution. As we have demonstrated, In the simulations, we considered that the typical white matter SNR from an MR acquisition using Connectom gradients was driven only by the intra-axonal compartment.…”

“…In its current state, the metric d eff cannot differentiate fundamentally different situations such as a small diameter increase of all axons versus a large diameter increase from a small proportion of the axon population. In pathological cases where the very few extra-large axons (or possibly glial cells) are affected, the effective diameter might provide additional information [53]. However, for many other purposes that require the full distribution, in particular for neuronal modeling, it is unsuitable.…”

“…Evidence points toward d eff from eq. 2 being an accurate description of the "averaging" process of a typical dMRI sequence over a distribution of axons in the presence of no other signal [47,52] and a recent in-vivo study [53] from voxels containing millions of axons. However, when comparing the d eff metric between different ROIs or subjects, it becomes impossible to distinguish between situations such as a small global shift toward larger axons or a thicker distribution tail.…”