Feasibility of axon density metrics for brain asymmetry evaluation in the UK Biobank subsample
preprint
OA: closed
CC-BY-NC-ND-4.0
Abstract
Standard diffusion MRI model with intra- and extra-axonal water pools offers a set of microstructural parameters describing brain white matter architecture. However, a non-linearity of the general model and diffusion data contamination by noise and imaging artefacts make estimation of diffusion metrics challenging. In order to develop reproducible and reliable diffusion approaches and to avoid computational model degeneracy, one needs to devise additional theoretical assumptions allowing a stable numerical implementation. As a result, it is possible to estimate intra-axonal water fraction (AWF) representing one of the important structural parameters. AWF can be treated as an indirect measure of axon density and has a strong potential as useful clinical biomarker. A few diffusion approaches such as white matter tract integrity, neurite orientation dispersion and density imaging, and spherical mean technique, allow one to evaluate AWF in the frame of their theoretical assumptions. In the present study, we considered the compatibility of axon density metrics obtained from different diffusion models and the influence of the diffusion metric on a brain asymmetry estimation in UK Biobank sample consisting of 182 subjects. We found AWF derived from a spherical mean technique is the most statistically representative measure. As a result, we revealed that brain asymmetry indecies derived from intra-axonal water fraction weakly decrease along the lifespan, reducing the left-right hemisphere difference within increased age.
My notes (saved in your browser only)
Citation neighborhood (no data yet)
We don't have any in-corpus citations linked to this paper yet. The paper's references may be in our DB but unresolved to ``paper_id`` (resolution happens at ingest when the cited DOI matches a row we already have). Run the cross-source citation reconcile pass to retry.
Source provenance
- europepmc
- last seen: 2026-05-19T01:45:01.086888+00:00
- unpaywall
- last seen: 2026-05-22T02:00:06.705733+00:00
License: CC-BY-NC-ND-4.0