The Relationship Between Axon Density, Myelination, and Fractional Anisotropy in the Human Corpus Callosum

Abstract

The corpus callosum serves the functional integration and interaction between the two hemispheres. Many studies investigate callosal microstructure via diffusion tensor imaging (DTI) fractional anisotropy (FA) in geometrically parcellated segments. However, FA is influenced by several different microstructural properties such as myelination and axon density, hindering a neurobiological interpretation. This study explores the relationship between FA and more specific measures of microstructure within the corpus callosum in a sample of 271 healthy participants. DTI tractography was used to assess 11 callosal segments and gain estimates of FA. We quantified axon density and myelination via neurite orientation dispersion and density imaging (NODDI) to assess intra-neurite volume fraction and a multiecho gradient spin-echo sequence estimating myelin water fraction. The results indicate three common factors in the distribution of FA, myelin content and axon density, indicating potentially shared rules of topographical distribution. Moreover, the relationship between measures varied across the corpus callosum, suggesting that FA should not be interpreted uniformly. More specific magnetic resonance imaging-based quantification techniques, such as NODDI and multiecho myelin water imaging, may thus play a key role in future studies of clinical trials and individual differences.

MICRA: Microstructural image compilation with repeated acquisitions

“…Multi-shell diffusion-weighted data were pre-processed using a custom in-house pipeline comprising tools from both the FSL ( Andersson et al., 2003 ; Andersson and Sotiropoulos, 2016 ) and MRTrix ( Veraart et al., 2016 ; Vos et al., 2017 ) software packages and in-house software. Specifically, AP- and PA-encoded images were separately denoised (MRTrix dwidenoise, Veraart et al., 2016 ) and drift corrected ( Vos et al., 2017 ), then merged (with incorporated EPI, susceptibility and motion correction; FSL topup ( Andersson et al., 2003 ) and eddy ( Andersson et al., 2016 )) corrected for gradient non-linearity distortions ( Glasser et al., 2013 ) with spatio-temporal b-value/vector tracking ( Rudrapatna et al., 2018 ), and finally corrected for Gibbs ringing artefacts (MRTrix mrdegibbs, Kellner et al., 2016 ). Subsequent processing involved computation of: (i) free-water corrected fractional anisotropy (FA), mean diffusivity (MD) and radial diffusivity (RD) maps ( Hoy et al., 2014 ) from diffusion tensor MRI using the b = 1000 s/mm 2 shell (linear least squares estimation with outlier rejection, Chang et al., 2005 ).…”

Diffusion Tensor Imaging of the Median Nerve: A Systematic Review and Meta-Analysis of Normal Values in Asymptomatic Adults and How They Change in Carpal Tunnel Syndrome

“…1 Compression of peripheral nerves leads to distortion of the axonal architecture, demyelination with or without poor remyelination, loss of the intrinsic vasculature and ultimately, brosis of the perineurial and epineurial connective tissue. 2,3 Diffusion tensor imaging (DTI) characterises tissue microstructure and generates reproducible [4][5][6][7] proxy measures of nerve 'health' which are sensitive to myelination, axon diameter, bre density and organisation [8][9][10] (Figure 1). DTI typically generates the following metrics: fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD).…”

Handedness and midsagittal corpus callosum morphology: A systematic meta-analytic evaluation

“…Consequently, it has long been suggested that inter-individual differences in callosal morphology are related to differences in functional hemispheric asymmetries (Galaburda, Rosen, & Sherman, 1990;Ringo, Doty, Demeter, & Simard, 1994;Witelson & Nowakowski, 1991). Recent neuroimaging studies in general support this notion as they have shown an association between measures of structural corpus callosum connectivity and the distribution of neuronal processing between the hemispheres (e.g., Friedrich et al, 2020;Haberling, Badzakova-Trajkov, & Corballis, 2011;Josse, Seghier, Kherif, & Price, 2008;Karolis, Corbetta, & De Schotten, 2019;Labache et al, 2020;Moffat, Hampson, & Lee, 1998;Westerhausen et al, 2006).…”