Investigating white matter fibre density and morphology using fixel-based analysis

Abstract

Voxel-based analysis of diffusion MRI data is increasingly popular. However, most white matter voxels contain contributions from multiple fibre populations (often referred to as crossing fibres), and therefore voxel-averaged quantitative measures (e.g. fractional anisotropy) are not fibre-specific and have poor interpretability. Using higher-order diffusion models, parameters related to fibre density can be extracted for individual fibre populations within each voxel (‘fixels’), and recent advances in statistics enable the multi-subject analysis of such data. However, investigating within-voxel microscopic fibre density alone does not account for macroscopic differences in the white matter morphology (e.g. the calibre of a fibre bundle). In this work, we introduce a novel method to investigate the latter, which we call fixel-based morphometry (FBM). To obtain a more complete measure related to the total number of white matter axons, information from both within-voxel microscopic fibre density and macroscopic morphology must be combined. We therefore present the FBM method as an integral piece within a comprehensive fixel-based analysis framework to investigate measures of fibre density, fibre-bundle morphology (cross-section), and a combined measure of fibre density and cross-section. We performed simulations to demonstrate the proposed measures using various transformations of a numerical fibre bundle phantom. Finally, we provide an example of such an analysis by comparing a clinical patient group to a healthy control group, which demonstrates that all three measures provide distinct and complementary information. By capturing information from both sources, the combined fibre density and cross-section measure is likely to be more sensitive to certain pathologies and more directly interpretable.

The relationship between brain structure and function of very preterm infants, and the ability to predict neurodevelopmental outcomes

“…Concurrent validity has been demonstrated in 2 studies (n=168 and n=66), where poorer scores on the HNNE related to increasing severity of cerebral abnormality on structural MRI 72,80 . A systematic review examining the predictive validity of the HNNE to predict an outcome of CP report a sensitivity range of 57-86% and specificity range of 45-83% when performed before term age (<37 weeks PMA) 78,79 . This increases to a sensitivity range of 68-96% and specificity range of 52-97% when assessed in the post term period 78,81 .…”

“…A systematic review examining the predictive validity of the HNNE to predict an outcome of CP report a sensitivity range of 57-86% and specificity range of 45-83% when performed before term age (<37 weeks PMA) 78,79 . This increases to a sensitivity range of 68-96% and specificity range of 52-97% when assessed in the post term period 78,81 .…”

“…Prediction of CP and motor outcome in the preterm period is relatively poor due to the presence of early transient abnormal signs with later good outcomes causing false positives and the converse resulting in false negatives 10,77 . When neurological examination is performed before term age in preterm infants, the sensitivity for an outcome of CP is 57-86% and specificity 45-83% 78,79 . At term, neurological assessment has a sensitivity of 88% and specificity of 46% to predict structural MRI abnormalities 80 and 68-79% and 63-70% to predict CP 78,81 .…”

“…When neurological examination is performed before term age in preterm infants, the sensitivity for an outcome of CP is 57-86% and specificity 45-83% 78,79 . At term, neurological assessment has a sensitivity of 88% and specificity of 46% to predict structural MRI abnormalities 80 and 68-79% and 63-70% to predict CP 78,81 . In the post term period sensitivity and specificity range from 68-96% and 52-97% respectively 78,81 .…”

Study of human structural brain connectivity in healthy aging based on tracts

“…The most common intravoxel parameters are the fractional anisotropy, mean, axial and radial diffusivities. Using the CSD diffusion model it is possible to assess another intravoxel WM integrity parameter, AFD, that describes the density of fibers in the white matter, measured by the proportion of space occupied by the fibers aligned in each direction (RAFFELT et al, 2012(RAFFELT et al, , 2017. It is used to compare this parameter between groups, and it makes possible to evaluate the effects in each direction.…”