Evaluating fibre orientation dispersion in white matter: Comparison of diffusion MRI, histology and polarized light imaging

Abstract

Diffusion MRI is an exquisitely sensitive probe of tissue microstructure, and is currently the only non-invasive measure of the brain's fibre architecture. As this technique becomes more sophisticated and microstructurally informative, there is increasing value in comparing diffusion MRI with microscopic imaging in the same tissue samples. This study compared estimates of fibre orientation dispersion in white matter derived from diffusion MRI to reference measures of dispersion obtained from polarized light imaging and histology.Three post-mortem brain specimens were scanned with diffusion MRI and analyzed with a two-compartment dispersion model. The specimens were then sectioned for microscopy, including polarized light imaging estimates of fibre orientation and histological quantitative estimates of myelin and astrocytes. Dispersion estimates were correlated on region – and voxel-wise levels in the corpus callosum, the centrum semiovale and the corticospinal tract.The region-wise analysis yielded correlation coefficients of r = 0.79 for the diffusion MRI and histology comparison, while r = 0.60 was reported for the comparison with polarized light imaging. In the corpus callosum, we observed a pattern of higher dispersion at the midline compared to its lateral aspects. This pattern was present in all modalities and the dispersion profiles from microscopy and diffusion MRI were highly correlated. The astrocytes appeared to have minor contribution to dispersion observed with diffusion MRI.These results demonstrate that fibre orientation dispersion estimates from diffusion MRI represents the tissue architecture well. Dispersion models might be improved by more faithfully incorporating an informed mapping based on microscopy data.

Local volume fraction distributions of axons, astrocytes, and myelin in deep subcortical white matter

“…curved axons with varying radius) may have different relations between A A and V V than the ones modelled, but they are expected to be negligible compared to the errors previously mentioned. In contrast, no significant changes with ageing in the astrocytic fraction were reported in (Sloane et al, 2000), which agrees with our results and previous measurements of astrocyte volume fractions in the corpus callosum, the centrum semiovale and the corticospinal tract (Mollink et al, 2017). Thus, with ageing, we seem to get closer proportions of axons and astrocyes.…”

“…(Chenevert et al, 2000;Assaf et al, 2008;Jespersen et al, 2010;Xu et al, 2014;Sepehrband et al, 2015;Szczepankiewicz et al, 2016)). Additionally, combined analyses of histology and dMRI have been performed to further understand the development of certain diseases and the healthy brain (Budde and Frank, 2012;Kolasinski et al, 2012;Khan et al, 2016;Mollink et al, 2017). Information from histology can also help developing realistic in silico biomimetic phantoms of brain tissue (Cook et al, 2006;Beltrachini et al, 2015).…”

Neurite dispersion: a new marker of multiple sclerosis spinal cord pathology?

“…Future validation of our preliminary findings could include: analysis of tissue from areas beyond the spinal cord; extension of the histology to the third dimension50, 51; further confirmation from in vivo data; characterization of more complex morphological features of glial cells52; more accurate diffusion MRI signal modeling43, 53; analysis of other quantitative MRI metrics (such as those from relaxometry, magnetization transfer techniques or susceptibility imaging).…”

Presymptomatic spinal cord pathology in c9orf72 mutation carriers: A longitudinal neuroimaging study

“…Furthermore, emerging diffusion imaging techniques such as neurite orientation dispersion and density imaging (NODDI) may have superior detection sensitivity and be particularly useful in detecting crossing fiber degeneration. 48,49 Our study is not without limitations. 46 Accordingly, WM atrophy, which is closely related to neurite density and is readily measurable in the cervical SC, may be a more sensitive marker of pathology than DTI metrics at the early asymptomatic stage of the disease.…”