On the need for bundle-specific microstructure kernels in diffusion MRI

Publication date: Available online 14 December 2019Source: NeuroImageAuthor(s): Daan Christiaens, Jelle Veraart, Lucilio Cordero-Grande, Anthony N. Price, Jana Hutter, Joseph V. Hajnal, J-Donald TournierAbstractProbing microstructure with diffusion magnetic resonance imaging (dMRI) on a scale orders of magnitude below the imaging resolution relies on biophysical modelling of the signal response in the tissue. The vast majority of these biophysical models of diffusion in white matter assume that the measured dMRI signal is the sum of the signals emanating from each of the constituent compartments, each of which exhibits a distinct behaviour in the b-value and/or orientation domain. Many of these models further assume that the dMRI behaviour of the oriented compartments (e.g. the intra-axonal space) is identical between distinct fibre populations, at least at the level of a single voxel. This implicitly assumes that any potential biological differences between fibre populations are negligible, at least as far as is measurable using dMRI. Here, we validate this assumption by means of a voxel-wise, model-free signal decomposition that, under the assumption above and in the absence of noise, is shown to be rank-1. We evaluate the effect size of signal components beyond this rank-1 representation and use permutation testing to assess their significance. We conclude that in the healthy adult brain, the dMRI signal is adequately represented by a rank-1 model, implying that biological...

Source: NeuroImage - December 14, 2019 Category: Neuroscience Source Type: research