Intra-axonal diffusivity in brain white matter

Abstract

ABSTRACT Biophysical modeling lies at the core of evaluating tissue cellular structure using diffusion‐weighted MRI, albeit with shortcomings. The challenges lie not only in the complexity of the diffusion phenomenon, but also in the need to know the diffusion‐specific properties of diverse cellular compartments in vivo. The likelihood function obtained from the commonly acquired Stejskal‐Tanner diffusion‐weighted MRI data is degenerate with different parameter constellations explaining the signal equally well, thereby hindering an unambiguous parameter estimation. The aim of this study is to measure the intra‐axonal water diffusivity which is one of the central parameters of white matter models. Estimating intra‐axonal diffusivity is complicated by (i) the presence of other compartments, and (ii) the orientation dispersion of axons. Our measurement involves an efficient signal suppression of water in extra‐axonal space and all cellular processes oriented outside a narrow cone around the principal fiber direction. This is achieved using a planar water mobility filter that suppresses signal from all molecules that are mobile in the plane transverse to the fiber bundle. After the planar filter, the diffusivity of the remaining intra‐axonal signal is measured using linear and spherical diffusion encoding. We find the average intra‐axonal diffusivity Symbol for the timing of the applied gradients, which gives Symbol when extrapolated to infinite diffusion time. The result imposes a strong limitation on the parameter selection for biophysical modeling of diffusion‐weighted MRI. Symbol. No caption available. Symbol. No caption available. HIGHLIGHTSDiffusion‐weighted planar filter was used to suppress extra‐axonal white matter compartments.The trace of intra‐axonal diffusion tensor and the intra‐axonal diffusivity were measured in the normal human brain in vivo.The traces of the intra‐ and extra‐axonal compartments were found to be very close to each other.Planar filter narrows the native axonal orientation distribution and allows estimating axonal orientation distribution.