Commentary on “Microanisotropy imaging: quantification of microscopic diffusion anisotropy and orientation of order parameter by diffusion MRI with magic-angle spinning of the q-vector”

Abstract

In their recent paper, Lasic et al. describe a parameter termed μFA (microscopic fractional anisotropy) that quantifies microscopic anisotropy independently of macroscopic anisotropy [1]. Specifically such a microstructural parameter makes it possible to detect and characterize anisotropic domains even if they are organized in a macroscopically (i.e., at the level of the voxel) isotropic way—essentially decoupling macroscopic and microscopic anisotropy. Their method is based on the combination of two types of diffusion measurements, a powder average experiment and magic angle spinning of the q vector: The powder average experiment uses a traditional single pulsed field gradient or PGSE acquisition, where the signal along a large number of diffusion directions is averaged, thus emulating an isotropic preparation of the sample. The magic angle spinning of the q vector, the so-called q-MAS, is an approach for isotropic diffusion weighting recently introduced by the same group [2]. A similar parameter of microscopic anisotropy, termed fractional eccentricity (FE), but relying on double pulsed field gradient (dPFG) diffusion experiments was introduced by us recently in Jespersen et al. [3]. In it we extended previous work on indices of microscopic anisotropy in the long diffusion time limit proposed by Lawrenz et al. [4]. The FE terminology was motivated by the existing nomenclature in the dPFG field. However, a simple argument shows that the two metrics μFA and FE are in fact identical in systems consisting of identical pores. First, when all domains are coherently aligned along one direction, it was shown in Jespersen et al. [3] that FE=FA, and similarly in Lasic et al. [1] that μFA=FA: thus FE=μFA in such a system. Secondly, both metrics are independent of the pore orientation distribution function, so both FE and μFA are unaffected when reorganizing the domains to match any anisotropic distribution. Hence the identity FE=μFA is conserved. Nevertheless, a number of observations concerning differences and similarities must be made. Clearly, both approaches presuppose the existence of compartments (pores), in which the bulk of the spins will remain during the relevant time of observation. For the q-MAS approach, this is the duration of the q-MAS modulation, 40 ms in Lasic et al. [1]. For the dPFG approach, the relevant time is the sum of diffusion and exchange times from the onset of the first field pulse to the end of the last field pulse, which was 43 ms in Jespersen et al. [3]. These (comparable) numbers put constraints on the exchange time/permeability of the compartments. Moreover, both approaches involve non-conventional diffusion sequences, requiring programming of gradient modulation waveforms. The qMAS approach requires the combination of two different types of diffusion experiments, and both approaches use data acquired along several diffusion directions. The dPFG experiment can be used to extract also the diffusion tensor. The q-MAS approach assumes that diffusion in the individual pores is Gaussian. This can be a good approximation for example when diffusion weighting is not too strong and diffusion times are large. However, another requirement of the qMAS analysis approach is that the diffusion coefficients in the individual pores are time independent, a condition which may be challenging to balance against the necessity for the spins to experience the pore boundaries, the very source of the μFA. On the other hand, this is presumably a good approximation for the extracellular space in the long diffusion time limit, still assuming no exchange between the intraand extracellular space. The Gaussian approximation can be accurate also when diffusion times are very small, but in this regime μFA will be vanishing as the effect of the confinement is negligible. The dPFG approach to microscopic anisotropy requires long mixing times,