Multi-compartment microscopic diffusion imaging

Abstract

This paper introduces a multi-compartment model for microscopic diffusion anisotropy imaging. The aim is to estimate microscopic features specific to the intra- and extra-neurite compartments in nervous tissue unconfounded by the effects of fibre crossings and orientation dispersion, which are ubiquitous in the brain. The proposed MRI method is based on the Spherical Mean Technique (SMT), which factors out the neurite orientation distribution and thus provides direct estimates of the microscopic tissue structure. This technique can be immediately used in the clinic for the assessment of various neurological conditions, as it requires only a widely available off-the-shelf sequence with two b-shells and high-angular gradient resolution achievable within clinically feasible scan times. To demonstrate the developed method, we use high-quality diffusion data acquired with a bespoke scanner system from the Human Connectome Project. This study establishes the normative values of the new biomarkers for a large cohort of healthy young adults, which may then support clinical diagnostics in patients. Moreover, we show that the microscopic diffusion indices offer direct sensitivity to pathological tissue alterations, exemplified in a preclinical animal model of Tuberous Sclerosis Complex (TSC), a genetic multi-organ disorder which impacts brain microstructure and hence may lead to neurological manifestations such as autism, epilepsy and developmental delay.

Design and Validation of Diffusion MRI Models of White Matter

“…By contrast to these two approaches, the method described by (Kaden et al, 2016) based on the spherical mean technique is similar in spirit, in the sense that it factors out the fiber ODF, but it only exploits the lowest order rotational invariant and the estimation of the scalar kernel is constrained by D a,‖ = D e,‖ and by the tortuosity approximation for the extra-axonal space (Equation 6). …”

How to choose the right MR sequence for your research question at 7 T and above?

“…Differences in gradient performance between vendors may necessitate some modification to the protocol. As a general advice two-shell acquisitions could become the norm for DTI because they allow spherical mean calculations of axonal diffusion coefficients (Kaden et al, 2016b(Kaden et al, , 2016a. For situations where high spatial fidelity is desired and it is not necessary to acquire at a large number of diffusion gradient orientations then readout segmented EPI or MUSE (Chen et al, 2013) present viable options if available.…”

Assessing White Matter Microstructure in Brain Regions with Different Myelin Architecture Using MRI

“…Such approaches have been shown to reveal the underlying fibre architecture and provide microstructural parameters with improved sensitivity to pathological changes and better specificity to histological tissue properties than the more classical DTI-based metrics [51–53]. While it has been argued that a strict compartmentalization of the tissue might be an oversimplification of modelling the diffusion signal [54], several promising models have been introduced and validated by histology [9,10,55,56], although some of them require very long scan times. One of the recently introduced methods that can be achieved within clinically feasible scan times, is neurite orientation dispersion and density imaging (NODDI) [57].…”