Multi-compartment microscopic diffusion imaging

Neuroimage. 2016 Oct 1;139:346-359. doi: 10.1016/j.neuroimage.2016.06.002. Epub 2016 Jun 6.


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.

Keywords: Fibre crossings; Microscopic diffusion anisotropy; Neurite density; Orientation dispersion; Spherical Mean Technique (SMT); Tuberous Sclerosis Complex (TSC).

MeSH terms

  • Adult
  • Animals
  • Anisotropy
  • Brain / anatomy & histology*
  • Brain / pathology
  • Brain Mapping / methods*
  • Diffusion Magnetic Resonance Imaging*
  • Disease Models, Animal
  • Female
  • Humans
  • Image Processing, Computer-Assisted
  • Male
  • Neurites*
  • Signal Processing, Computer-Assisted
  • Tuberous Sclerosis