Advanced Multicompartment Diffusion MRI Models and Their Application in Multiple Sclerosis.

D.A Lakhani,J Xu,K.G Schilling,F Bagnato

doi:10.3174/ajnr.a6484

Abstract

Conventional MR imaging techniques are sensitive to pathologic changes of the brain and spinal cord seen in MS, but they lack specificity for underlying axonal and myelin integrity. By isolating the signal contribution from different tissue compartments, newly developed advanced multicompartment diffusion MR imaging models have the potential to detect specific tissue subtypes and associated injuries with increased pathologic specificity. These models include neurite orientation dispersion and density imaging, diffusion basis spectrum imaging, multicompartment microscopic diffusion MR imaging with the spherical mean technique, and models enabled through high-gradient diffusion MR imaging. In this review, we provide an appraisal of the current literature on the physics principles, histopathologic validation, and clinical applications of each of these techniques in both brains and spinal cords of patients with MS. We discuss limitations of each of the methods and directions that future research could take to provide additional validation of their roles as biomarkers of axonal and myelin injury in MS.

Highlights

The results suggest a diffusion time-dependence of neurite orientation dispersion and density imaging (NODDI)- and spherical mean technique (SMT)-derived metrics, which will provide new opportunities to optimize these methodologies for spinal cord imaging
Clinical studies show the potential for high-gradient diffusion MR imaging to differentiate tissues with different degrees of axonal pathology
There is an urgent need to discover a biometric of neurodegeneration and repair, which can be used to untangle MS disease progression before it manifests as an irreversible disability

Summary

Introduction

We appraise the current literature on the physics principles, histopathologic validation, and clinical applications of each of these techniques in both brain and spinal cord imaging of patients with MS. Further work is needed to untangle these technical challenges, and to investigate the efficacy of NODDI-derived metrics as biomarkers of neurodegeneration, by assessing the sensitivity to tissue injury and clinical measures in larger cohorts of patients followed longitudinally over time.

Results

Conclusion