Diffusion MRI and its Role in Neuropsychology

Abstract

Diffusion Magnetic Resonance Imaging (dMRI) is a popular method used by neuroscientists to uncover unique information about the structural connections within the brain. dMRI is a non-invasive imaging methodology in which image contrast is based on the diffusion of water molecules in tissue. While applicable to many tissues in the body, this review focuses exclusively on the use of dMRI to examine white matter in the brain. In this review, we begin with a definition of diffusion and how diffusion is measured with MRI. Next we introduce the diffusion tensor model, the predominant model used in dMRI. We then describe acquisition issues related to acquisition parameters and scanner hardware and software. Sources of artifacts are then discussed, followed by a brief review of analysis approaches. We provide an overview of the limitations of the traditional diffusion tensor model, and highlight several more sophisticated non-tensor models that better describe the complex architecture of the brain’s white matter. We then touch on reliability and validity issues of diffusion measurements. Finally, we describe examples of ways in which dMRI has been applied to studies of brain disorders and how identified alterations relate to symptomatology and cognition.

Potential of a statistical approach for the standardization of multicenter diffusion tensor data: A phantom study

“…When dealing with longitudinal studies, one must keep in mind that the software needs to be updated from time to time. These software updates may change some of the acquisition parameters unexpectedly . Therefore, the variability in FA is more likely to be the result of changes in acquisition parameters, rather than the used software version itself.…”

Prediction of age at onset in Parkinson’s disease using objective specific neuroimaging genetics based on a sparse canonical correlation analysis

“…We generated voxel-wise maps of FA, which quantifies how elongated the diffusion tensor ellipsoid is. Additionally, it is known to be sensitive to a wide range of pathologies 20 . FA maps were registered onto the common MNI space using the same procedure to process T1 MRI.…”

Effects ofSYN1Q555Xmutation on cortical gray matter microstructure

“…It estimates the complex microstructure related to dendrites and axons using a three‐compartment physiological model. The estimation of neuronal density or dispersion is of clinical interest since these aspects are related to cerebral function and can be affected in various pathologies and normal aging (Billiet et al, ; Caverzasi et al, ; Kunz et al, ; Mueller, Lim, Hemmy, & Camchong, ; Winston, ; Winston et al, ). NODDI was shown to be useful in disentangling the contribution of neurite (axons/dendrites) orientation dispersion and density that can be confounded in FA (Zhang et al, ).…”

“…It estimates the complex microstructure related to dendrites and axons using a three-compartment physiological model. The estimation of neuronal density or dispersion is of clinical interest since these aspects are related to cerebral function and can be affected in various pathologies and normal aging (Billiet et al, 2015;Caverzasi et al, 2016;Kunz et al, 2014;Mueller, Lim, Hemmy, & Camchong, 2015;Winston, 2015;Winston et al, 2014).…”