NEW METHODOLOGIES FOR DATA ANALYSIS OF DIFFUSION WEIGHTED MAGNETIC RESONANCE IMAGING

Abstract

Diffusion tensor imaging (DTI) is a non-invasive quantitative method of characterizing tissue micro-structure. Diffusion imaging attempts to characterize the manner by which the water molecules within a particular location move within a given amount of time. The advantage of this modality lies in the fact that the changes in water diffusion at each direction, produced by alterations in brain biochemistry, can be measured as the Apparent Diffusion coefficient (ADC). Measurement of the diffusion tensor (D) within a voxel enables the mobility of water to be characterized along orthotropic axes, allows a macroscopic voxel-averaged description of fiber structure, orientation and fully quantitative evaluation of the microstructural features of healthy and diseased tissue.

The single tensor model is incapable of resolving multiple fiber orientations within an individual voxel. This shortcoming of the tensor model stems from the fact that the tensor possesses only a single orientational maximum. At the millimeter-scale resolution typical of DTI, the volume of cerebral white matter containing such intravoxel orientational heterogeneity (IVOH) may be considerable given the widespread divergence and convergence of fascicles. Several authors reported this non-mono-exponential behavior for the diffusion-induced attenuation in brain tissue in water and NAA signals.