Comparison of Diffusion Tensor‐Based Tractography and Quantified Brain Atrophy for Analyzing Demyelination and Axonal Loss in MS

Abstract

We combined diffusion tensor imaging (DTI) measures of the corpus callosum (CC) and the superior longitudinal fascicle (SLF) with calculation of brain atrophy in 53 patients with relapsing-remitting multiple sclerosis (MS) and 15 healthy controls, to analyze their interrelation and their correlation with disease duration and clinical impairment. The lateral ventricle volume in MS patients was increased; the fractional anisotropy in the CC was decreased as was the fiber volume. Perpendicular (in the literature also referred to as radial) diffusivity (ped), which reflects the diffusion perpendicular to the long axis of the axons within the fiber bundle, was increased in the SLF and the posterior CC, but contrary to our predictions, parallel (also called axial) diffusivity (pad) that refers to the amount of diffusion in the direction of the axon was increased, too. Brain atrophy and DTI-derived parameters were highly intercorrelated and both correlated with disease duration. Discriminant analysis showed that DTI-derived atrophy measures are superior to brain atrophy measures in classifying patients and controls. In light of our results, animal studies focusing on demyelination and axonal loss are reinterpreted.

Neuroimaging of corpus callosum in central nervous system demyelinating disorders

“…[39] A significant increase in CC's MD was observed in relapsing remitting MS, even in benign form. [40][41][42][43][44] Moreover, patterns of tract FA reduction for cognitive test, including localization of lesions in the body and splenium of the CC, only partially overlapped with T2 lesions, supporting that NAWM abnormality contributes to cognitive dysfunction. In the study by Rimkus et al [45] results showed correlation between mean diffusion and radial diffusivity, and expended disability status scale (EDSS), suggesting possible relationship between callosal demyelination and sensory motor dysfunction.…”

“…Most of recent studies showed increased ADC and reduced FA in both pathologic and NAWM. [29][30][31][32][33] Sigal et al [11] used DTI to investigate CC integrity in MS patients and age matched controls. In agreement with other studies, [15,26,28,31] MS patients had significant reduction in CC 's FA compared with control group in all subregion of CC, indicating axonal loss and dysfunction in callosal fibers.…”

On the Reliability of Diffusion Neuroimaging

“…We have tested both the deterministic and the probabilistic FT (Bayesian) to determine whether and how they allow the detection of differences of diffusion-derived parameters between relapsing-remitting MS patients and healthy controls (10 patients, 10 healthy volunteers). For that purpose, we decided to quantify the superior longitudinal fasciculus (SLF) which has already been shown to be a structure for which differences between MS patients and healthy volunteers can be determined very well using deterministic FT (Fink et al, 2009). After extracting the right and left SLF, diffusion-derived parameters such as the FA, axial diffusivity, radial diffusivity, and diffusion strength were obtained along the tracts, and average values were computed.…”

“…Whereas tumors can infiltrate or displace white matter fiber tracts, MS lesions do not necessarily influence the localization or structure of axonal fibers. Rather, the lesions and the corresponding de-and remyelinization may influence the diffusion parameters along the fibers (Fink et al, 2009). Thus, for both groups, we perform FT of bundles of interest, i.e., bundles near the tumor or bundles which can be influenced by lesions.…”

“…Moreover, methods for tract-based quantification have been developed for which parameters are computed depending on the local curvature or geodesic distance from a user-defined origin. These methods allow to automatically determine DTIderived parameters along fiber bundles and have already been used to mirror disease progression and executive function in MS (Fink et al, 2009). Probabilistic methods (Friman et al, 2006) allow for tracking in regions of low anisotropy and are also used to provide a quantitative measure of the probability of the existence of a connection between two regions.…”