Tract-Based Spatial Statistics of the Corpus Callosum using Different Tensor-Derived Indices

Prior work has shown that white matter fiber integrity decreases in Alzheimer’s disease (AD) and mild cognitive impairment (MCI). This integrity can be quantified using diffusion tensor imaging techniques, which describe the anisotropic water movement in the brain. It is important to identify features that can predict the chance of conversion from MCI to AD within a certain time frame. In this study we applied tract-based spatial statistics (TBSS) in order to perform this task, overcoming limitations that are commonly associated with ROI-based approaches and voxel-based morphometry (VBM). Diffusion weighted images were taken from 15 healthy controls, 15 AD patients and 17 MCI patients. 8 MCI patients remained stable during 3 year follow-up investigations (“non-converters”, MCI-nc) and 9 converted to AD (“converters”, MCI-c). Significant differences between the MCI-nc and MCI-c groups were found in a large part of the corpus callosum using fractional anisotropy (FA) and radial diffusivity. In comparison, the MCI-c group did not differ significantly from the AD group and the MCI-nc group exhibited similar measurements as the control group. These results demonstrate that, although MCI-c and MCI-nc patients were clinically similar at time of inclusion, the MCI-c group already exhibited pathologic features associated with AD. This finding could lead to more powerful techniques in the early identification of AD and thus support an earlier and more successful treatment.