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Diffusion tensor imaging (DTI) is a useful diagnostic marker for differentiating patients with mild cognitive impairment (MCI) and Alzheimer's disease dementia (AD) from cognitively normal controls, as reported in various monocentric studies. Few monocentric studies performed DTI in individuals with subjective cognitive decline (SCD), who may be at risk of future AD. Compared to normal controls, most of these studies showed decreased fractional anisotropy (FA) and increased mean diffusivity (MD). However, multicenter studies using retrospective data reported a high vulnerability of DTI indices to nuisance variance, introduced by differences in acquisition parameters and study procedures. In the present study, we examined the stability of DTI in a large prospective multicenter cohort using identical scanning protocols and high-level standardized procedures. Furthermore, we assessed the usefulness of multicenter DTI to differentiate between individuals with SCD, MCI patients, AD patients and normal controls. N = 198 subjects from the DZNE Longitudinal Cognitive Impairment and Dementia (DELCODE) study were included in the analysis. We calculated the FA and MD indices for the baseline DTI data that was acquired across seven sites and analyzed them using tract-based spatial statistics (TBSS) and voxel-based analysis. For the latter approach, we applied partial volume correction to reduce the effect of cerebrospinal fluid contamination on grey matter MD estimates. Results will be presented at the conference. We expect to find reduced inter-site variability compared to a multicenter DTI study without harmonized acquisition parameters (European DTI study on Dementia; EDSD). Comparing the diagnostic groups, we expect to find decreased FA and increased MD indices in SCD subjects compared to normal controls, as well as in MCI and AD patients compared to SCD subjects and normal controls. The results from this study will contribute to the evaluation of DTI as a diagnostic marker at prodromal and at-risk stages of AD.
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Brueggen et al. (2017) studied this question.
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