WHITE MATTER FRACTIONAL ANISOTROPY ANALYSIS OF BEHAVIOURAL AND COGNITIVE DYSEXECUTIVE SYNDROMES IN AMNESTIC MILD COGNITIVE IMPAIRMENT AND ALZHEIMER'S DISEASE: A MEXICAN PILOT STUDY

Abstract

Impairment in executive functions (EF) can appear early in the course of Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI). Dysexecutive syndromes can be divided into behavioural and cognitive components (1), which can coexist or occur independently, and have been linked to alterations in specific neural pathways (2), that can be analysed measuring the fractional anisotropy (FA) of white matter using Diffusion Tensor Imaging (DTI) MRI studies (3). We included 10 AD patients, 10 aMCI patients and 10 elderly controls. Behavioural disturbances were assessed using a cross-culturally adapted version of the Behavioural Dysexecutive Syndrome Inventory (1); cognitive impairment was measured using EF psychological tests. We used the FSL software to examine DTI data in 3 tesla MRI, measuring the FA of 60 white-matter tracts identified by the ICBM-DTI-81 and JHU white-matter tractography atlases (Figure 1). We analysed the statistical differences of mean FA values of tracts between groups. The associations between FA and dysexecutive disturbances were sought. There were no statistical differences between groups' age (p= 0.182), sex (p= 1.0) or academic attainment (p= 0.89) distribution; only in MMSE mean scores by group (p= 0.001). Associations between behavioral disturbances and tracts' FA values different from controls, and the significant correlation indexes between FA values and performance in EF tests are shown in Table 1. In this pilot study, we identified relationships between white-matter integrity and EF's behavioral and cognitive components. We found associations that are consistent with those reported by other authors, but some of our findings have not been reported and can't be supported by current evidence (i.e. medial lemniscus). It's advisable to include more subjects and to refine DTI data analysis in order to get better information on the micro-structural neural underpinnings of these syndromes. 1. Godefroy, O. et al. (2010). Ann. Neurol., 68, 855–864 2. Ardila, A. (2013). J. Neurol. Disord., 3. Teipel, S.J. et al. (2014). Eur. Arch. Psychiatry Clin. Neurosci., 264, 467–483. Skeletonized image of mean FA values of the studied groups.