Determination of diffusion weighted magnetic resonance imaging based biomarkers of mild cognitive impairment in parkinson's disease

Abstract

Parkinson’s Disease (PD) results in structural changes on white matter (WM) of the brain, creating cognitive deficits in addition to motor problems generally ending up with Parkinson’s disease dementia (PDD). Mild cognitive impairment (MCI) is the middle stage of this cognitive decline. There is a need for finding non-invasive biomarkers for early diagnosis of PD-MCI. In this study, 27 cognitively intact PD (PDCI), 32 PD-MCI and 18 healthy controls (HC) were included to assess the structural differences. Diffusion weighted magnetic resonance images (DW-MRI) were obtained at a Philips 3T clinical scanner. Fractional anisotropy (FA) and mean diffusivity (MD) maps were estimated from DW-MRI via FMRIB Software Library (FSL) tools. Mean FA and MD values were calculated at regions of Johns Hopkins University (JHU) 81 WM atlas and Montreal Neurological Institute (MNI) atlas. For each region, a Kruskal Wallis test was applied to detect statistically significantly FA or MD differences between the three subject groups, followed by a Mann Whitney rank sum test for pairwise comparisons. FA and MD maps were also fed into tract based spatial statistics (TBSS) tool of FSL and permutation tests were applied. Region based results showed that mean FA and MD values significantly differed in some WM regions mostly between PD-MCI and HC groups. TBSS results showed that there was a statistically significant difference between PD-MCI and HC FA maps at all of the regions assessed. Less number of regions had significant FA differences between PD-MCI and PD-CI groups, but no regions were found to be different between PD-CI and HC. The results obtained with this study may contribute into an early detection of PD-MCI.|Keywords : Parkinson’s disease, mild cognitive impairment, diffusion weighted magnetic resonance imaging.