Regional and Whole-Brain Assessment of Fractional Anisotropy on Parkinson s Disease DTI-Datasets

Parkinson’s disease (PD) is one of the most common neurodegenerative diseases and grows progressively worse with time. Diffusion Tensor Imaging (DTI) is a useful advanced technique employed to facilitate the differential diagnosis, which enables diffusion to be measured in multiple directions. The objective of this study is to investigate fractional anisotropy (FA) and its differences between PD patients and healthy controls (HC) for both regional and whole-brain analysis. In the regional study, three major parts of the basal ganglia loop mostly damaged in PD have been assessed. Method The dataset contains diffusion MR images of 27 PD patients and 26 age-, sex-, and education-matched HC. Standard Atlases for specific regions was then transformed non-linearly into the diffusion space of 53 subjects’ brains for assessing FA images. The method used a General Linear Model to summarize the global differences between Tract-Based Spatial Statistics (TBSS) FA skeleton images. Also, an independent unpaired t-test applied to check the differential diagnosis in Substantia Nigra (SN), Thalamus and Caudate of two groups’ mean FA measurements.Results We found that PD patients represent lower fractional anisotropy in SN (p = 0.012902) and Thalamus (p = 0.016155), and higher fractional anisotropy in Caudate (p = 0.027077) compared to HC. In contrast, no statistically significant results were observed from the TBSS analysis of FA skeleton images (after applying TFCE).Conclusions Regardless of some restrictions, DTI seems a sensitive method to study PD related changes. FA in the studied regions is an acceptable indicator not only to identify PD patients but also for PD progression. The results reveal that the reduction of anisotropy in SN and Thalamus reflects the loss of integrity of fibers of the studied regions of the brain. This suggests DTI measures might improve discrimination methods to identify PD Patients correctly in the early stages of the disease.