Diffusion Tensor Imaging to Characterized Early Stages of Parkinson's Disease

Parkinson's disease (PD) is characterized by several motor and cognitive symptoms reflecting the progression of the underlying pathology. The neuroanatomical basis and topography of the neurobiological processes that account for motor and cognitive impairments have not been well characterized in the early stage of PD. Diffusion tensor imaging (DTI) constitutes a non-invasive technique to evaluate the microstructural integrity of white matter (WM). The aim of this study is to evaluate the relationship between WM abnormalities and cognitive and motor conditions in early stages of PD. For this, a DTI methodology based on graph theory is implemented to describe the specific connections between different regions of gray matter (GM) and to evaluate the relationships between them. Subsequently, the anatomical connectivity measures obtained were correlated with neurocognitive and motor evaluation. In this study, all enrolled subjects (10 controls and 10 patients with PD) were examined for UPDRS score, classified by Hoehn-Yahr stage and evaluated by using magnetic resonance imaging (DTI and structural data). A method based on graph theory was implemented to quantify the anatomic connectivity between GM zones through three measures: anatomical connectivity strength (ACS), anatomical connectivity probability (ACP) and anatomical connectivity density (ACD). A correlation among UPDRS values and the decrease of ACP and ACD in PD group was identified. The study revealed that cognitive and motor decline in early stage of PD is associated with microstructural of WM damage extended to the frontal, parietal and temporal regions. DTI combined with neurocognitive tests would be a valuable biomarker for identifying cognitive impairment in PD.