Mapping track density changes in nigrostriatal and extranigral pathways in Parkinson's disease

peer reviewedHighlights First whole-brain probabilistic tractography study in Parkinson's disease High quality diffusion-weighted images (120 gradient directions, b = 2500 s/mm2) Voxel-based group analysis comparing early-stage patients and controls Abnormal reconstructed track density in the nigrostriatal pathway and brainstem Track density also increased in limbic and cognitive circuits

Comparison of brain functional connectivity methods for the diagnosis of Parkinson’s disease using resting state fMRI

Background In the absence of validated biomarkers, the early diagnosis of Parkinson’s disease (PD), the second most common neurodegenerative disorder worldwide [1], is challenging and is prone to low accuracy [2]. Recent evidence suggests that the average pattern of functional connectivity (FC) between the basal ganglia and cerebral cortex assessed in the resting state using functional magnetic resonance imaging (rs-fMRI) might discriminate between mild PD and healthy controls with 85% overall accuracy [3]. Goal We will test if this finding can be replicated in our population. We will also compare the diagnosis accuracy of this approach, which depicts an average pattern of connectivity during the whole scanning period, with that of dynamic FC that investigates the spontaneous fluctuations of the pattern of connectivity over the scanning period [4]. Methods We are currently processing and analyzing rs-fMRI data prospectively acquired on a 3T MRI in 39 patients with PD (mean disease duration 5.4 years; mean Hoehn and Yahr stage 1.5) and 39 healthy controls matched for age, gender and levels of education. For dynamic FC we will compare two different methods [4], one that use slice-time windows to capture brain dynamics with another that captures spatial co-activation patters (CAPs) at specific time points. Conclusion The selected methods will be further validated in a new cohort of de novo drug-naïve PD patients. [1] Tessitore, A., et al. Sensorimotor connectivity in Parkinson’s disease: the role of functional neuroimaging. Frontiers in neurology 5 (2014). [2] Adler et al. Low clinical diagnostic accuracy of early vs advanced Parkinson disease. Clinicopathologic study. Neurology 2014;83:406–412 [3] Szewczyk-Krolikowski, K., et al. Functional connectivity in the basal ganglia network differentiates PD patients from controls. Neurology 83.3 (2014): 208-214. [4] Hutchison, M., et al. Dynamic functional connectivity: promise, issues, and interpretations. Neuroimage 80 (2013): 360-378

Contribution of four lifelong factors of cognitive reserve on late cognition in normal aging and Parkinson’s disease

Introduction. Cognitive reserve (CR) was proposed to explain how individual differences in brain function help to cope with the effects of normal aging and neurodegenerative diseases. Education, professional solicitations, engagement in leisure and physical activities across the lifetime are considered as major determinants of this reserve. Method. Using multiple linear regression analyses, we tested separately in healthy elderly and Parkinson's disease (PD) populations to what extent cognitive performance in several domains was explained by (1) any of these four environmental lifespan variables ; (2) demographic and clinical variables (age, gender, depression score and, for the PD group, duration of disease and dopaminergic drugs). We also tested for an interaction, if any, between these lifespan variables and brain pathology indexed by global atrophy measured from high-resolution anatomical magnetic resonance imaging. Results. Age was negatively associated with cognitive performance in the PD group. In healthy elderly participants, we observed significant positive associations between cognitive performance and 1) education, 2) leisure activities, 3) professional solicitation (decisional latitude). Furthermore, participants with greater brain atrophy benefited more from CR. In PD patients, education and professional solicitations contributed to cognitive performance but to a lesser extent than in controls. CR factors modulated the relationship between cognition and brain atrophy only in patients with a slight or moderate brain atrophy. Conclusions. Education is the CR factor that contributed the most to late cognitive functioning in both groups, closely followed by leisure activity in normal aging and professional solicitations in PD. Our results also provide evidence suggesting that the effects of CR does not express similarly in normal aging and PD. From a broader perspective, these results seem to indicate that CR factors the most consistently practiced across lifespan (education and professional solicitation) are those that are the more strongly associated to late cognitive efficiency