Characterizing structural neural networks in de novo Parkinson disease patients using diffusion tensor imaging

Abstract

Parkinson disease (PD) can be considered as a brain multisystemic disease arising from dysfunction in several neural networks. The principal aim of this study was to assess whether large-scale structural topological network changes are detectable in PD patients who have not been exposed yet to dopaminergic therapy (de novo patients). Twenty-one drug-naïve PD patients and thirty healthy controls underwent a 3T structural MRI. Next, Diffusion Tensor Imaging (DTI) and graph theoretic analyses to compute individual structural white-matter (WM) networks were combined. Centrality (degree, eigenvector centrality), segregation (clustering coefficient), and integration measures (efficiency, path length) were assessed in subject-specific structural networks. Moreover, Network-based statistic (NBS) was used to identify whether and which subnetworks were significantly different between PD and control participants. De novo PD patients showed decreased clustering coefficient and strength in specific brain regions such as putamen, pallidum, amygdala, and olfactory cortex compared with healthy controls. Moreover, NBS analyses demonstrated that two specific subnetworks of reduced connectivity characterized the WM structural organization of PD patients. In particular, several key pathways in the limbic system, basal ganglia, and sensorimotor circuits showed reduced patterns of communications when comparing PD patients to controls. This study shows that PD is characterized by a disruption in the structural connectivity of several motor and non-motor regions. These findings provide support to the presence of disconnectivity mechanisms in motor (basal ganglia) as well as in non-motor (e.g., limbic, olfactory) circuits at an early disease stage of PD. Hum Brain Mapp 37:4500-4510, 2016. © 2016 Wiley Periodicals, Inc.

Regional and network properties of white matter function in Parkinson's disease

“…Diffusion tensor imaging (DTI) is a powerful tool to investigate microstructural alterations to the human brain in vivo. In PD, this technique has been combined with voxel‐ or region‐of‐interest (ROI)‐wise (Atkinson‐Clement, Pinto, Eusebio, & Coulon, ; Schwarz et al, ), and graph‐theoretical analyses (Aarabi et al, ; Li et al, ; Nigro et al, ; Pereira et al, ). Tract‐based spatial statistics (TBSS) is a voxel‐wise method, specifically developed to minimize the methodological pitfalls caused by misalignment and misregistration in conventional voxel‐based analyses (Smith et al, ).…”

Structural Network Analysis Using Diffusion MRI Tractography in Parkinson's Disease and Correlations With Motor Impairment

“…No differences were found between patients and HCs, whereas decreases of efficiency values have previously been shown with fMRI ( 20 – 22 ) and structural MRI ( 24 – 26 ). At the whole-brain level, differences in E glob and E loc provide a general indication of disease-associated differences in the integration and segregation capacities of the entire cerebral network.…”

Diffusion tensor imaging marks dopaminergic and serotonergic lesions in the Parkinsonian monkey

“…This is what we have observed in our double DA/5‐HT lesioned monkey model of PD, in which DTI variations were found in many brain structures. In PD patients, DTI alterations take place not only in the SN and the frontal lobe but also in other brain regions (caudate, putamen, pallidum, amygdala, and cingulate cortex) . The presence of disconnectivity mechanisms in motor as well as in nonmotor circuits is coherent with the fact that PD can be considered to be a multisystemic brain disease arising from dysfunction in several networks.…”

“…Diffusion tensor imaging (DTI) holds promise for studying abnormalities in both white matter tracts and gray matter areas . Brain diffusion parameters are altered within both the SN (where dopaminergic cell body loss takes place) and projecting structures in early and advanced PD patients. DTI studies in rodent and monkey models of PD have found alterations of diffusion parameters in the SN.…”