Disrupted morphological grey matter networks in early-stage Parkinson’s disease

AbstractWhile previous structural-covariance studies have an advanced understanding of brain alterations in Parkinson's disease (PD), brain–behavior relationships have not been examined at the individual level. This study investigated the topological organization of grey matter (GM) networks, their relation to disease severity, and their potential imaging diagnostic value in PD. Fifty-four early-stage PD patients and 54 healthy controls (HC) underwent structural T1-weighted magnetic resonance imaging. GM networks were constructed by estimating interregional similarity in the distributions of regional GM volume using the Kullback–Leibler divergence measure. Results were analyzed using graph theory and network-based statistics (NBS), and the relationship to disease severity was assessed. Exploratory support vector machine analyses were conducted to discriminate PD patients from HC and different motor subtypes. Compared with HC, GM networks in PD showed a higher clustering coefficient (P = 0.014) and local efficiency (P = 0.014). Locally, nodal centralities in PD were lower in postcentral gyrus and temporal-occipital regions, and higher in right superior frontal gyrus and left putamen. NBS analysis revealed decreased morphological connections in the sensorimotor and default mode networks and increased connections in the salience and frontoparietal networks in PD. Connection matrices and graph-based metrics allowed single-subject classification of PD and HC with significant accuracy of 73.1 and 72.7%, respectively, while graph-based metrics allowed single-subject classification of tremor-dominant and akinetic–rigid motor subtypes with significant accuracy of 67.0%. The topological organization of GM networks was disrupted in early-stage PD in a way that suggests greater segregation of information processing. There is potential for application to early imaging diagnosis.</jats:p

Brain connectivity analysis of patients with Parkinson’s disease

Mestrado em Radiações Aplicadas às Tecnologias da Saúde - Ramo de especialização: Ressonância MagnéticaAtualmente existe um debate sobre “Scans Without Evidence for Dopaminergic Deficit" (SWEDD) de ser uma patologia independente ou um subtipo benigno da doença de Parkinson (DP). Neste estudo analisou-se a conectividade estrutural cerebral de 30 indivíduos saudáveis, 29 doentes com SWEDD e 29 doentes com DP, utilizando diversos softwares especializados e a teoria dos grafos para caracterizar 96 regiões de interesse. Diferentes métricas de imagem e de conectividade foram obtidas a partir de dados de imagem em ponderação T1 e de tensor de difusão. Em relação aos dados demográficos dos grupos, observaram-se diferenças estatísticas na Unified Parkinson Disease Rating Scale entre os indivíduos saudáveis (Controlo) e os doentes com DP (p=0,000) e com SWEDD (p=0,000). Na comparação Controlo vs DP, várias diferenças foram observadas em relação às métricas de imagem e de conectividade, particularmente nos núcleos da base de ambos os hemisférios. No Controlo vs SWEDD, as regiões dos lobos frontal e parietal mostraram alterações nas métricas de conectividade, particularmente o giro marginal superior e o giro parietal superior de ambos os hemisférios. Na DP vs SWEDD, foram observadas alterações de métricas de imagem e de conectividade, particularmente no polo frontal e no córtex pré-frontal anterior. Todos os resultados observados neste estudo estão de acordo com a literatura sobre mudanças observadas nas regiões relacionadas com as, mesolímbica mesocortical e nigroestriatal. Estes achados sugerem que o estudo da conectividade estrutural é um importante método para distinguir SWEDD e DP.ABSTRACT - Currently, there is an ongoing controversy about Scans Without Evidence of Dopaminergic deficit (SWEDD) being a Parkinson’s Disease (PD) lookalike disease or a benign subtype of PD. In this study the brain structural connectivity of 30 healthy subjects, 29 patients with SWEDD and 29 patients with PD was analysed, using various specialized software and graph theory to characterize the structural connectivity of 96 regions of interest. Different imaging metrics and connectivities were obtained from diffusion tensor imaging and T1 weighted data. With regard to group data, statistical differences in Unified Parkinson Disease Rating Scale (UPDRS) scores were observed between healthy subjects (Control) and PD (p=0.000) and SWEDD (p=0.000) patients. In comparing Control vs PD, several differences were observed regarding various imaging and connectivity metrics, particularly in the basal ganglia of both hemispheres. In comparing Control vs SWEDD, regions of the frontal and parietal lobes showed various connectivity metrics changes, particularly in the superior marginal gyrus and superior parietal gyrus of both hemispheres. In comparing SWEDD vs PD, various DTI-based imaging and connectivity metrics changes were observed, particularly in the frontal pole and rostral middle frontal gyrus. All results observed in this study are in agreement with the literature regarding observed changes in regions related to the nigrostriatal, mesocortical and mesolimbic pathways. These findings suggest that the study of SC is an important method in distinguishing between SWEDD and PD.info:eu-repo/semantics/publishedVersio