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Abstract #1921

Analysis of Structural Connectivity in Parkinson's Disease using Graph Theory Analysis

Joo M. Sousa 1,2 , Rita G. Nunes 1 , Sofia Reimo 3 , Joaquim Ferreira 4 , and Hugo A. Ferreira 1

1 IBEB - Faculdade de Cincias da Universidade de Lisboa, Lisbon, Portugal, 2 FCT - NOVA University of Lisbon, Almada, Setubal, Portugal, 3 Neurologial Imaging Department, Centro Hospitalar Lisboa Norte - Hospital de Santa Maria, Lisbon, Portugal, 4 Clinical Pharmacology Unit, Instituto de Medicina Molecular and Laboratory of Clinical Pharmacology, Lisbon, Portugal

In this work we compared structural connectivity metrics derived from diffusion data of Parkinsons Disease (PD) subjects and a control group. As well as standard analysis of Fractional Anisotropy (FA) and Mean Diffusivity (MD) Diffusion Tensor measures, Graph Theory (GT) analysis was employed. Detected differences in FA and MD were consistent with previous work, while connectivity metrics derived from GT were able to detect significant changes in further areas also known to be involved in PD. A new framework for exploring connectivity metrics as biomarkers for PD has been proposed which may offer novel insights into the disease.

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