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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