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Fractional anisotropy patterns in non-demented Parkinson’s disease patients using hierarchical cluster analysis

H. Erostarbe, A. Inguanzo, R. Sala, A. Abos, A. Campabadal, C. Uribe, H. Baggio, Y. Compta, M. Marti, F. Valldeoriola, C. Junque, B. Segura (Barcelona, Spain)

Meeting: 2019 International Congress

Abstract Number: 1903

Keywords: Magnetic resonance imaging(MRI), Parkinsonism

Session Information

Date: Wednesday, September 25, 2019

Session Title: Neuroimaging

Session Time: 1:15pm-2:45pm

Location: Les Muses Terrace, Level 3

Objective: We aim to characterize PD subtypes using a hypothesis-free, data driven approach based on fractional anisotropy (FA) measures.

Background: Clinical variability in the Parkinson’s disease (PD) phenotype suggests the existence of disease subtypes. Previous studies evidenced the value of structural magnetic resonance imaging (MRI) and cluster analysis to find subtypes of patients based on the pattern of cortical degeneration [1]. However, the potential of other neuroimaging modalities has not been addressed.

Method: We included Diffusion MRI images from 33 healthy controls (HC) and 50 PD. We obtained registered and skeletonized FA maps from all subjects using a DTI approach with FSL. We then calculated mean FA within 20 tracts of interest from the JHU atlas [2] and performed hierarchical cluster analysis using Ward’s linkage method of the PD sample. With the identified PD subgroups, we calculated differences for each tract with the HC using a permutation based t-test. Significance threshold was set at a corrected p<0.05.

Results: Using clustering analysis, we identified 2 groups of PD patients with different FA profiles. The first group (N=20) showed alterations with respect to HC in 11 tracts (all corrected p<0.05) named bilateral cingulate gyrus, right cingulum in the hippocampal area, forceps minor, bilateral inferior longitudinal fasciculus, bilateral inferior fronto-occipital fasciculus, bilateral uncinate fasciculus and left superior longitudinal fasciculus. Whereas the second PD group (N=30) did not differ from HC in FA values.

Conclusion: Neuroimaging clustering analysis is able to detect PD subgroups based on FA values from DTI. One group with reduced white matter integrity and a second group with no manifested FA abnormalities compared to HC.

References: [1] Uribe C., Segura B., Baggio H.C., Abos A., Marti M.J., Valledeoriola F., Compta Y., Bargallo, N., Junque C. (2016). Patterns of Cortical Thinning in Nondemented Parkinson’s Disease Patients. Movement Disorders 31 (5). [2] Hua K., Zhang J., Wakana S., Jiang H., Li X., Reich D.S., Calabresi P.A., Pekar J.J., van Zijl P. C. M., Mori S. (2008). Tract Probability Maps in Stereotaxic Spaces: Analyses of White Matter Anatomy and Tract-Specific Quantification. Neuroimage 39(1): 336-347.

To cite this abstract in AMA style:

H. Erostarbe, A. Inguanzo, R. Sala, A. Abos, A. Campabadal, C. Uribe, H. Baggio, Y. Compta, M. Marti, F. Valldeoriola, C. Junque, B. Segura. Fractional anisotropy patterns in non-demented Parkinson’s disease patients using hierarchical cluster analysis [abstract]. Mov Disord. 2019; 34 (suppl 2). https://www.mdsabstracts.org/abstract/fractional-anisotropy-patterns-in-non-demented-parkinsons-disease-patients-using-hierarchical-cluster-analysis/. Accessed June 14, 2025.
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