MRI supervised and unsupervised classification of Parkinson’s disease and multiple system atrophy

Patrice Péran, Gaetano Barbagallo, Federico Nemmi, Maria Sierra, Monique Galitzky, Anne Pavy-Le Traon, Pierre Payoux, Wassilios G. Meissner, Olivier Rascol
Mov Disord.. 2018-02-23; 33(4): 600-608
DOI: 10.1002/mds.27307

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1. Mov Disord. 2018 Apr;33(4):600-608. doi: 10.1002/mds.27307. Epub 2018 Feb 23.

MRI supervised and unsupervised classification of Parkinson’s disease and
multiple system atrophy.

Péran P(1), Barbagallo G(2), Nemmi F(1), Sierra M(3), Galitzky M(4), Traon
AP(5)(6), Payoux P(1), Meissner WG(7)(8)(9), Rascol O(1)(10).

Author information:
(1)ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS,
France.
(2)Institute of Neurology, University Magna Graecia, Catanzaro, Italy.
(3)Neurology Service, University Hospital Marqués de Valdecilla and Centro de
Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED),
Santander, Spain.
(4)Centre d’Investigation Clinique (CIC), CHU de Toulouse, Toulouse, France.
(5)UMR Institut National de la Santé et de la Recherche Médicale 1048, Institut
des Maladies Métaboliques et Cardiovasculaires, Toulouse, France.
(6)Department of Neurology and Institute for Neurosciences, University Hospital
of Toulouse, Toulouse, France.
(7)Service de Neurologie, CHU Bordeaux, Bordeaux, France.
(8)Univ. de Bordeaux, Institut des Maladies Neurodégénératives, UMR 5293,
Bordeaux, France.
(9)CNRS, Institut des Maladies Neurodégénératives, UMR 5293, Bordeaux, France.
(10)Université de Toulouse 3, CHU de Toulouse, INSERM, Centre de Reference AMS,
Service de Neurologie et de Pharmacologie Clinique, Centre d’Investigation
Clinique CIC1436, Réseau NS-Park/FCRIN et Centre of excellence for
neurodegenerative disorders (COEN) de Toulouse, Toulouse, France.

BACKGROUND: Multimodal MRI approach is based on a combination of MRI parameters
sensitive to different tissue characteristics (eg, volume atrophy, iron
deposition, and microstructural damage). The main objective of the present study
was to use a multimodal MRI approach to identify brain differences that could
discriminate between matched groups of patients with multiple system atrophy,
Parkinson’s disease, and healthy controls. We assessed the 2 different MSA
variants, namely, MSA-P, with predominant parkinsonism, and MSA-C, with more
prominent cerebellar symptoms.
METHODS: Twenty-six PD patients, 29 MSA patients (16 MSA-P, 13 MSA-C), and 26
controls underwent 3-T MRI comprising T2*-weighted, T1-weighted, and diffusion
tensor imaging scans. Using whole-brain voxel-based MRI, we combined gray-matter
density, T2* relaxation rates, and diffusion tensor imaging scalars to compare
and discriminate PD, MSA-P, MSA-C, and healthy controls.
RESULTS: Our main results showed that this approach reveals multiparametric
modifications within the cerebellum and putamen in both MSA-C and MSA-P patients,
compared with PD patients. Furthermore, our findings revealed that specific
single multimodal MRI markers were sufficient to discriminate MSA-P and MSA-C
patients from PD patients. Moreover, the unsupervised analysis based on
multimodal MRI data could regroup individuals according to their clinical
diagnosis, in most cases.
CONCLUSIONS: This study demonstrates that multimodal MRI is able to discriminate
patients with PD from those with MSA with high accuracy. The combination of
different MR biomarkers could be a great tool in early stage of disease to help
diagnosis. © 2018 International Parkinson and Movement Disorder Society.

© 2018 International Parkinson and Movement Disorder Society.

DOI: 10.1002/mds.27307
PMID: 29473662

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