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Differentiation of multiple system atrophy from Parkinson's disease by structural connectivity derived from probabilistic tractography.

ABSTRACT: Recent studies combining diffusion tensor-derived metrics and machine learning have shown promising results in the discrimination of multiple system atrophy (MSA) and Parkinson's disease (PD) patients. This approach has not been tested using more complex methodologies such as probabilistic tractography. The aim of this work is assessing whether the strength of structural connectivity between subcortical structures, measured as the number of streamlines (NOS) derived from tractography, can be used to classify MSA and PD patients at the single-patient level. The classification performance of subcortical FA and MD was also evaluated to compare the discriminant ability between diffusion tensor-derived metrics and NOS. Using diffusion-weighted images acquired in a 3?T MRI scanner and probabilistic tractography, we reconstructed the white matter tracts between 18 subcortical structures from a sample of 54 healthy controls, 31 MSA patients and 65 PD patients. NOS between subcortical structures were compared between groups and entered as features into a machine learning algorithm. Reduced NOS in MSA compared with controls and PD were found in connections between the putamen, pallidum, ventral diencephalon, thalamus, and cerebellum, in both right and left hemispheres. The classification procedure achieved an overall accuracy of 78%, with 71% of the MSA subjects and 86% of the PD patients correctly classified. NOS features outperformed the discrimination performance obtained with FA and MD. Our findings suggest that structural connectivity derived from tractography has the potential to correctly distinguish between MSA and PD patients. Furthermore, NOS measures obtained from tractography might be more useful than diffusion tensor-derived metrics for the detection of MSA.

SUBMITTER: Abos A

PROVIDER: S-EPMC6848175 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Differentiation of multiple system atrophy from Parkinson's disease by structural connectivity derived from probabilistic tractography.

Abos Alexandra A Baggio Hugo C HC Segura Barbara B Campabadal Anna A Uribe Carme C Giraldo Darly Milena DM Perez-Soriano Alexandra A Muñoz Esteban E Compta Yaroslau Y Junque Carme C Marti Maria Jose MJ

Scientific reports 20191111 1

Recent studies combining diffusion tensor-derived metrics and machine learning have shown promising results in the discrimination of multiple system atrophy (MSA) and Parkinson's disease (PD) patients. This approach has not been tested using more complex methodologies such as probabilistic tractography. The aim of this work is assessing whether the strength of structural connectivity between subcortical structures, measured as the number of streamlines (NOS) derived from tractography, can be use ...[more]

PMID: 31712681

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Project description:BackgroundBoth Parkinson's disease (PD) and multiple system atrophy (MSA) exhibit degeneration of brainstem serotoninergic nuclei, affecting multiple subcortical and cortical serotoninergic projections. In MSA, medullary serotoninergic neuron pathology is well documented, but serotonin system changes throughout the rest of the brain are less well characterized.ObjectivesTo use serotonin transporter [11 C]3-amino-4-(2-dimethylaminomethyl-phenylsulfaryl)-benzonitrile positron emission tomography (PET) to compare serotoninergic innervation in patients with MSA and PD.MethodsWe performed serotonin transporter PET imaging in 18 patients with MSA, 23 patients with PD, and 16 healthy controls to explore differences in brainstem, subcortical, and cortical regions of interest.ResultsPatients with MSA showed lower serotonin transporter distribution volume ratios compared with patients with PD in the medulla, raphe pontis, ventral striatum, limbic cortex, and thalamic regions, but no differences in the dorsal striatal, ventral anterior cingulate, or total cortical regions. Controls showed greater cortical serotonin transporter binding compared with PD or MSA groups but lower serotonin transporter binding in the striatum and other relevant basal ganglia regions. There were no regional differences in binding between patients with MSA-parkinsonian subtype (n = 8) and patients with MSA-cerebellar subtype (n = 10). Serotonin transporter distribution volume ratios in multiple different regions of interest showed an inverse correlation with the severity of Movement Disorders Society Unified Parkinson's Disease Rating Scale motor score in patients with MSA but not patients with PD.ConclusionsBrainstem and some forebrain subcortical region serotoninergic deficits are more severe in MSA compared with PD and show an MSA-specific correlation with the severity of motor impairments. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Dataset Information

Differentiation of multiple system atrophy from Parkinson's disease by structural connectivity derived from probabilistic tractography.

Publications

Differentiation of multiple system atrophy from Parkinson's disease by structural connectivity derived from probabilistic tractography.

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