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Diffusion tensor imaging in the characterization of multiple system atrophy

Overview of attention for article published in Neuropsychiatric Disease and Treatment, August 2016
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Title
Diffusion tensor imaging in the characterization of multiple system atrophy
Published in
Neuropsychiatric Disease and Treatment, August 2016
DOI 10.2147/ndt.s109094
Pubmed ID
Authors

Aaron Michael Rulseh, Jiri Keller, Jan Rusz, Michael Syka, Hana Brozova, Robert Rusina, Petra Havrankova, Katerina Zarubova, Hana Malikova, Robert Jech, Josef Vymazal

Abstract

Multiple system atrophy (MSA) is a rare neurodegenerative disease that remains poorly understood, and the diagnosis of MSA continues to be challenging. We endeavored to improve the diagnostic process and understanding of in vivo characteristics of MSA by diffusion tensor imaging (DTI). Twenty MSA subjects, ten parkinsonian dominant (MSA-P), ten cerebellar dominant (MSA-C), and 20 healthy volunteer subjects were recruited. Fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity maps were processed using tract-based spatial statistics. Diffusion data were additionally evaluated in the basal ganglia. A support vector machine was used to assess diagnostic utility, leave-one-out cross-validation in the evaluation of classification schemes, and receiver operating characteristic analyses to determine cutoff values. We detected widespread changes in the brain white matter of MSA subjects; however, no group-wise differences were found between MSA-C and MSA-P subgroups. Altered DTI metrics in the putamen and middle cerebellar peduncles were associated with a positive parkinsonian and cerebellar phenotype, respectively. Concerning clinical applicability, we achieved high classification performance on mean diffusivity data in the combined bilateral putamen and middle cerebellar peduncle (accuracy 90.3%±9%, sensitivity 86.5%±11%, and specificity 99.3%±4%). DTI in the middle cerebellar peduncle and putamen may be used in the diagnosis of MSA with a high degree of accuracy.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 15%
Student > Doctoral Student 4 15%
Student > Bachelor 2 8%
Researcher 2 8%
Professor > Associate Professor 2 8%
Other 6 23%
Unknown 6 23%
Readers by discipline Count As %
Neuroscience 8 31%
Psychology 4 15%
Medicine and Dentistry 3 12%
Engineering 2 8%
Business, Management and Accounting 1 4%
Other 2 8%
Unknown 6 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 August 2016.
All research outputs
#17,285,668
of 25,374,647 outputs
Outputs from Neuropsychiatric Disease and Treatment
#1,901
of 3,132 outputs
Outputs of similar age
#252,529
of 381,036 outputs
Outputs of similar age from Neuropsychiatric Disease and Treatment
#75
of 102 outputs
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