↓ Skip to main content

Can neuroimaging predict dementia in Parkinson’s disease?

Overview of attention for article published in Brain, August 2018
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

news
1 news outlet
twitter
82 X users
facebook
1 Facebook page
reddit
1 Redditor

Citations

dimensions_citation
57 Dimensions

Readers on

mendeley
188 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Can neuroimaging predict dementia in Parkinson’s disease?
Published in
Brain, August 2018
DOI 10.1093/brain/awy211
Pubmed ID
Authors

Juliette H Lanskey, Peter McColgan, Anette E Schrag, Julio Acosta-Cabronero, Geraint Rees, Huw R Morris, Rimona S Weil

Abstract

Dementia in Parkinson's disease affects 50% of patients within 10 years of diagnosis but there is wide variation in severity and timing. Thus, robust neuroimaging prediction of cognitive involvement in Parkinson's disease is important: (i) to identify at-risk individuals for clinical trials of potential new treatments; (ii) to provide reliable prognostic information for individuals and populations; and (iii) to shed light on the pathophysiological processes underpinning Parkinson's disease dementia. To date, neuroimaging has not made major contributions to predicting cognitive involvement in Parkinson's disease. This is perhaps unsurprising considering conventional methods rely on macroscopic measures of topographically distributed neurodegeneration, a relatively late event in Parkinson's dementia. However, new technologies are now emerging that could provide important insights through detection of other potentially relevant processes. For example, novel MRI approaches can quantify magnetic susceptibility as a surrogate for tissue iron content, and increasingly powerful mathematical approaches can characterize the topology of brain networks at the systems level. Here, we present an up-to-date overview of the growing role of neuroimaging in predicting dementia in Parkinson's disease. We discuss the most relevant findings to date, and consider the potential of emerging technologies to detect the earliest signs of cognitive involvement in Parkinson's disease.

X Demographics

X Demographics

The data shown below were collected from the profiles of 82 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 188 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 188 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 29 15%
Researcher 29 15%
Student > Bachelor 19 10%
Student > Master 18 10%
Other 9 5%
Other 30 16%
Unknown 54 29%
Readers by discipline Count As %
Neuroscience 39 21%
Medicine and Dentistry 33 18%
Psychology 17 9%
Engineering 9 5%
Biochemistry, Genetics and Molecular Biology 7 4%
Other 18 10%
Unknown 65 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 56. 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 24 April 2019.
All research outputs
#736,909
of 25,028,065 outputs
Outputs from Brain
#686
of 7,576 outputs
Outputs of similar age
#15,889
of 339,279 outputs
Outputs of similar age from Brain
#15
of 63 outputs
Altmetric has tracked 25,028,065 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,576 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.5. This one has done particularly well, scoring higher than 90% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 339,279 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 63 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.