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Modeling clustered activity increase in amyloid-beta positron emission tomographic images with statistical descriptors

Overview of attention for article published in Clinical Interventions in Aging, April 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (78th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

Mentioned by

news
1 news outlet

Citations

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5 Dimensions

Readers on

mendeley
23 Mendeley
Title
Modeling clustered activity increase in amyloid-beta positron emission tomographic images with statistical descriptors
Published in
Clinical Interventions in Aging, April 2015
DOI 10.2147/cia.s82128
Pubmed ID
Authors

Sepideh Shokouhi, Baxter P Rogers, Hakmook Kang, Zhaohua Ding, Daniel O Claassen, John W Mckay, William R Riddle

Abstract

Amyloid-beta (Aβ) imaging with positron emission tomography (PET) holds promise for detecting the presence of Aβ plaques in the cortical gray matter. Many image analyses focus on regional average measurements of tracer activity distribution; however, considerable additional information is available in the images. Metrics that describe the statistical properties of images, such as the two-point correlation function (S2), have found wide applications in astronomy and materials science. S2 provides a detailed characterization of spatial patterns in images typically referred to as clustering or flocculence. The objective of this study was to translate the two-point correlation method into Aβ-PET of the human brain using 11C-Pittsburgh compound B (11C-PiB) to characterize longitudinal changes in the tracer distribution that may reflect changes in Aβ plaque accumulation. We modified the conventional S2 metric, which is primarily used for binary images and formulated a weighted two-point correlation function (wS2) to describe nonbinary, real-valued PET images with a single statistical function. Using serial 11C-PiB scans, we calculated wS2 functions from two-dimensional PET images of different cortical regions as well as three-dimensional data from the whole brain. The area under the wS2 functions was calculated and compared with the mean/median of the standardized uptake value ratio (SUVR). For three-dimensional data, we compared the area under the wS2 curves with the subjects' cerebrospinal fluid measures. Overall, the longitudinal changes in wS2 correlated with the increase in mean SUVR but showed lower variance. The whole brain results showed a higher inverse correlation between the cerebrospinal Aβ and wS2 than between the cerebrospinal Aβ and SUVR mean/median. We did not observe any confounding of wS2 by region size or injected dose. The wS2 detects subtle changes and provides additional information about the binding characteristics of radiotracers and Aβ accumulation that are difficult to verify with mean SUVR alone.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 22%
Student > Ph. D. Student 3 13%
Lecturer 1 4%
Student > Doctoral Student 1 4%
Professor 1 4%
Other 3 13%
Unknown 9 39%
Readers by discipline Count As %
Medicine and Dentistry 3 13%
Neuroscience 2 9%
Nursing and Health Professions 1 4%
Agricultural and Biological Sciences 1 4%
Psychology 1 4%
Other 3 13%
Unknown 12 52%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 19 June 2015.
All research outputs
#4,836,164
of 25,374,647 outputs
Outputs from Clinical Interventions in Aging
#493
of 1,968 outputs
Outputs of similar age
#56,937
of 279,170 outputs
Outputs of similar age from Clinical Interventions in Aging
#8
of 26 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,968 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.1. This one has gotten more attention than average, scoring higher than 72% 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 279,170 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 78% of its contemporaries.
We're also able to compare this research output to 26 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.