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Towards A Noninvasive Method for Determination of Patient-Specific Wall Strength Distribution in Abdominal Aortic Aneurysms

Overview of attention for article published in Annals of Biomedical Engineering, June 2006
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (71st percentile)

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1 policy source
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4 Wikipedia pages

Citations

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179 Dimensions

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172 Mendeley
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Title
Towards A Noninvasive Method for Determination of Patient-Specific Wall Strength Distribution in Abdominal Aortic Aneurysms
Published in
Annals of Biomedical Engineering, June 2006
DOI 10.1007/s10439-006-9132-6
Pubmed ID
Authors

Jonathan P. Vande Geest, David H. J. Wang, Stephen R. Wisniewski, Michel S. Makaroun, David A. Vorp

Abstract

The spatial distributions of both wall stress and wall strength are required to accurately evaluate the rupture potential for an individual abdominal aortic aneurysm (AAA). The purpose of this study was to develop a statistical model to non-invasively estimate the distribution of AAA wall strength. Seven parameters--namely age, gender, family history of AAA, smoking status, AAA size, local diameter, and local intraluminal thrombus (ILT) thickness--were either directly measured or recorded from the patients hospital chart. Wall strength values corresponding to these predictor variables were calculated from the tensile testing of surgically procured AAA wall specimens. Backwards-stepwise regression techniques were used to identify and eliminate insignificant predictors for wall strength. Linear mixed-effects modeling was used to derive a final statistical model for AAA wall strength, from which 95% confidence intervals on the model parameters were formed. The final statistical model for AAA wall strength consisted of the following variables: sex, family history, ILT thickness, and normalized transverse diameter. Demonstrative application of the model revealed a unique, complex wall strength distribution, with strength values ranging from 56 N/cm2 to 133 N/cm2. A four-parameter statistical model for the noninvasive estimation of patient-specific AAA wall strength distribution has been successfully developed. The currently developed model represents a first attempt towards the noninvasive assessment of AAA wall strength. Coupling this model with our stress analysis technique may provide a more accurate means to estimate patient-specific rupture potential of AAA.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 172 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 2%
United Kingdom 2 1%
Italy 2 1%
France 1 <1%
Unknown 164 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 44 26%
Student > Master 24 14%
Researcher 19 11%
Professor > Associate Professor 11 6%
Student > Bachelor 11 6%
Other 31 18%
Unknown 32 19%
Readers by discipline Count As %
Engineering 72 42%
Medicine and Dentistry 27 16%
Agricultural and Biological Sciences 7 4%
Computer Science 4 2%
Biochemistry, Genetics and Molecular Biology 3 2%
Other 13 8%
Unknown 46 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 28 February 2020.
All research outputs
#5,620,968
of 25,986,827 outputs
Outputs from Annals of Biomedical Engineering
#2
of 2 outputs
Outputs of similar age
#15,686
of 88,143 outputs
Outputs of similar age from Annals of Biomedical Engineering
#1
of 2 outputs
Altmetric has tracked 25,986,827 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.5. This one scored the same or higher as 0 of them.
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 88,143 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them