↓ Skip to main content

Fluid–structure interaction simulation of the brain–skull interface for acute subdural haematoma prediction

Overview of attention for article published in Biomechanics and Modeling in Mechanobiology, August 2018
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#45 of 486)
  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

twitter
7 X users

Citations

dimensions_citation
64 Dimensions

Readers on

mendeley
71 Mendeley
Title
Fluid–structure interaction simulation of the brain–skull interface for acute subdural haematoma prediction
Published in
Biomechanics and Modeling in Mechanobiology, August 2018
DOI 10.1007/s10237-018-1074-z
Pubmed ID
Authors

Zhou Zhou, Xiaogai Li, Svein Kleiven

Abstract

Traumatic brain injury is a leading cause of disability and mortality. Finite element-based head models are promising tools for enhanced head injury prediction, mitigation and prevention. The reliability of such models depends heavily on adequate representation of the brain-skull interaction. Nevertheless, the brain-skull interface has been largely simplified in previous three-dimensional head models without accounting for the fluid behaviour of the cerebrospinal fluid (CSF) and its mechanical interaction with the brain and skull. In this study, the brain-skull interface in a previously developed head model is modified as a fluid-structure interaction (FSI) approach, in which the CSF is treated on a moving mesh using an arbitrary Lagrangian-Eulerian multi-material formulation and the brain on a deformable mesh using a Lagrangian formulation. The modified model is validated against brain-skull relative displacement and intracranial pressure responses and subsequently imposed to an experimentally determined loading known to cause acute subdural haematoma (ASDH). Compared to the original model, the modified model achieves an improved validation performance in terms of brain-skull relative motion and is able to predict the occurrence of ASDH more accurately, indicating the superiority of the FSI approach for brain-skull interface modelling. The introduction of the FSI approach to represent the fluid behaviour of the CSF and its interaction with the brain and skull is crucial for more accurate head injury predictions.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 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 71 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 71 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 25%
Researcher 14 20%
Student > Master 5 7%
Student > Bachelor 3 4%
Student > Doctoral Student 3 4%
Other 5 7%
Unknown 23 32%
Readers by discipline Count As %
Engineering 29 41%
Medicine and Dentistry 4 6%
Neuroscience 3 4%
Mathematics 1 1%
Biochemistry, Genetics and Molecular Biology 1 1%
Other 3 4%
Unknown 30 42%
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 31 January 2019.
All research outputs
#4,846,517
of 23,849,058 outputs
Outputs from Biomechanics and Modeling in Mechanobiology
#45
of 486 outputs
Outputs of similar age
#91,509
of 336,584 outputs
Outputs of similar age from Biomechanics and Modeling in Mechanobiology
#3
of 9 outputs
Altmetric has tracked 23,849,058 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 486 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one has gotten more attention than average, scoring higher than 74% 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 336,584 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 72% of its contemporaries.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 6 of them.