Evidence map›Paper›PMID 22655600›Full record

ReviewAnnual review of biomedical engineering2012

Quantitative imaging methods for the development and validation of brain biomechanics models.

Philip V Bayly, Erik H Clayton, Guy M Genin

Abstract readReview
In one paragraph

Review in Annual review of biomedical engineering, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

44 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Group characterization of impact-induced,Journal of the Royal Society, Interface · 2021
    Article
  10. Article
  11. Article
  12. Nonlinear Inversion MR Elastography With Low-Frequency Actuation.IEEE transactions on medical imaging · 2020
    Article
  13. Article
  14. Article
  15. Quantitative Validation of MRI-Based Motion Estimation for Brain Impact Biomechanics.Computational biomechanics for medicine. Personalisation, validation and therapy · 2020
    Article
  16. Article
  17. Review
  18. Article
  19. Biomechanical simulation of traumatic brain injury in the rat.Clinical biomechanics (Bristol, Avon) · 2019
    Review
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Philip V BaylyDepartment of Mechanical Engineering and Materials Science, Washington University in St. Louis, St. Louis, Missouri 63130, USA. pvb@wustl.edu
Erik H Clayton
Guy M Genin

Funding

IN VIVO MEASUREMENT OF BRAIN BIOMECHANICSR01NS055951 · NINDS · WASHINGTON UNIVERSITY · PI BAYLY, PHILIP V · 2007 to 2017
$3.9M
Mechanics Characterization of Cellular Force RegulationK25HL079165 · NHLBI · WASHINGTON UNIVERSITY · PI GENIN, GUY M · 2006 to 2010
$701k
In Vivo Measurement of Brain BiomechanicsR56NS055951 · NINDS · WASHINGTON UNIVERSITY · PI BAYLY, PHILIP V · 2018 to 2018
$563k
MECHANICAL CHANGES IN THE DEVELOPING BRAINR21EB005834 · NIBIB · WASHINGTON UNIVERSITY · PI BAYLY, PHILIP V · 2009 to 2010
$410k
Intracranial Strain in Mild Traumatic Head InjuryR21NS045237 · NINDS · WASHINGTON UNIVERSITY · PI BAYLY, PHILIP V · 2003 to 2004
$363k
NHLBI NIH HHS HL079165NHLBI NIH HHS K25 HL079165NIBIB NIH HHS EB005834NIBIB NIH HHS R21 EB005834NINDS NIH HHS NS045237NINDS NIH HHS NS055951NINDS NIH HHS R01 NS055951NINDS NIH HHS R21 NS045237NINDS NIH HHS R56 NS055951
6 · The paper itself

Abstract

Rapid deformation of brain tissue in response to head impact or acceleration can lead to numerous pathological changes, both immediate and delayed. Modeling and simulation hold promise for illuminating the mechanisms of traumatic brain injury (TBI) and for developing preventive devices and strategies. However, mathematical models have predictive value only if they satisfy two conditions. First, they must capture the biomechanics of the brain as both a material and a structure, including the mechanics of brain tissue and its interactions with the skull. Second, they must be validated by direct comparison with experimental data. Emerging imaging technologies and recent imaging studies provide important data for these purposes. This review describes these techniques and data, with an emphasis on magnetic resonance imaging approaches. In combination, these imaging tools promise to extend our understanding of brain biomechanics and improve our ability to study TBI in silico.

Indexed as

AnimalsBiomechanical PhenomenaBiomedical EngineeringBrainBrain InjuriesCadaverDiagnostic ImagingElasticity Imaging TechniquesHumansMagnetic Resonance ImagingModels, AnatomicModels, BiologicalModels, StatisticalModels, TheoreticalRatsSkull

Identifiers

PMID22655600
PMCPMC3711121

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.