Evidence map›Paper›PMID 40205286›Full record

ArticleAnnals of biomedical engineering2025

Average Biomechanical Responses of the Human Brain Grouped by Age and Sex.

Ahmed Alshareef, Aaron Carass, Yuan-Chiao Lu, Joy Mojumder, Alexa M Diano, Olivia M Bailey, Ruth J Okamoto, Dzung L Pham, Jerry L Prince, Philip V Bayly and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Annals of biomedical engineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Multimodal characterization of intracranial biomechanics in a 3D biofidelic head surrogate.Journal of the mechanical behavior of biomedical materials · 2026
    Article
  4. 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

11 authors.

Ahmed AlshareefDepartment of Biomedical Engineering, University of South Carolina, Columbia, SC, USA. alshareef@sc.edu.ORCID http://orcid.org/0000-0003-4512-1618
Aaron CarassImage Analysis and Communications Laboratory, Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA.
Yuan-Chiao LuThe Military Traumatic Brain Injury Initiative, The Henry M. Jackson Foundation, Bethesda, MD, USA.
Joy MojumderDepartment of Radiology and Imaging Sciences, National Institutes of Health, Bethesda, MD, USA.
Alexa M DianoDepartment of Biomedical Engineering, University of Delaware, Newark, DE, USA.
Olivia M BaileyDepartment of Biomedical Engineering, University of Delaware, Newark, DE, USA.
Ruth J OkamotoDepartment of Mechanical Engineering, Washington University in St. Louis, St. Louis, MO, USA.
Dzung L PhamThe Military Traumatic Brain Injury Initiative, The Henry M. Jackson Foundation, Bethesda, MD, USA.
Jerry L PrinceImage Analysis and Communications Laboratory, Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA.
Philip V BaylyDepartment of Mechanical Engineering, Washington University in St. Louis, St. Louis, MO, USA.
Curtis L JohnsonDepartment of Biomedical Engineering, University of Delaware, Newark, DE, USA.

Funding

MRI Measurement of the Mechanical Vulnerability of the BrainU01NS112120 · NINDS · WASHINGTON UNIVERSITY · PI BAYLY, PHILIP V · 2019 to 2023
$3.7M
Biomechanics of the Human Brain During High-Severity Impacts: A Multimodal ApproachR01NS136056 · NINDS · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI Ahmed Alshareef, Matthew Brian Panzer · 2025 to 2026
$1.1M
Congressionally Directed Medical Research Programs W81XWH2211117NINDS NIH HHS R01 NS136056NINDS NIH HHS U01 NS112120NINDS NIH HHS U01NS112120
6 · The paper itself

Abstract

Traumatic brain injuries (TBIs) occur from rapid head motion that results in brain deformation. Computational models are typically used to estimate brain deformation to predict risk of injury and evaluate the effectiveness of safety countermeasures. The accuracy of these models relies on validation to experimental brain deformation data. In this study, we create the first group-average biomechanical responses of the brain, including structure, material properties, and deformation response, by age and sex from 157 subjects. Subjects were sorted intro three age groups-young, mid-age, and older-and by sex to create group-average neuroanatomy, material properties, and brain deformation response to non-injurious loading using structural and specialized magnetic resonance imaging data. Computational models were also built using the group-average geometry and material properties for each of the six groups. The material properties did not depend on sex, but showed a decrease in shear stiffness in the older adult group. The brain deformation response also showed differences in the distribution of strain and a decrease in the magnitude of maximum strain in the older adult group. The computational models were simulated using the same non-injurious loading conditions as the subject data. While the models' strain response showed differences among the models, there were no clear relationships with age. Further studies, both modeling and experimental, with more data from subjects in each age group, are needed to clarify the mechanisms underlying the observed changes in strain response with age, and for computational models to better match the trends observed across the group-average responses.

Indexed as

AgingBrainBrain Injuries, TraumaticModels, BiologicalSex CharacteristicsAdolescentAdultAgedAged, 80 and overBiomechanical PhenomenaFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedBrain deformationFinite element modelingGroup averageMagnetic resonance imagingTraumatic brain injury

Identifiers

PMID40205286
PMCPMC12075284

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LicenceCC BY
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Registered trials

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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.