ArticleAnnals of biomedical engineering2014
Parametric comparisons of intracranial mechanical responses from three validated finite element models of the human head.
Article in Annals of biomedical engineering, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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Who cites it
39 citing papers in PubMed, 99 citations in OpenAlex.
- Estimated Brain Tissue Response Following Impacts Associated With and Without Diagnosed Concussion.Annals of biomedical engineering · 2018Trial
- Six Degree-of-Freedom Measurements of Human Mild Traumatic Brain Injury.Annals of biomedical engineering · 2015Trial
- High-order mesoscale modeling with geometrically conforming gray/white matter interface for traumatic brain injury.Computer methods and programs in biomedicine · 2025Article
- A mechanics-informed machine learning framework for traumatic brain injury prediction in police and forensic investigations.Communications engineering · 2025Article
- Full-field, frequency-domain comparison of simulated and measured human brain deformation.Biomechanics and modeling in mechanobiology · 2025Article
- Assessment of brain response in operators subject to recoil force from firing long-range rifles.Frontiers in bioengineering and biotechnology · 2024Article
- Evaluating the Intracranial Pressure Biofidelity and Response Repeatability of a Physical Head-Brain Model in Frontal Impacts.Annals of biomedical engineering · 2023Article
- White matter degradation near cerebral microbleeds is associated with cognitive change after mild traumatic brain injury.Neurobiology of aging · 2022Article
- Use of Brain Biomechanical Models for Monitoring Impact Exposure in Contact Sports.Annals of biomedical engineering · 2022Review
- American Football Helmet Effectiveness Against a Strain-Based Concussion Mechanism.Annals of biomedical engineering · 2022Article
- Real-time dynamic simulation for highly accurate spatiotemporal brain deformation from impact.Computer methods in applied mechanics and engineering · 2022Article
- Normalized Brain Tissue-Level Evaluation of Volumetric Changes of Youth Athletes Participating in Collision Sports.Neurotrauma reports · 2022Article
- Displacement Error Propagation From Embedded Markers to Brain Strain.Journal of biomechanical engineering · 2021Article
- Regional White Matter Diffusion Changes Associated with the Cumulative Tensile Strain and Strain Rate in Nonconcussed Youth Football Players.Journal of neurotrauma · 2021Article
- Ranking and Rating Bicycle Helmet Safety Performance in Oblique Impacts Using Eight Different Brain Injury Models.Annals of biomedical engineering · 2021Article
- A Methodology to Compare Biomechanical Simulations With Clinical Brain Imaging Analysis Utilizing Two Blunt Impact Cases.Frontiers in bioengineering and biotechnology · 2021Article
- A Machine Learning Enhanced Mechanistic Simulation Framework for Functional Deficit Prediction in TBI.Frontiers in bioengineering and biotechnology · 2021Article
- An Image Registration-Based Morphing Technique for Generating Subject-Specific Brain Finite Element Models.Annals of biomedical engineering · 2020Article
- Displacement- and Strain-Based Discrimination of Head Injury Models across a Wide Range of Blunt Conditions.Annals of biomedical engineering · 2020Article
- A network-based response feature matrix as a brain injury metric.Biomechanics and modeling in mechanobiology · 2020Article
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Authors and funding
13 authors at 5 institutions in 3 countries.
Funding
Abstract
A number of human head finite element (FE) models have been developed from different research groups over the years to study the mechanisms of traumatic brain injury. These models can vary substantially in model features and parameters, making it important to evaluate whether simulation results from one model are readily comparable with another, and whether response-based injury thresholds established from a specific model can be generalized when a different model is employed. The purpose of this study is to parametrically compare regional brain mechanical responses from three validated head FE models to test the hypothesis that regional brain responses are dependent on the specific head model employed as well as the region of interest (ROI). The Dartmouth Scaled and Normalized Model (DSNM), the Simulated Injury Monitor (SIMon), and the Wayne State University Head Injury Model (WSUHIM) were selected for comparisons. For model input, 144 unique kinematic conditions were created to represent the range of head impacts sustained by male collegiate hockey players during play. These impacts encompass the 50th, 95th, and 99th percentile peak linear and rotational accelerations at 16 impact locations around the head. Five mechanical variables (strain, strain rate, strain × strain rate, stress, and pressure) in seven ROIs reported from the FE models were compared using Generalized Estimating Equation statistical models. Highly significant differences existed among FE models for nearly all output variables and ROIs. The WSUHIM produced substantially higher peak values for almost all output variables regardless of the ROI compared to the DSNM and SIMon models (p < 0.05). DSNM also produced significantly different stress and pressure compared with SIMon for all ROIs (p < 0.05), but such differences were not consistent across ROIs for other variables. Regardless of FE model, most output variables were highly correlated with linear and rotational peak accelerations. The significant disparities in regional brain responses across head models regardless of the output variables strongly suggest that model-predicted brain responses from one study should not be extended to other studies in which a different model is utilized. Consequently, response-based injury tolerance thresholds from a specific model should not be generalized to other studies either in which a different model is used. However, the similar relationships between regional responses and the linear/rotational peak accelerations suggest that each FE model can be used independently to assess regional brain responses to impact simulations in order to perform statistical correlations with medical images and/or well-selected experiments with documented injury findings.
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