ArticleBiomechanics and modeling in mechanobiology2017
Injury prediction and vulnerability assessment using strain and susceptibility measures of the deep white matter.
Article in Biomechanics and modeling in mechanobiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.
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Who cites it
33 citing papers in PubMed, 1 synthesis or guideline pooled it, 83 citations in OpenAlex.
- Uncovering the hidden effects of repetitive subconcussive head impact exposure: A mega-analytic approach characterizing seasonal brain microstructural changes in contact and collision sports athletes.Human brain mapping · 2024Pooled it
- Estimated Brain Tissue Response Following Impacts Associated With and Without Diagnosed Concussion.Annals of biomedical engineering · 2018Trial
- Effect of modeling subject-specific cortical folds on brain injury risk prediction under blunt impact loading.Biomechanics and modeling in mechanobiology · 2026Article
- Axonal tract-integrated finite element brain model for predicting mild traumatic brain injury based on axonal strain.Frontiers in bioengineering and biotechnology · 2026Article
- Peaks and Distributions of White Matter Tract-related Strains in Bicycle Helmeted Impacts: Implication for Helmet Ranking and Optimization.Annals of biomedical engineering · 2025Article
- Efficient Generation of Pretraining Samples for Developing a Deep Learning Brain Injury Model via Transfer Learning.Annals of biomedical engineering · 2024Article
- Head Impact Kinematics and Brain Tissue Strains in High School Lacrosse.Annals of biomedical engineering · 2024Article
- Effect of Human Head Shape on the Risk of Traumatic Brain Injury: A Gaussian Process Regression-Based Machine Learning Approach.Military medicine · 2024Article
- Neuroimaging, wearable sensors, and blood-based biomarkers reveal hyperacute changes in the brain after sub-concussive impacts.Brain multiphysics · 2023Article
- A window into eye movement dysfunction following mTBI: A scoping review of magnetic resonance imaging and eye tracking findings.Brain and behavior · 2022Article
- Data-driven Uncertainty Quantification in Computational Human Head Models.Computer methods in applied mechanics and engineering · 2022Article
- Cerebral vascular strains in dynamic head impact using an upgraded model with brain material property heterogeneity.Journal of the mechanical behavior of biomedical materials · 2022Article
- The Presence of the Temporal Horn Exacerbates the Vulnerability of Hippocampus During Head Impacts.Frontiers in bioengineering and biotechnology · 2022Article
- Displacement voxelization to resolve mesh-image mismatch: Application in deriving dense white matter fiber strains.Computer methods and programs in biomedicine · 2022Article
- Review
- Regional White Matter Diffusion Changes Associated with the Cumulative Tensile Strain and Strain Rate in Nonconcussed Youth Football Players.Journal of neurotrauma · 2021Article
- The Hammer and the Nail: Biomechanics of Striking and Struck Canadian University Football Players.Annals of biomedical engineering · 2021Article
- Instantaneous Whole-Brain Strain Estimation in Dynamic Head Impact.Journal of neurotrauma · 2021Article
- Brain Strain: Computational Model-Based Metrics for Head Impact Exposure and Injury Correlation.Annals of biomedical engineering · 2021Article
- A Machine Learning Approach to Investigate the Uncertainty of Tissue-Level Injury Metrics for Cerebral Contusion.Frontiers in bioengineering and biotechnology · 2021Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Reliable prediction and diagnosis of concussion is important for its effective clinical management. Previous model-based studies largely employ peak responses from a single element in a pre-selected anatomical region of interest (ROI) and utilize a single training dataset for injury prediction. A more systematic and rigorous approach is necessary to scrutinize the entire white matter (WM) ROIs as well as ROI-constrained neural tracts. To this end, we evaluated injury prediction performances of the 50 deep WM regions using predictor variables based on strains obtained from simulating the 58 reconstructed American National Football League head impacts. To objectively evaluate performance, repeated random subsampling was employed to split the impacts into independent training and testing datasets (39 and 19 cases, respectively, with 100 trials). Univariate logistic regressions were conducted based on training datasets to compute the area under the receiver operating characteristic curve (AUC), while accuracy, sensitivity, and specificity were reported based on testing datasets. Two tract-wise injury susceptibilities were identified as the best overall via pair-wise permutation test. They had comparable AUC, accuracy, and sensitivity, with the highest values occurring in superior longitudinal fasciculus (SLF; 0.867-0.879, 84.4-85.2, and 84.1-84.6%, respectively). Using metrics based on WM fiber strain, the most vulnerable ROIs included genu of corpus callosum, cerebral peduncle, and uncinate fasciculus, while genu and main body of corpus callosum, and SLF were among the most vulnerable tracts. Even for one un-concussed athlete, injury susceptibility of the cingulum (hippocampus) right was elevated. These findings highlight the unique injury discriminatory potentials of computational models and may provide important insight into how best to incorporate WM structural anisotropy for investigation of brain injury.
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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.