Assessment of Kinematic Brain Injury Metrics for Predicting Strain Responses in Diverse Automotive Impact Conditions

Abstract

Numerous injury criteria have been developed to predict brain injury using the kinematic response of the head during impact. Each criterion utilizes a metric that is some mathematical combination of the velocity and/or acceleration components of translational and/or rotational head motion. Early metrics were based on linear acceleration of the head, but recent injury criteria have shifted towards rotational-based metrics. Currently, there is no universally accepted metric that is suitable for a diverse range of head impacts. In this study, we assessed the capability of fifteen existing kinematic-based metrics for predicting strain-based brain response using four different automotive impact conditions. Tissue-level strains were obtained through finite element model simulation of 660 head impacts including occupant and pedestrian crash tests, and pendulum head impacts. Correlations between head kinematic metrics and predicted brain strain-based metrics were evaluated. Correlations between brain strain and metrics based on angular velocity were highest among those evaluated, while metrics based on linear acceleration were least correlative. BrIC and RVCI were the kinematic metrics with the highest overall correlation; however, each metric had limitations in certain impact conditions. The results of this study suggest that rotational head kinematics are the most important parameters for brain injury criteria.

Performance Evaluation of a Pre-computed Brain Response Atlas in Dummy Head Impacts

“…Two commonly used, strain-based injury metrics were derived from ε est and ε actual , respectively: peak maximum principal strain ( ε p ) and CSDM 15 . The comparison was conducted in four ROIs (cerebrum, cerebellum, brainstem, and the corpus callosum) and the whole brain.…”

“…The comparison was conducted in four ROIs (cerebrum, cerebellum, brainstem, and the corpus callosum) and the whole brain. To avoid potential numerical issues, ε p was determined as the element-wise 95 th percentile peak response 15 . For CSDM, a range of strain thresholds were enumerated (0.05 to 0.25, with a step size of 0.05).…”

“…BrIC was selected because it was one of the 15 kinematic metrics that correlated the strongest with the directly simulated brain strains in diverse automotive impact conditions 15 . BrIC is formulated using the maximum magnitudes of three orthogonal head angular velocity components, ω x , ω y , and ω z in a body-fix coordinate system, regardless of their time of occurrence: $$\mathit{BrIC}=\sqrt{{(\frac{{\omega }_x}{{\omega }_{xc}})}^2+{(\frac{{\omega }_y}{{\omega }_{yc}})}^2+{(\frac{{\omega }_z}{{\omega }_{zc}})}^2}$$ where ω xc , ω yc , and ω zc are critical velocity values corresponding to a 50% injury probability along the three major axes.…”

“…Indeed, recent studies have shown that tissue response-based metrics outperform kinematics in injury prediction 17,19,27,33 . This has led to the use of model-simulated brain strains to benchmark injury prediction performances of other kinematic metrics 15,27,40 . For example, BrIC and RVCI were identified to correlate the best overall among 15 kinematic metrics with directly simulated brain strains in diverse automotive impact conditions 15 .…”

Evaluating Pedestrian Head Sub-system Test Procedure against Full-scale Vehicle-pedestrian Impact Using Numerical Models

“…Two strain-based brain injury metrics have been used in previous computational studies to categorize brain injury: maximum principle strain (MPS) and Cumulative Strain Damage Measure (CSDM) (Takhounts et al 2013). Gabler et al (2016) assessed fifteen kinematic-based brain injury metrics by comparing their correlation to tissue-level strain responses obtained from 660 head impacts simulated in two separate human head FE models (SIMon and GHBMC head model) (Takhounts et al 2003(Takhounts et al , 2008, and two angular velocity-based metrics, the Brain Injury Criterion (BrIC) and Rotational Velocity Change Index (RVCI), were found to have the highest overall correlation with closed head injuries. The BrIC, is the updated criterion to the original BRIC formulation after finding that angular velocity alone was sufficient to predict FE model strains (Takhounts et al 2013), and is formulated using the maximum magnitudes of the three orthogonal head angular velocity components:…”