Predictors for traumatic brain injuries evaluated through accident reconstructions.
The aim of this study is to evaluate all the 58 available NFL cases and compare various predictors for mild traumatic brain injuries using a detailed and extensively validated finite element model of the human head. Global injury measures such as magnitude in angular and translational acceleration, change in angular velocity, head impact power (HIP) and HIC were also investigated with regard to their ability to predict the intracranial pressure and strains associated with injury. The brain material properties were modeled using a hyperelastic and viscoelastic constitutive law. Also, three different stiffness parameters, encompassing a range of published brain tissue properties, were tested. 8 tissue injury predictors were evaluated for 6 different regions, covering the entire cerebrum, as well as for the whole brain. In addition, 10 head kinematics based predictors were evaluated both for correlation with injury as well as with strain and pressure. When evaluating the results, a statistical correlation between strain, strain rate, product of strain and strain rate, Cumulative Strain Damage Measure (CSDM), strain energy density, maximum pressure, magnitude of minimum pressure, as well as von Mises effective stress, with injury was found when looking into specific regions of the brain. However, the maximal pressure in the gray matter showed a higher correlation with injury than other evaluated measures. On the other hand, it was possible, through the reconstruction of a motocross accident, to re-create the injury pattern in the brain of the injured rider using maximal principal strain. It was also found that a simple linear combination of peak change in rotational velocity and HIC showed a high correlation (R=0.98) with the maximum principal strain in the brain, in addition to being a significant predictor of injury. When applying the rotational and translational kinematics separately for one of the cases, it was found that the translational kinematics contribute very little to the intracranial distortional strains while the rotational kinematics contributes insignificantly to the pressure response. This study underlines that the strain based brain tissue injury predictors are very sensitive to the choice of stiffness for the brain tissue.
Kleiven
Svein
S
Royal Institute of Technology, School of Technology and Health, Alfred Nobels Allé 10, SE-141 52 Huddinge, Sweden. sveink@kth.se
D000063:Accidents, Traffic / Q000706:statistics & numerical data*; D001696:Biomechanical Phenomena; D001930:Brain Injuries / Q000145:classification* / Q000209:etiology / Q000503:physiopathology; D003198:Computer Simulation; D005069:Evaluation Studies as Topic; D005538:Football / Q000293:injuries*; D006257:Head / Q000033:anatomy & histology*; D006801:Humans; D016015:Logistic Models; D008954:Models, Biological; D011237:Predictive Value of Tests