ABSTRACT
BACKGROUND: Traumatic brain injury (TBI) is a major health problem, both in terms of the economic cost to society and the survivor's quality of life. The development of devices to protect against TBI requires criteria that relate observed injury to measurements of head kinematics. The objective of this study is to find the best statistical correlates to impact-induced TBI in nonhuman primates using a qualified, self-consistent set of historical kinematic and TBI data from impact tests on nonhuman primates. METHODS: A database was constructed and qualified from historical head impact tests on nonhuman primates. Multivariate logistic regression analysis with backwards stepwise elimination was performed. Variables considered are the peak rotational acceleration (Omegamax), the peak linear acceleration (Amax), and the number of impacts (N). RESULTS: Bivariate combinations of angular acceleration and the number of impacts are the best correlates to all modes of TBI considered, i.e., concussion, subarachnoid hemorrhage, brain contusion, and subdural hematoma. For a nonhuman primate with 100-g brain mass, the criteria that the probability of TBI is less than 10% by injury mode are:Concussion: OmegamaxN(0.84) < 70 krad/s/s SAH: OmegamaxN(0.70) < 160 krad/s/s Contusion: Omegamax N(0.35) < 160 krad/s/s SDH: Omegamax N(0.60) < 280 krad/s/s CONCLUSIONS: Based on this dataset, the best statistically based risk factor for all modes of TBI in nonhuman primates is the bivariate combination of rotational acceleration and number of impacts.
Subject(s)
Brain Injuries/prevention & control , Brain Injuries/physiopathology , Acceleration , Animals , Biomechanical Phenomena , Brain Concussion/physiopathology , Brain Concussion/prevention & control , Disease Models, Animal , Hematoma, Subdural, Acute/physiopathology , Hematoma, Subdural, Acute/prevention & control , Logistic Models , Multivariate Analysis , Primates , Risk Factors , Subarachnoid Hemorrhage, Traumatic/physiopathology , Subarachnoid Hemorrhage, Traumatic/prevention & controlABSTRACT
This work develops a skull fracture criterion for lateral impact-induced head injury using postmortem human subject tests, anatomical test device measurements, statistical analyses, and finite element modeling. It is shown that skull fracture correlates with the tensile strain in the compact tables of the cranial bone as calculated by the finite element model and that the Skull Fracture Correlate (SFC), the average acceleration over the HIC time interval, is the best predictor of skull fracture. For 15% or less probability of skull fracture the lateral skull fracture criterion is SFC < 120 g, which is the same as the frontal criterion derived earlier. The biomechanical basis of SFC is established by its correlation with strain.
Subject(s)
Skull Fractures/physiopathology , Biomechanical Phenomena , Elasticity , Finite Element Analysis , Humans , Logistic Models , Risk Factors , Stress, MechanicalABSTRACT
This work developed a skull fracture criterion for impact-induced head injury, using post mortem human subject tests, anatomical test device measurements, statistical analyses, and finite element modeling. It is shown that skull fracture correlates with the tensile strain in the outer table of the cranial bone, and an index termed the Skull Fracture Correlate (SFC) predicts injury. SFC offers several advantages as a protection criterion. It accounts for compliance of the impact site; it is extensible to varying head mass; and it is easily implemented using current software. For a 15% or less probability of skull fracture the criterion is SFC < 120 g, with a 95% confidence band of 88 < SFC < 135 g.
