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Objective: Fatal brain injuries result from physiological changes in brain tissues, subsequent to primary damage caused by head impact. Although efforts have been made in past studies to estimate the probability of brain injury, none of them involved prediction of such physiological changes. The goal of this study was to evaluate the fatality prediction capability of a novel approach that predicts an increase in intracranial pressure (ICP) due to primary head injury to estimate the fatality rate using clinical data that correlate ICP with fatality rate. Methods: A total of 12 sets of head acceleration time histories were used to represent no, severe, and fatal brain injury. They were obtained from the literature presenting head kinematics data in noninjurious volunteer sled tests or from accident reconstruction for severe and fatal injury cases. These were first applied to a Global Human Body Models Consortium (GHBMC) head-brain model to predict nodal displacement time histories of the brain, which were then fed into FEBio to predict ICP. A Weibull distribution was applied to the data for the relationship between fatality rate and ICP obtained from a clinical paper to estimate fatality rate from ICP (procedure A). Fatality rate was also estimated by applying the temporal and spatial maximum value of maximum principal strain (MPS max ) obtained from the GHBMC simulation to an injury probability function for MPS max (procedure B). Estimated fatality rates were compared between the 2 procedures. Results: Both procedures estimated higher average fatality rate for higher injury severity. The average fatality rate for procedure A without ischemia representation and procedure B was 72.4 and 51.0% for the fatal injury group and 8.2 and 21.7% for the severe injury group, respectively, showing that procedure A provides more distinct classification between fatal and nonfatal brain injury. It was also found that representation of ischemia in procedure A provides results sensitive to injury severity and impact conditions, requiring further validation of the initial estimate for the relationship between brain compression and ischemic cell death. Conclusions: Prediction of the probability of fatality by means of a combination of simulations of the primary brain deformation and subsequent ICP increase was found to be more distinct compared to the prediction of primary injury alone combined with the injury probability function from a past study in the select 12 head impact cases. ARTICLE HISTORY

In this study, finite element models for two types of bicycles with different shapes were constructed. These deformable models were validated in quasi-static loading conditions, and were used to investigate the effect of the deformation of the bicycle body on the head injuries to its occupant. The analysis confirmed that, when deformable models are used, the kinematics of the cyclist after the contact with a vehicle changes, and the injury values are different, from those obtained by rigid models. In addition, different bicycle types produce different riding postures, which significantly change the rotational motion of the cyclist around the vertical axis, subsequently affecting head injuries.

The high fatality rate of the elderly in traffic accidents is one of the important issues in traffic safety. It is necessary to consider the influence of age and gender to reduce traffic fatalities of elderly occupants according to previous studies. The objective was to identify representative accident scenarios for elderly female occupants in side impacts. The Delta-V, PDOF and the most common seat track were identified using accident statistics. In addition, The influence of the seat track on thoracic injuries was investigated against the standard side impact protocol using a simulation model.