Head injury prediction capability of the HIC, HIP, SIMon and ULP criteria

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Abstract

The objective of the present study is to synthesize and investigate using the same set of sixty-one real-world accidents the human head injury prediction capability of the head injury criterion (HIC) and the head impact power (HIP) based criterion as well as the injury mechanisms related criteria provided by the simulated injury monitor (SIMon) and the Louis Pasteur University (ULP) finite element head models. Each accident has been classified according to whether neurological injuries, subdural haematoma and skull fractures were reported. Furthermore, the accidents were reconstructed experimentally or numerically in order to provide loading conditions such as acceleration fields of the head or initial head impact conditions. Finally, thanks to this large statistical population of head trauma cases, injury risk curves were computed and the corresponding regression quality estimators permitted to check the correlation of the injury criteria with the injury occurrences. As different kinds of accidents were used, i.e. footballer, motorcyclist and pedestrian cases, the case-independency could also be checked. As a result, FE head modeling provides essential information on the intracranial mechanical behavior and, therefore, better injury criteria can be computed. It is clearly shown that moderate and severe neurological injuries can only be distinguished with a criterion that is computed using intracranial variables and not with the sole global head acceleration.

Introduction

The brain is among the most vital organs of the human body. From a mechanical point of view, the natural evolution of the head has lead to a number of integrated protection devices. The scalp and the skull, but also to a certain extent the pressurized subarachnoidal space and the dura matter, are natural protections for the brain. However, these structures are not adapted to the dynamic loading conditions involved in modern road and sports accidents. The consequence of this extreme loading is often moderate-to-severe injuries. Thus, preventing these head injuries is a high priority.

Over the past 40 years, an emphasis has been placed by biomechanical research on understanding the mechanism of head injuries. One of the main difficulties in this research field is that functional deficiency is not necessarily directly linked to a visibly damaged tissue. Nevertheless, an injury is always a consequence of exceeded tissue tolerance to a specific load. Even if local tissue tolerance has been investigated for decades, the global acceleration of the impacted head as well as impact duration is usually utilized as impact severity descriptors. The Wayne State University Tolerance Curve has been used since the early 1960s; according to Lissner et al. (1960) and Gurdjian and Webster (1958) the curve shows the link between the impact of the head, described by head acceleration, the impact duration and risk of head injury. Based on the work of Gadd (1966), the National Highway Traffic Safety Administration (NHTSA) proposed the head injury criterion (HIC) in 1972. This is the tool currently used in safety standards for head protection systems using headforms. Since it is based solely on global linear resultant acceleration of a one-mass head model, some limitations of this empiric criterion are well known (Newman, 1986). For example, the HIC is not specific to direction of impact and it neglects the angular accelerations. This is why Newman proposed the GAMBIT and more recently the head impact power (HIP) at the end of the 1990s (Newman et al., 2000). A methodology was formulated to assess brain injuries based on multiple accident reconstructions of American football players’ head collisions during recorded games.

In the computation of the HIC and HIP criteria, the head is modeled as a rigid mass without any deformation. Using the finite element method and, as a consequence of computing capacitity improvement, the deformation of the skull and the internal components can now be simulated. This method allows for the addition of mechanical observations that begin to match the description of known injury mechanisms. Hence, new injury criteria are proposed. In the past few decades, more than ten different three-dimensional finite element head models (FEHM) have been reported in the literature by Ward et al. (1980), Shugar (1977), Hosey and Liu (1980), Dimasi et al. (1991), Mendis (1992), Ruan et al. (1991), Bandak et al. (1994), Zhou et al. (1995), Al-Bsharat et al. (1999), Willinger et al. (1999) and Zhang et al. (2001). Fully documented head impact cases can be simulated in order to compute mechanical loading sustained by brain tissue as well as other tissues in the surrounding areas and we compare it to the real injuries described in the medical reports. Zhou et al. (1996), Kang et al. (1997), and more recently King et al. (2003) show that brain shear stress and strain rates predicted by their FEHM agree with the location and severity of axonal injuries described in medical reports.

Due to finite element head models, new injury prediction tools based on computed intracranial loading are becoming available. The FEHM developed at Wayne State University has been used by Zhou et al. (1995) to develop these tools. Thirteen motorcyclist accidents were reconstructed by Willinger and Baumgartner (2001) at Strasbourg Louis Pasteur University (ULP) using the FEHM presented in Willinger et al. (1999) and described in Section 3 of this paper. This study establishes that computed brain pressure is not correlated with the occurrence of brain hemorrhages, whereas brain Von Mises stress is. In order to undertake a statistical approach to injury mechanisms, more football, motorcycle and pedestrian accident cases were introduced in Willinger and Baumgartner (2003). This was the first proposal of injury criteria to specific mechanisms. Another FEHM, developed by Takhounts et al. (2003) is the simulated injury monitor or SIMon. It is appropriate for this kind of study due to its short computing time. In that study, a number of scaled animal model loading conditions lead the authors to provide criteria as reported in Section 3.

The objective of this study is to use a set of real-world accidents to assess the injury prediction capability of the HIC, HIP as well as the criteria provided by the SIMon FEHM and the ULP FEHM.

Section snippets

Methodology

A database of sixty-one real-world accident cases is used in order to compare the injury prediction capability of the HIC, the HIP, the SIMon and the ULP FEHM criteria. Football, motorcycle and pedestrian accidents are described in Section 3 of this paper. Each accident case is classified according to its medical report as follows:

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    Cases of neurological injuries are the cases in which a concussion, unconsciousness, a coma or diffuse axonal injuries (DAI) have been reported. These injuries are

Data sources

This section describes the real-world accidents that were used in the present study and details how the initial conditions are handled to drive the head models in order to compute the related injury criteria. Furthermore, head models and details on criteria computation are also synthesized.

Results

The determination of the head injury risk curves for specific injury mechanisms is based on a correlation study between the values of the proposed candidate criteria and the injury occurrences. A histogram is built for each specific injury and the value taken by a given criterion for each case is plotted. These accident cases are sorted according to the injury classification as explained in the methodology section, i.e. moderate and severe neurological injuries, SDH and skull fractures. When

Discussion

The logistic regression analysis has been made on a rather relevant statistical population of 61 accident cases when considering neurological injuries or SDH and of 27 accident cases when considering skull fractures. The estimator EB of the logistic regression takes the quality of the statistical populations into account as well as the correlation between the proposed injury metric and the injury occurrences. It is also important to note that there are different kinds of accidents so that the

Conclusion and perspectives

Sixty-one real-world accident cases have been reconstructed in order to provide head acceleration fields and head initial impact conditions so that the HIC, the HIP, the SIMon and the ULP criteria could be computed. New tolerance limits to specific injury mechanisms were deduced for the ULP head FE model and the relevance of their capability to predict injuries could therefore be investigated comparatively with HIC, HIP and SIMON criteria, using histograms and injury risk curves. The advantage

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