Abstract

The elucidation and prediction of the biomechanics of lower limb fractures could serve as a useful tool in forensic practices. Finite element (FE) analysis could potentially help in the understanding of the fracture mechanisms of lower limb fractures frequently caused by car–pedestrian accidents. Our aim was (1) to develop and validate a FE model of the human lower limb, (2) to assess the biomechanics of specific injuries concerning run-over and impact loading conditions, and (3) to reconstruct one real car–pedestrian collision case using the model created in this study. We developed a novel lower limb FE model and simulated three different loading scenarios. The geometry of the model was reconstructed using Mimics 13.0 based on computed tomography (CT) scans from an actual traffic accident. The material properties were based upon a synthesis of data found in published literature. The FE model validation and injury reconstruction were conducted using the LS-DYNA code. The FE model was validated by a comparison of the simulation results of three-point bending, overall lateral impact tests and published postmortem human surrogate (PMHS) results. Simulated loading scenarios of running-over the thigh with a wheel, the impact on the upper leg, and impact on the lower thigh were conducted with velocities of 10m/s, 20m/s, and 40m/s, respectively. We compared the injuries resulting from one actual case with the simulated results in order to explore the possible fracture bio-mechanism. The peak fracture forces, maximum bending moments, and energy lost ratio exhibited no significant differences between the FE simulations and the literature data. Under simulated run-over conditions, the segmental fracture pattern was formed and the femur fracture patterns and mechanisms were consistent with the actual injury features of the case. Our study demonstrated that this simulation method could potentially be effective in identifying forensic cases and exploring of the injury mechanisms of lower limb fractures encountered due to inflicted lesions. This model can also help to distinguish between possible and impossible scenarios.

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