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J Biomech Eng. 2018 Feb 20. doi: 10.1115/1.4039393. [Epub ahead of print]

Finite Element Based Pelvic Injury Metric Creation and Validation in Lateral Impact for a Human Body Model.

Author information

1
Wake Forest University School of Medicine, Virginia Tech-Wake Forest University Center for Injury Biomechanics, 575 N. Patterson Ave., Ste. 120, Winston-Salem, NC 27101, US Army Research Laboratory Soldier Protection Sciences Branch, RDRL-WMP-B, Aberdeen Proving Ground, MD 21005.
2
Wake Forest University School of Medicine, Virginia Tech-Wake Forest University Center for Injury Biomechanics, 575 N. Patterson Ave., Ste. 120, Winston-Salem, NC 27101.
3
Washington University, Department of Orthopaedic Surgery, 660 S. Euclid Ave., Box 8233, St. Louis, MO 63110.

Abstract

Pelvic fractures are serious injuries resulting in high mortality and morbidity. The objective of this study is to develop and validate local pelvic anatomical, cross-section-based injury risk metrics for a finite element (FE) model of the human body. Cross-sectional instrumentation was implemented in the pelvic region of the Global Human Body Models Consortium (GHBMC M50-O) 50th percentile detailed male FE model (v4.3). In total, 25 lateral impact FE simulations were performed using input data from cadaveric lateral impact tests performed by Bouquet et al. The experimental force-time data was scaled using five normalization techniques, which were evaluated using log rank, Wilcoxon rank sum, and correlation and analysis (CORA) testing. Survival analyses with Weibull distribution were performed on the experimental peak force (scaled and unscaled) and the simulation test data to generate injury risk curves (IRCs) for total pelvic injury. Additionally, IRCs were developed for regional injury using cross-sectional forces from the simulation results and injuries documented in the experimental autopsies. These regional IRCs were also evaluated using the receiver operator characteristic (ROC) curve analysis. Based on the results of the all the evaluation methods, the Equal Stress Equal Velocity (ESEV) and ESEV using effective mass (ESEV-EM) scaling techniques performed best. The simulation IRC shows slight under prediction of injury in comparison to these scaled experimental data curves. However, this difference was determined to not be statistically significant. Additionally, the ROC curve analysis showed moderate predictive power for all regional IRCs.

PMID:
29560493
DOI:
10.1115/1.4039393

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