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

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 were 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 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 not to be statistically significant. Additionally, the ROC curve analysis showed moderate predictive power for all regional IRCs.

Characterizing and Modeling Ovine Hide and Costal Cartilage for Use in Modeling High-Rate Non-Penetrating Blunt Impact.

INTRODUCTION: High-rate non-penetrating blunt impacts to the thorax, such as from impacts to protective equipment, can lead to a wide range of thoracic injuries. These injuries can include rib fractures, lung contusions, and abdominal organ contusions. Ovine animals have been used to study such impacts, in a variety of ways, including in silico. To properly model these impacts in silico, it is imperative that the tissues impacted are properly characterized. The objective of this study is to characterize and validate two tissues impacted that are adjacent to the point of impact-costal cartilage and hide. Heretofore, these materials have not been characterized for use in computational models despite their nearly immediate engagement in the high-rate, non-penetrating loading environment. MATERIALS AND METHODS: Ovine costal cartilage and hide samples were procured from a local abattoir following USDA regulations. Costal cartilage samples were then cut into ASTM D638 Type V tensile coupons and compressive disks for testing. The cartilage tensile coupons were tested at 150 ε/s, and the compressive samples were tested at -150 ε/s. Identical coupons and disks were then simulated in LS-Dyna using a hyperelastic material model based on test data and experimental boundary conditions. Hide samples were shaved and cut into ASTM D638 Type V tensile coupons and validated in silico using identical boundary conditions and an Ogden rubber model based on test data. RESULTS: The structural responses of costal cartilage and hide are presented and exhibit typical behavior for biological specimens. The respective model fits in LS-Dyna were a hyperelastic- based "simplified rubber" for the costal cartilage and an Ogden rubber for the hide. The costal cartilage had a mean failure strain of 0.094 ± 0.040 in tension and -0.1755 ± 0.0642 in compression. The costal cartilage was also noted to have an order-of-magnitude difference in the stresses observed experimentally between the tensile and compressive experiments. Hide had a mean failure strain of 0.2358 ± 0.1362. The energies for all three simulations showed material stability. CONCLUSIONS: Overall, we successfully characterized the mechanical behavior of the hide and costal cartilage in an ovine model. The data are intended for use in computational analogs of the ovine model for testing non-penetrating blunt impact in silico. To improve upon these models, rate sensitivity should be included, which will require additional mechanical testing.

Micro-CT Imaging and Mechanical Properties of Ovine Ribs.

The use of ovine animal models in the study of injury biomechanics and modeling is increasing, due to their favorable size and other physiological characteristics. Along with this increase, there has also been increased interest in the development of in silico ovine models for computational studies to compliment physical experiments. However, there remains a gap in the literature characterizing the morphological and mechanical characteristics of ovine ribs. The objective of this study therefore is to report anatomical and mechanical properties of the ovine ribs using microtomography (micro-CT) and two types of mechanical testing (quasi-static bending and dynamic tension). Using microtomography, young ovine rib samples obtained from a local abattoir were cut into approximately fourteen 38 mm sections and scanned. From these scans, the cortical bone thickness and cross-sectional area were measured, and the moment of inertia was calculated to enhance the mechanical testing data. Based on a standard least squares statistical model, the cortical bone thickness varied depending on the region of the cross-section and the position along the length of the rib (p < 0.05), whereas the cross-sectional area remained consistent (p > 0.05). Quasi-static three-point bend testing was completed on ovine rib samples, and the resulting force-displacement data was analyzed to obtain the stiffness (44.67 ± 17.65 N/mm), maximum load (170.54 ± 48.28 N) and displacement at maximum load (7.19 ± 2.75 mm), yield load (167.81 ± 48.12 N) and displacement at yield (6.10 ± 2.25 mm), and the failure load (110.90 ± 39.30 N) and displacement at failure (18.43 ± 2.10 mm). The resulting properties were not significantly affected by the rib (p > 0.05), but by the animal they originated from (p < 0.05). For the dynamic testing, samples were cut into coupons and tested in tension with an average strain rate of 18.9 strain/sec. The resulting dynamic testing properties of elastic modulus (5.16 ± 2.03 GPa), failure stress (63.29 ± 14.02 MPa), and failure strain (0.0201 ± 0.0052) did not vary based on loading rate (p > 0.05).

Contrast enhanced computed tomography of small ruminants: Caprine and ovine.

The use of small ruminants, mainly sheep and goats, is increasing in biomedical research. Small ruminants are a desirable animal model due to their human-like anatomy and physiology. However, the large variability between studies and lack of baseline data on these animals creates a barrier to further research. This knowledge gap includes a lack of computed tomography (CT) scans for healthy subjects. Full body, contrast enhanced CT scans of caprine and ovine subjects were acquired for subsequent modeling studies. Scans were acquired from an ovine specimen (male, Khatadin, 30-35 kg) and caprine specimen (female, Nubian 30-35 kg). Scans were acquired with and without contrast. Contrast enhanced scans utilized 1.7 mL/kg of contrast administered at 2 mL/s and scans were acquired 20 seconds, 80 seconds, and 5 minutes post-contrast. Scans were taken at 100 kV and 400 mA. Each scan was reconstructed using a bone window and a soft tissue window. Sixteen full body image data sets are presented (2 specimens by 4 contrast levels by 2 reconstruction windows) and are available for download through the form located at: https://redcap.link/COScanData. Scans showed that the post-contrast timing and scan reconstruction method affected structural visualization. The data are intended for further biomedical research on ruminants related to computational model development, device prototyping, comparative diagnostics, intervention planning, and other forms of translational research.

Optimization of a simplified automobile finite element model using time varying injury metrics.

In 2011, frontal crashes resulted in 55% of passenger car injuries with 10,277 fatalities and 866,000 injuries in the United States. To better understand frontal crash injury mechanisms, human body finite element models (FEMs) can be used to reconstruct Crash Injury Research and Engineering Network (CIREN) cases. A limitation of this method is the paucity of vehicle FEMs; therefore, we developed a functionally equivalent simplified vehicle model. The New Car Assessment Program (NCAP) data for our selected vehicle was from a frontal collision with Hybrid III (H3) Anthropomorphic Test Device (ATD) occupant. From NCAP test reports, the vehicle geometry was created and the H3 ATD was positioned. The material and component properties optimized using a variation study process were: steering column shear bolt fracture force and stroke resistance, seatbelt pretensioner force, frontal and knee bolster airbag stiffness, and belt friction through the D-ring. These parameters were varied using three successive Latin Hypercube Designs of Experiments with 130-200 simulations each. The H3 injury response was compared to the reported NCAP frontal test results for the head, chest and pelvis accelerations, and seat belt and femur forces. The phase, magnitude, and comprehensive error factors, from a Sprague and Geers analysis were calculated for each injury metric and then combined to determine the simulations with the best match to the crash test. The Sprague and Geers analyses typically yield error factors ranging from 0 to 1 with lower scores being more optimized. The total body injury response error factor for the most optimized simulation from each round of the variation study decreased from 0.466 to 0.395 to 0.360. This procedure to optimize vehicle FEMs is a valuable tool to conduct future CIREN case reconstructions in a variety of vehicles.