Evaluation of the effectiveness of toe board energy-absorbing material for foot, ankle, and lower leg injury reduction

<p><b>Objective</b>: Since 2000, numerous improvements have been made to the National Association for Stock Car Auto Racing, Incorporated (NASCAR®) driver restraint system, resulting in improved crash protection for motorsports drivers. Advancements have included seats, head and neck restraints (HNRs), seat belt restraint systems, driver helmets, and others. These enhancements have increased protection for drivers from severe crash loading. Extending protection to the driver's extremities remains challenging. Though the drivers’ legs are well contained for lateral and vertical crashes, they remain largely unrestrained in frontal and frontal oblique crashes.</p> <p><b>Method</b>: Sled testing was conducted for the evaluation of an energy-absorbing (EA) toe board material to be used as a countermeasure for leg and foot injuries. Testing included baseline rigid toe boards, tests with EA material–covered toe boards, and pretest positioning of the 50th percentile male frontal Hybrid III anthropomorphic test device (ATD) lower extremities. ATD leg and foot instrumentation included foot acceleration and tibia forces and moments.</p> <p><b>Results</b>: The sled test data were evaluated using established injury criteria for tibial plateau fractures, leg shaft fractures, and calcaneus, talus, ankle, and midfoot fractures.</p> <p><b>Conclusion</b>: A polyurethane EA foam was found to be effective in limiting axial tibia force and foot accelerations when subjected to frontal impacts using the NASCAR motorsport restraint system.</p

Finite Element Model Prediction of Pulmonary Contusion in Vehicle-to-Vehicle Simulations of Real-World Crashes

<div><p><b>Objective:</b> Pulmonary contusion (PC) is a common chest injury following motor vehicle crash (MVC). Because this injury has an inflammatory component, studying PC in living subjects is essential. Medical and vehicle data from the Crash Injury Research and Engineering Network (CIREN) database were utilized to examine pulmonary contusion in case occupants with known crash parameters.</p><p><b>Method:</b> The selected CIREN cases were simulated with vehicle finite element models (FEMs) with the Total HUman Model for Safety (THUMS) version 4 as the occupant. To match the CIREN crash parameters, vehicle simulations were iteratively improved to optimize maximum crush location and depth. Fifteen cases were successfully modeled with the simulated maximum crush matching the CIREN crush to within 10%. Following the simulations, stress and strain metrics for the elements within the lungs were calculated. These injury metrics were compared to patient imaging data to determine the best finite element predictor of pulmonary contusion.</p><p><b>Results:</b> When the thresholds were evaluated using volumetric criteria, first principal strain was the metric with the least variation in the FEM prediction of PC.</p><p><b>Conclusions:</b> A preliminary threshold for maximum crush was calculated to predict a clinically significant volume of pulmonary contusion.</p></div

Thoracoabdominal Organ Volumes for Small Women

<div><p><b>Objective:</b> Thoracoabdominal injuries commonly occur as a result of motor vehicle crashes. In order to design occupant protection systems that reduce risk of injury, researchers are using a variety of tools, including computational human body models. Though research has been conducted to provide morphological and volumetric data for the thoracoabdominal cavity of the average male, there is currently an interest in developing models for a wider range of occupants. One particular cohort of interest is the small female by stature and weight because of their use in restraint system development. Geometric data on thoracoabdominal organs are needed to construct accurate representations of female occupants. This study aimed to gather information on organ volumes from clinical medical imaging studies of small females.</p><p><b>Methods:</b> Anonymized clinical computed tomography (CT) and magnetic resonance images were used to segment organs relevant to crash-induced injuries: namely, the liver, spleen, left kidney, right kidney, pancreas, gallbladder, lungs, and heart. Segmentations were conducted using semi-automatic techniques. Additionally, diametric measurements of the vena cava, aorta, trachea, and colon were obtained from the medical images at discrete locations using linear measurement tools.</p><p><b>Results:</b> A total of 14 adult scans were selected with stature and weight ranges of 145.0 to 162.6 cm and 43.7 to 65.5 kg, respectively. The following are the average thoracoabdominal organ volumes: liver (1,224.5 ± 220.7 mL), spleen (151.6 ± 42.1 mL), left kidney (123.7 ± 20.1 mL), right kidney (115.4 ± 20.9 mL), heart (417.8 ± 36.6 mL), pancreas (54.1 ± 11.8 mL), and gallbladder (20.6 ± 13.4 mL). The average diameters were 19.7 ± 3.2 mm and 17.7 ± 5.1 mm for the vena cava and aorta, respectively. The colon had an average diameter of 37.9 ± 7.1 mm.</p><p><b>Conclusion:</b> Data characterizing the small female are important to validate the geometries used in computational models, including models derived from scaling techniques and those developed using subject-specific medical imaging. The goal of this study was to use a sample of subjects anthropometrically representative of small females to evaluate the average volume for organs commonly injured in motor vehicle crashes. Based on these data, the right and left lungs were strongly correlated with stature and the heart was strongly correlated with weight. Ultimately, these measurements will be useful for the validation of computational models of the small female.</p></div

Driver Injury Risk Variability in Finite Element Reconstructions of Crash Injury Research and Engineering Network (CIREN) Frontal Motor Vehicle Crashes

<div><p><b>Objective:</b> A 3-phase real-world motor vehicle crash (MVC) reconstruction method was developed to analyze injury variability as a function of precrash occupant position for 2 full-frontal Crash Injury Research and Engineering Network (CIREN) cases.</p><p><b>Method:</b> Phase I: A finite element (FE) simplified vehicle model (SVM) was developed and tuned to mimic the frontal crash characteristics of the CIREN case vehicle (Camry or Cobalt) using frontal New Car Assessment Program (NCAP) crash test data. Phase II: The Toyota HUman Model for Safety (THUMS) v4.01 was positioned in 120 precrash configurations per case within the SVM. Five occupant positioning variables were varied using a Latin hypercube design of experiments: seat track position, seat back angle, D-ring height, steering column angle, and steering column telescoping position. An additional baseline simulation was performed that aimed to match the precrash occupant position documented in CIREN for each case. Phase III: FE simulations were then performed using kinematic boundary conditions from each vehicle's event data recorder (EDR). HIC15, combined thoracic index (CTI), femur forces, and strain-based injury metrics in the lung and lumbar vertebrae were evaluated to predict injury.</p><p><b>Results:</b> Tuning the SVM to specific vehicle models resulted in close matches between simulated and test injury metric data, allowing the tuned SVM to be used in each case reconstruction with EDR-derived boundary conditions. Simulations with the most rearward seats and reclined seat backs had the greatest HIC15, head injury risk, CTI, and chest injury risk. Calculated injury risks for the head, chest, and femur closely correlated to the CIREN occupant injury patterns. CTI in the Camry case yielded a 54% probability of Abbreviated Injury Scale (AIS) 2+ chest injury in the baseline case simulation and ranged from 34 to 88% (mean = 61%) risk in the least and most dangerous occupant positions. The greater than 50% probability was consistent with the case occupant's AIS 2 hemomediastinum. Stress-based metrics were used to predict injury to the lower leg of the Camry case occupant. The regional-level injury metrics evaluated for the Cobalt case occupant indicated a low risk of injury; however, strain-based injury metrics better predicted pulmonary contusion. Approximately 49% of the Cobalt occupant's left lung was contused, though the baseline simulation predicted 40.5% of the lung to be injured.</p><p><b>Conclusions:</b> A method to compute injury metrics and risks as functions of precrash occupant position was developed and applied to 2 CIREN MVC FE reconstructions. The reconstruction process allows for quantification of the sensitivity and uncertainty of the injury risk predictions based on occupant position to further understand important factors that lead to more severe MVC injuries.</p></div

Development of a Computationally Efficient Full Human Body Finite Element Model

<div><p><b>Introduction:</b> A simplified and computationally efficient human body finite element model is presented. The model complements the Global Human Body Models Consortium (GHBMC) detailed 50th percentile occupant (M50-O) by providing kinematic and kinetic data with a significantly reduced run time using the same body habitus.</p><p><b>Methods:</b> The simplified occupant model (M50-OS) was developed using the same source geometry as the M50-O. Though some meshed components were preserved, the total element count was reduced by remeshing, homogenizing, or in some cases omitting structures that are explicitly contained in the M50-O. Bones are included as rigid bodies, with the exception of the ribs, which are deformable but were remeshed to a coarser element density than the M50-O. Material models for all deformable components were drawn from the biomechanics literature. Kinematic joints were implemented at major articulations (shoulder, elbow, wrist, hip, knee, and ankle) with moment vs. angle relationships from the literature included for the knee and ankle. The brain of the detailed model was inserted within the skull of the simplified model, and kinematics and strain patterns are compared.</p><p><b>Results:</b> The M50-OS model has 11 contacts and 354,000 elements; in contrast, the M50-O model has 447 contacts and 2.2 million elements. The model can be repositioned without requiring simulation. Thirteen validation and robustness simulations were completed. This included denuded rib compression at 7 discrete sites, 5 rigid body impacts, and one sled simulation. Denuded tests showed a good match to the experimental data of force vs. deflection slopes. The frontal rigid chest impact simulation produced a peak force and deflection within the corridor of 4.63 kN and 31.2%, respectively. Similar results vs. experimental data (peak forces of 5.19 and 8.71 kN) were found for an abdominal bar impact and lateral sled test, respectively. A lateral plate impact at 12 m/s exhibited a peak of roughly 20 kN (due to stiff foam used around the shoulder) but a more biofidelic response immediately afterward, plateauing at 9 kN at 12 ms. Results from a frontal sled simulation showed that reaction forces and kinematic trends matched experimental results well. The robustness test demonstrated that peak femur loads were nearly identical to the M50-O model. Use of the detailed model brain within the simplified model demonstrated a paradigm for using the M50-OS to leverage aspects of the M50-O. Strain patterns for the 2 models showed consistent patterns but greater strains in the detailed model, with deviations thought to be the result of slightly different kinematics between models. The M50-OS with the deformable skull and brain exhibited a run time 4.75 faster than the M50-O on the same hardware.</p><p><b>Conclusions:</b> The simplified GHBMC model is intended to complement rather than replace the detailed M50-O model. It exhibited, on average, a 35-fold reduction in run time for a set of rigid impacts. The model can be used in a modular fashion with the M50-O and more broadly can be used as a platform for parametric studies or studies focused on specific body regions.</p></div

Lumbar vertebrae fracture injury risk in finite element reconstruction of CIREN and NASS frontal motor vehicle crashes

<p><b>Introduction:</b> The objective of this study was to reconstruct 4 real-world motor vehicle crashes (MVCs), 2 with lumbar vertebral fractures and 2 without vertebral fractures in order to elucidate the MVC and/or restraint variables that increase this injury risk.</p> <p><b>Methods:</b> A finite element (FE) simplified vehicle model (SVM) was used in conjunction with a previously developed semi-automated tuning method to arrive at 4 SVMs that were tuned to mimic frontal crash responses of a 2006 Chevrolet Cobalt, 2012 Ford Escape, 2007 Hummer H3, and 2002 Chevrolet Cavalier. Real-world crashes in the first 2 vehicles resulted in lumbar vertebrae fractures, whereas the latter 2 did not. Once each SVM was tuned to its corresponding vehicle, the Total HUman Model for Safety (THUMS) v4.01 was positioned in 120 precrash configurations in each SVM by varying 5 parameters using a Latin hypercube design (LHD) of experiments: seat track position, seatback angle, steering column angle, steering column telescoping position, and d-ring height. For each case, the event data recorder (EDR) crash pulse was used to apply kinematic boundary conditions to the model. By analyzing cross-sectional vertebral loads, vertebral bending moments, and maximum principal strain and stress in both cortical and trabecular bone, injury metric response as a function of posture and restraint parameters was computed.</p> <p><b>Results:</b> Tuning the SVM to specific vehicle models produced close matches between the simulated and experimental crash test responses for head, T6, and pelvis resultant acceleration; left and right femur loads; and shoulder and lap belt loads. Though vertebral load in the THUMS simulations was highly similar between injury cases and noninjury cases, the amount of bending moment was much higher for the injury cases. Seatback angle had a large effect on the maximum compressive load and bending moment in the lumbar spine, indicating the upward tilt of the seat pan in conjunction with precrash positioning may increase the likelihood of suffering lumbar injury even in frontal, planar MVCs.</p> <p><b>Conclusion:</b> In conclusion, precrash positioning has a large effect on lumbar injury metrics. The lack of lumbar injury criteria in regulatory crash tests may have led to inadvertent design of seat pans that work to apply axial force to the spinal column during frontal crashes.</p

Estimated Injury Risk for Specific Injuries and Body Regions in Frontal Motor Vehicle Crashes

<div><p><b>Objective:</b> Injury risk curves estimate motor vehicle crash (MVC) occupant injury risk from vehicle, crash, and/or occupant factors. Many vehicles are equipped with event data recorders (EDRs) that collect data including the crash speed and restraint status during a MVC. This study's goal was to use regulation-required data elements for EDRs to compute occupant injury risk for (1) specific injuries and (2) specific body regions in frontal MVCs from weighted NASS-CDS data.</p><p><b>Methods:</b> Logistic regression analysis of NASS-CDS single-impact frontal MVCs involving front seat occupants with frontal airbag deployment was used to produce 23 risk curves for specific injuries and 17 risk curves for Abbreviated Injury Scale (AIS) 2+ to 5+ body region injuries. Risk curves were produced for the following body regions: head and thorax (AIS 2+, 3+, 4+, 5+), face (AIS 2+), abdomen, spine, upper extremity, and lower extremity (AIS 2+, 3+). Injury risk with 95% confidence intervals was estimated for 15–105 km/h longitudinal delta-<i>V</i>s and belt status was adjusted for as a covariate.</p><p><b>Results:</b> Overall, belted occupants had lower estimated risks compared to unbelted occupants and the risk of injury increased as longitudinal delta-<i>V</i> increased. Belt status was a significant predictor for 13 specific injuries and all body region injuries with the exception of AIS 2+ and 3+ spine injuries. Specific injuries and body region injuries that occurred more frequently in NASS-CDS also tended to carry higher risks when evaluated at a 56 km/h longitudinal delta-<i>V</i>. In the belted population, injury risks that ranked in the top 33% included 4 upper extremity fractures (ulna, radius, clavicle, carpus/metacarpus), 2 lower extremity fractures (fibula, metatarsal/tarsal), and a knee sprain (2.4–4.6% risk). Unbelted injury risks ranked in the top 33% included 4 lower extremity fractures (femur, fibula, metatarsal/tarsal, patella), 2 head injuries with less than one hour or unspecified prior unconsciousness, and a lung contusion (4.6–9.9% risk). The 6 body region curves with the highest risks were for AIS 2+ lower extremity, upper extremity, thorax, and head injury and AIS 3+ lower extremity and thorax injury (15.9–43.8% risk).</p><p><b>Conclusions:</b> These injury risk curves can be implemented into advanced automatic crash notification (AACN) algorithms that utilize vehicle EDR measurements to predict occupant injury immediately following a MVC. Through integration with AACN, these injury risk curves can provide emergency medical services (EMS) and other patient care providers with information on suspected occupant injuries to improve injury detection and patient triage.</p></div

Computational modeling and analysis of thoracolumbar spine fractures in frontal crash reconstruction

<p><b>Objective:</b> This study aimed to reconstruct 11 motor vehicle crashes (6 with thoracolumbar fractures and 5 without thoracolumbar fractures) and analyze the fracture mechanism, fracture predictors, and associated parameters affecting thoracolumbar spine response.</p> <p><b>Methods:</b> Eleven frontal crashes were reconstructed with a finite element simplified vehicle model (SVM). The SVM was tuned to each case vehicle and the Total HUman Model for Safety (THUMS) Ver. 4.01 was scaled and positioned in a baseline configuration to mimic the documented precrash driver posture. The event data recorder crash pulse was applied as a boundary condition. For the 6 thoracolumbar fracture cases, 120 simulations to quantify uncertainty and response variation were performed using a Latin hypercube design of experiments (DOE) to vary seat track position, seatback angle, steering column angle, steering column position, and D-ring height. Vertebral loads and bending moments were analyzed, and lumbar spine indices (unadjusted and age-adjusted) were developed to quantify the combined loading effect. Maximum principal strain and stress data were collected in the vertebral cortical and trabecular bone. DOE data were fit to regression models to examine occupant positioning and thoracolumbar response correlations.</p> <p><b>Results:</b> Of the 11 cases, both the vertebral compression force and bending moment progressively increased from superior to inferior vertebrae. Two thoracic spine fracture cases had higher average compression force and bending moment across all thoracic vertebral levels, compared to 9 cases without thoracic spine fractures (force: 1,200.6 vs. 640.8 N; moment: 13.7 vs. 9.2 Nm). Though there was no apparent difference in bending moment at the L1–L2 vertebrae, lumbar fracture cases exhibited higher vertebral bending moments in L3–L4 (fracture/nonfracture: 45.7 vs. 33.8 Nm). The unadjusted lumbar spine index correctly predicted thoracolumbar fracture occurrence for 9 of the 11 cases (sensitivity = 1.0; specificity = 0.6). The age-adjusted lumbar spine index correctly predicted thoracolumbar fracture occurrence for 10 of the 11 cases (sensitivity = 1.0; specificity = 0.8). The age-adjusted principal stress in the trabecular bone was an excellent indicator of fracture occurrence (sensitivity = 1.0; specificity = 1.0). A rearward seat track position and reclined seatback increased the thoracic spine bending moment by 111–329%. A more reclined seatback increased the lumbar force and bending moment by 16–165% and 67–172%, respectively.</p> <p><b>Conclusions:</b> This study provided a computational framework for assessing thoracolumbar fractures and also quantified the effect of precrash driver posture on thoracolumbar response. Results aid in the evaluation of motor vehicle crash–induced vertebral fractures and the understanding of factors contributing to fracture risk.</p

Lumbar Bone Mineral Density Phantomless Computed Tomography Measurements and Correlation with Age and Fracture Incidence

<div><p><b>Objective</b>: Low bone quality is a contributing factor to motor vehicle crash (MVC) injury. Quantification of occupant bone mineral density (BMD) is important from an injury causation standpoint. The first aim of this study was to validate a technique for measuring lumbar volumetric BMD (vBMD) from phantomless computed tomography (CT) scans. The second aim was to apply the validated phantomless technique to quantify lumbar vBMD in Crash Injury Research and Engineering Network (CIREN) occupants for correlation with age, fracture incidence, and osteopenia/osteoporosis diagnoses.</p><p><b>Methods</b>: Quantitative CT (qCT) and dual-energy X-ray absorptiometry (DXA) were collected prospectively for 50 subjects and used to validate a technique to measure vBMD from 281 phantomless CT scans of CIREN occupants. Hounsfield unit (HU) measurements were collected from the L1–L5 vertebrae, right psoas major muscle, and anterior subcutaneous fat for all subjects and from 3 phantom ports with known mg/cc calcium hydroxyapatite values for the validation group. qCT calibration was accomplished using regressions between the phantom HU and mg/cc values to convert L1–L5 HU values to mg/cc. A phantomless calibration technique was developed where the fat and muscle HU values were linearly regressed against fat (−69 mg/cc) and muscle (77 mg/cc) to establish a conversion for L1–L5 HU measurements to mg/cc. vBMD calculated from qCT versus the phantomless method was compared for the 50 subjects to assess agreement and a mg/cc osteopenia threshold was established using DXA T-scores. CIREN HU measurements were converted to mg/cc using the phantomless technique and the mg/cc osteopenia threshold was used to compare vBMD to age, fracture incidence, and osteopenia comorbidity classifications in CIREN.</p><p><b>Results</b>: Linear regression of lumbar vBMD derived from the qCT versus phantomless calibrations showed excellent agreement (<i>R</i>² = 0.87, <i>P</i> <.0001). A 145 mg/cc threshold for osteopenia was established (sensitivity = 1, specificity = 0.57) and 44 CIREN occupants had vBMD below this threshold. Of these 44 occupants, 64% were not classified as osteopenic in CIREN, but vBMD suggested undiagnosed osteopenia. Age was negatively correlated with vBMD in both sexes (<i>P</i> <.0001) and CIREN occupants with less than 145 mg/cc vBMD sustained an average 1.7 additional rib/sternum fractures (<i>P</i> =.036).</p><p><b>Conclusions</b>: Because lumbar vBMD was estimated from phantomless CT scans with accuracy similar to qCT, the phantomless technique can be broadly applied to both prospectively and retrospectively assess patient bone quality for research and clinical studies related to MVCs, falls, and aging.</p></div

Mortality Risk in Pediatric Motor Vehicle Crash Occupants: Accounting for Developmental Stage and Challenging Abbreviated Injury Scale Metrics

<div><p><b>Objective:</b> Survival risk ratios (SRRs) and their probabilistic counterpart, mortality risk ratios (MRRs), have been shown to be at odds with Abbreviated Injury Scale (AIS) severity scores for particular injuries in adults. SRRs have been validated for pediatrics but have not been studied within the context of pediatric age stratifications. We hypothesized that children with similar motor vehicle crash (MVC) injuries may have different mortality risks (MR) based upon developmental stage and that these MRs may not correlate with AIS severity.</p><p><b>Methods:</b> The NASS-CDS 2000–2011 was used to define the top 95% most common AIS 2+ injuries among MVC occupants in 4 age groups: 0–4, 5–9, 10–14, and 15–18 years. Next, the National Trauma Databank 2002–2011 was used to calculate the MR (proportion of those dying with an injury to those sustaining the injury) and the co-injury-adjusted MR (MR_MAIS) for each injury within 6 age groups: 0–4, 5–9, 10–14, 15–18, 0–18, and 19+ years. MR differences were evaluated between age groups aggregately, between age groups based upon anatomic injury patterns and between age groups on an individual injury level using nonparametric Wilcoxon tests and chi-square or Fisher's exact tests as appropriate. Correlation between AIS and MR within each age group was also evaluated.</p><p><b>Results:</b> MR and MR_MAIS distributions of the most common AIS 2+ injuries were right skewed. Aggregate MR of these most common injuries varied between the age groups, with 5- to 9-year-old and 10- to 14-year-old children having the lowest MRs and 0- to 4-year-old and 15- to 18-year-old children and adults having the highest MRs (all <i>P</i> <.05). Head and thoracic injuries imparted the greatest mortality risk in all age groups with median MR_MAIS ranging from 0 to 6% and 0 to 4.5%, respectively. Injuries to particular body regions also varied with respect to MR based upon age. For example, thoracic injuries in adults had significantly higher MR_MAIS than such injuries among 5- to 9-year-olds and 10- to 14-year-olds (<i>P</i> =.04; <i>P</i> <.01). Furthermore, though AIS was positively correlated with MR within each age group, less correlation was seen for children than for adults. Large MR variations were seen within each AIS grade, with some lower AIS severity injuries demonstrating greater MRs than higher AIS severity injuries. As an example, MR_MAIS in 0- to 18-year-olds was 0.4% for an AIS 3 radius fracture versus 1.4% for an AIS 2 vault fracture.</p><p><b>Conclusions:</b> Trauma severity metrics are important for outcome prediction models and can be used in pediatric triage algorithms and other injury research. Trauma severity may vary for similar injuries based upon developmental stage, and this difference should be reflected in severity metrics. The MR-based data-driven determination of injury severity in pediatric occupants of different age cohorts provides a supplement or an alternative to AIS severity classification for pediatric occupants in MVCs.</p></div