Multicenter analysis of CIREN occupant lumbar bone mineral density and correlation with age and fracture incidence

OBJECTIVE

This study aimed to quantify lumbar volumetric bone mineral density (vBMD) for 873 seriously injured Crash Injury Research and Engineering Network (CIREN) motor vehicle crash occupants (372 male, 501 female) from 8 centers using phantomless computed tomography scans and to associate vBMD with age, fracture incidence, and osteopenia/osteoporosis diagnoses. The novelty of this work is that it associates vBMD with region of injury by applying an established method for vBMD measurement using phantomless computed tomography (CT).

METHODS

A validated phantomless CT calibration method that uses patient-specific fat and muscle measurements to calibrate vBMD measured from the L1-L5 trabeculae was applied on 873 occupants from various CIREN centers. CT-measured lumbar vBMD < 145 mg/cc is indicative of osteopenia using a published threshold. CIREN occupant lumbar vBMD in milligrams per cubic centimeter was regressed against age, osteopenia/osteoporosis comorbidities, height, weight, body mass index (BMI), and the incidence of fracture in vertebral (cervical, thoracic, lumbar) and rib/sternum regions.

RESULTS

Among the 873 occupants analyzed, 11% (92 occupants) were diagnosed as osteopenic in CIREN. Of these 92 occupants, 42% (39 occupants) had normal vBMD measures (≥145 mg/cc), suggesting possible misclassification in CIREN. Of the 134 occupants classified as osteopenic in vBMD analysis, 60% were not classified as osteopenic in CIREN, suggesting undiagnosed osteopenia, and 40% were correctly classified in CIREN. Age was negatively correlated with vBMD (P <.0001) and occupants with <145 mg/cc vBMD sustained a median number of 2 rib/sternum fractures compared to a median value of 0 rib/sternum fractures for the ≥145 mg/cc vBMD group (P <.0001). Vertebral fracture analysis revealed that the thoracolumbar region was the most common region of injury in the spine. Though the incidence of fracture was not significantly different in the thoracic (10% versus 6%, P =.122) and lumbar (16% versus 13%, P =.227) regions between the 2 bone quality groups, the proportion of thoracolumbar fractures was significantly higher in occupants with <145 mg/cc vBMD versus occupants with ≥145 mg/cc vBMD (24% versus 17%, P =.043).

CONCLUSIONS

Low lumbar vertebral bone quality is associated with an increased number of rib/sternum fractures and a greater incidence of thoracolumbar vertebral body fractures within the CIREN population analyzed.

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

INTRODUCTION

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.

METHODS

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.

RESULTS

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.

CONCLUSION

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.

Subconcussive impacts and imaging findings over a season of contact sports

The effect of repeated subconcussive head impacts in youth and high school sports on the developing brain is poorly understood. Emerging neuroimaging data correlated with biomechanical exposure metrics are beginning to demonstrate relationships across a variety of modalities. The long-term consequences of these changes are unknown. A review of the currently available literature on the effect of subconcussive head impacts on youth and high school-age male football players provides compelling evidence for more focused studies of these effects in these vulnerable populations.

Concussions are known to cause clinical symptoms, which are especially concerning for youth and high school athletes. However, the effects of repeated head impacts that do not cause a diagnosed concussion, known as subconcussive head impacts, are currently unknown. Recent research has identified similar changes in the brain following repeated nonconcussive impacts to the head, once thought to be caused only by the occurrence of concussion with the presence of clinical symptoms. Similarly, many reports suggest that a higher exposure to head impacts is associated with a greater amount of structural and/or functional changes in the brain. Given the similar effects on the brain, with or without symptoms, more work is needed to determine the long-term effects of subconcussive head impacts on individual athletes, particularly in the youth and high school age population.

Abnormalities in Diffusional Kurtosis Metrics Related to Head Impact Exposure in a Season of High School Varsity Football

The purpose of this study was to determine whether the effects of cumulative head impacts during a season of high school football produce changes in diffusional kurtosis imaging (DKI) metrics in the absence of clinically diagnosed concussion. Subjects were recruited from a high school football team and were outfitted with the Head Impact Telemetry System (HITS) during all practices and games. Biomechanical head impact exposure metrics were calculated, including: total impacts, summed acceleration, and Risk Weighted Cumulative Exposure (RWE). Twenty-four players completed pre- and post-season magnetic resonance imaging, including DKI; players who experienced clinical concussion were excluded. Fourteen subjects completed pre- and post-season Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT). DKI-derived metrics included mean kurtosis (MK), axial kurtosis (K axial), and radial kurtosis (K radial), and white matter modeling (WMM) parameters included axonal water fraction, tortuosity of the extra-axonal space, extra-axonal diffusivity (D_e axial and radial), and intra-axonal diffusivity (D_a). These metrics were used to determine the total number of abnormal voxels, defined as 2 standard deviations above or below the group mean. Linear regression analysis revealed a statistically significant relationship between RWE combined probability (RWE_CP) and MK. Secondary analysis of other DKI-derived and WMM metrics demonstrated statistically significant linear relationships with RWE_CP after covariate adjustment. These results were compared with the results of DTI-derived metrics from the same imaging sessions in this exact same cohort. Several of the DKI-derived scalars (D_a, MK, K axial, and K radial) explained more variance, compared with RWE_CP, suggesting that DKI may be more sensitive to subconcussive head impacts. No significant relationships between DKI-derived metrics and ImPACT measures were found. It is important to note that the pathological implications of these metrics are not well understood. In summary, we demonstrate a single season of high school football can produce DKI measurable changes in the absence of clinically diagnosed concussion.

An Injury Severity-, Time Sensitivity-, and Predictability-Based Advanced Automatic Crash Notification Algorithm Improves Motor Vehicle Crash Occupant Triage

BACKGROUND

Advanced Automatic Crash Notification algorithms use vehicle telemetry measurements to predict risk of serious motor vehicle crash injury. The objective of the study was to develop an Advanced Automatic Crash Notification algorithm to reduce response time, increase triage efficiency, and improve patient outcomes by minimizing undertriage (<5%) and overtriage (<50%), as recommended by the American College of Surgeons.

STUDY DESIGN

A list of injuries associated with a patient's need for Level I/II trauma center treatment known as the Target Injury List was determined using an approach based on 3 facets of injury: severity, time sensitivity, and predictability. Multivariable logistic regression was used to predict an occupant's risk of sustaining an injury on the Target Injury List based on crash severity and restraint factors for occupants in the National Automotive Sampling System - Crashworthiness Data System 2000-2011. The Advanced Automatic Crash Notification algorithm was optimized and evaluated to minimize triage rates, per American College of Surgeons recommendations.

RESULTS

The following rates were achieved: <50% overtriage and <5% undertriage in side impacts and 6% to 16% undertriage in other crash modes. Nationwide implementation of our algorithm is estimated to improve triage decisions for 44% of undertriaged and 38% of overtriaged occupants. Annually, this translates to more appropriate care for >2,700 seriously injured occupants and reduces unnecessary use of trauma center resources for >162,000 minimally injured occupants.

CONCLUSIONS

The algorithm could be incorporated into vehicles to inform emergency personnel of recommended motor vehicle crash triage decisions. Lower under- and overtriage was achieved, and nationwide implementation of the algorithm would yield improved triage decision making for an estimated 165,000 occupants annually.

Evaluation of Skull Cortical Thickness Changes With Age and Sex From Computed Tomography Scans

Head injuries resulting from motor vehicle crashes (MVC) are extremely common, yet the details of the mechanism of injury remain to be well characterized. Skull deformation is believed to be a contributing factor to some types of traumatic brain injury (TBI). Understanding biomechanical contributors to skull deformation would provide further insight into the mechanism of head injury resulting from blunt trauma. In particular, skull thickness is thought be a very important factor governing deformation of the skull and its propensity for fracture. Previously, age- and sex-based skull cortical thickness changes were difficult to evaluate based on the need for cadaveric skulls. In this cross-sectional study, skull thickness changes with age and sex have been evaluated at homologous locations using a validated cortical density-based algorithm to accurately quantify cortical thickness from 123 high-resolution clinical computed tomography (CT) scans. The flat bones of the skull have a sandwich structure; therefore, skull thickness was evaluated for the inner and outer tables as well the full thickness. General trends indicated an increase in the full skull thickness, mostly attributed to an increase in the thickness of the diploic layer; however, these trends were not found to be statistically significant. There was a significant relationship between cortical thinning and age for both tables of the frontal, occipital, and parietal bones ranging between a 36% and 60% decrease from ages 20 to 100 years in females, whereas males exhibited no significant changes. Understanding how cortical and full skull thickness changes with age from a wide range of subjects can have implications in improving the biofidelity of age- and sex-specific finite element models and therefore aid in the prediction and understanding of TBI from impact and blast injuries.

Development and validation of an atlas-based finite element brain model

Traumatic brain injury is a leading cause of disability and injury-related death. To enhance our ability to prevent such injuries, brain response can be studied using validated finite element (FE) models. In the current study, a high-resolution, anatomically accurate FE model was developed from the International Consortium for Brain Mapping brain atlas. Due to wide variation in published brain material parameters, optimal brain properties were identified using a technique called Latin hypercube sampling, which optimized material properties against three experimental cadaver tests to achieve ideal biomechanics. Additionally, falx pretension and thickness were varied in a lateral impact variation. The atlas-based brain model (ABM) was subjected to the boundary conditions from three high-rate experimental cadaver tests with different material parameter combinations. Local displacements, determined experimentally using neutral density targets, were compared to displacements predicted by the ABM at the same locations. Error between the observed and predicted displacements was quantified using CORrelation and Analysis (CORA), an objective signal rating method that evaluates the correlation of two curves. An average CORA score was computed for each variation and maximized to identify the optimal combination of parameters. The strongest relationships between CORA and material parameters were observed for the shear parameters. Using properties obtained through the described multiobjective optimization, the ABM was validated in three impact configurations and shows good agreement with experimental data. The final model developed in this study consists of optimized brain material properties and was validated in three cadaver impacts against local brain displacement data.

Finite element comparison of human and Hybrid III responses in a frontal impact

The improvement of finite element (FE) Human Body Models (HBMs) has made them valuable tools for investigating restraint interactions compared to anthropomorphic test devices (ATDs). The objective of this study was to evaluate the effect of various combinations of safety restraint systems on the sensitivity of thoracic injury criteria using matched ATD and Human Body Model (HBM) simulations at two crash severities. A total of seven (7) variables were investigated: 3-point belt with two (2) load limits, frontal airbag, knee bolster airbag, a buckle pretensioner, and two (2) delta-v's - 40kph and 50kph. Twenty four (24) simulations were conducted for the Hybrid III ATD FE model and repeated with a validated HBM for 48 total simulations. Metrics tested in these conditions included sternum deflection, chest acceleration, chest excursion, Viscous Criteria (V*C) criteria, pelvis acceleration, pelvis excursion, and femur forces. Additionally, chest band deflection and rib strain distribution were measured in the HBM for additional restraint condition discrimination. The addition of a frontal airbag had the largest effect on the occupant chest metrics with an increase in chest compression and acceleration but a decrease in excursion. While the THUMS and Hybrid III occupants demonstrated the same trend in the chest compression measurements, there were conflicting results in the V*C, acceleration, and displacement metrics. Similarly, the knee bolster airbag had the largest effect on the pelvis with a decrease in acceleration and excursion. With a knee bolster airbag the simulated occupants gave conflicting results, the THUMS had a decrease in femur force and the ATD had an increase. Preferential use of dummies or HBM's is not debated; however, this study highlights the ability of HBM metrics to capture additional chest response metrics.

Development and Validation of an Older Occupant Finite Element Model of a Mid-Sized Male for Investigation of Age-related Injury Risk

The aging population is a growing concern as the increased fragility and frailty of the elderly results in an elevated incidence of injury as well as an increased risk of mortality and morbidity. To assess elderly injury risk, age-specific computational models can be developed to directly calculate biomechanical metrics for injury. The first objective was to develop an older occupant Global Human Body Models Consortium (GHBMC) average male model (M50) representative of a 65 year old (YO) and to perform regional validation tests to investigate predicted fractures and injury severity with age. Development of the GHBMC M50 65 YO model involved implementing geometric, cortical thickness, and material property changes with age. Regional validation tests included a chest impact, a lateral impact, a shoulder impact, a thoracoabdominal impact, an abdominal bar impact, a pelvic impact, and a lateral sled test. The second objective was to investigate age-related injury risks by performing a frontal US NCAP simulation test with the GHBMC M50 65 YO and the GHBMC M50 v4.2 models. Simulation results were compared to the GHBMC M50 v4.2 to evaluate the effect of age on occupant response and risk for head injury, neck injury, thoracic injury, and lower extremity injury. Overall, the GHBMC M50 65 YO model predicted higher probabilities of AIS 3+ injury for the head and thorax.

Image segmentation and registration algorithm to collect thoracic skeleton semilandmarks for characterization of age and sex-based thoracic morphology variation

Thoracic anthropometry variations with age and sex have been reported and likely relate to thoracic injury risk and outcome. The objective of this study was to collect a large volume of homologous semilandmark data from the thoracic skeleton for the purpose of quantifying thoracic morphology variations for males and females of ages 0-100 years. A semi-automated image segmentation and registration algorithm was applied to collect homologous thoracic skeleton semilandmarks from 343 normal computed tomography (CT) scans. Rigid, affine, and symmetric diffeomorphic transformations were used to register semilandmarks from an atlas to homologous locations in the subject-specific coordinate system. Homologous semilandmarks were successfully collected from 92% (7077) of the ribs and 100% (187) of the sternums included in the study. Between 2700 and 11,000 semilandmarks were collected from each rib and sternum and over 55 million total semilandmarks were collected from all subjects. The extensive landmark data collected more fully characterizes thoracic skeleton morphology across ages and sexes. Characterization of thoracic morphology with age and sex may help explain variations in thoracic injury risk and has important implications for vulnerable populations such as pediatrics and the elderly.

Evaluation of developmental metrics for utilization in a pediatric advanced automatic crash notification algorithm

OBJECTIVE

Appropriate treatment at designated trauma centers (TCs) improves outcomes among injured children after motor vehicle crashes (MVCs). Advanced Automatic Crash Notification (AACN) has shown promise in improving triage to appropriate TCs. Pediatric-specific AACN algorithms have not yet been created. To create such an algorithm, it will be necessary to include some metric of development (age, height, or weight) as a covariate in the injury risk algorithm. This study sought to determine which marker of development should serve as a covariate in such an algorithm and to quantify injury risk at different levels of this metric.

METHODS

A retrospective review of occupants age < 19 years within the MVC data set NASS-CDS 2000-2011 was performed. R(2) values of logistic regression models using age, height, or weight to predict 18 key injury types were compared to determine which metric should be used as a covariate in a pediatric AACN algorithm. Clinical judgment, literature review, and chi-square analysis were used to create groupings of the chosen metric that would discriminate injury patterns. Adjusted odds of particular injury types at the different levels of this metric were calculated from logistic regression while controlling for gender, vehicle velocity change (delta V), belted status (optimal, suboptimal, or unrestrained), and crash mode (rollover, rear, frontal, near-side, or far-side).

RESULTS

NASS-CDS analysis produced 11,541 occupants age < 19 years with nonmissing data. Age, height, and weight were correlated with one another and with injury patterns. Age demonstrated the best predictive power in injury patterns and was categorized into bins of 0-4 years, 5-9 years, 10-14 years, and 15-18 years. Age was a significant predictor of all 18 injury types evaluated even when controlling for all other confounders and when controlling for age- and gender-specific body mass index (BMI) classifications. Adjusted odds of key injury types with respect to these age categorizations revealed that younger children were at increased odds of sustaining Abbreviated Injury Scale (AIS) 2+ and 3+ head injuries and AIS 3+ spinal injuries, whereas older children were at increased odds of sustaining thoracic fractures, AIS 3+ abdominal injuries, and AIS 2+ upper and lower extremity injuries.

CONCLUSIONS

The injury patterns observed across developmental metrics in this study mirror those previously described among children with blunt trauma. This study identifies age as the metric best suited for use in a pediatric AACN algorithm and utilizes 12 years of data to provide quantifiable risks of particular injuries at different levels of this metric. This risk quantification will have important predictive purposes in a pediatric-specific AACN algorithm.

Head and neck response of a finite element anthropomorphic test device and human body model during a simulated rotary-wing aircraft impact

A finite element (FE) simulation environment has been developed to investigate aviator head and neck response during a simulated rotary-wing aircraft impact using both an FE anthropomorphic test device (ATD) and an FE human body model. The head and neck response of the ATD simulation was successfully validated against an experimental sled test. The majority of the head and neck transducer time histories received a CORrelation and analysis (CORA) rating of 0.7 or higher, indicating good overall correlation. The human body model simulation produced a more biofidelic head and neck response than the ATD experimental test and simulation, including change in neck curvature. While only the upper and lower neck loading can be measured in the ATD, the shear force, axial force, and bending moment were reported for each level of the cervical spine in the human body model using a novel technique involving cross sections. This loading distribution provides further insight into the biomechanical response of the neck during a rotary-wing aircraft impact.

Predicting patients that require care at a trauma center: analysis of injuries and other factors

INTRODUCTION

The detection of occult or unpredictable injuries in motor vehicle crashes (MVCs) is crucial in correctly triaging patients and thus reducing fatalities. The purpose of the study was to develop a metric that indicates the likelihood that an injury sustained in a MVC would require management at a Level I/II trauma centre (TC) versus a non-trauma centre (non-TC).

METHODS

Transfer Scores (TSs) were computed for 240 injuries that comprise the top 95% most frequently occurring injuries in the National Automotive Sampling System-Crashworthiness Data System (NASS-CDS) with an Abbreviated Injury Scale (AIS) severity of 2 or greater. A TS for each injury was computed using the proportions of patients involved in a MVC from the National Inpatient Sample (NIS) that were transferred to a TC or managed at a non-TC. Similarly, a TSMAIS that excludes patients with higher severity co-injuries was calculated using the proportion of patients with a maximum AIS (MAIS) equal to the AIS severity of a given injury.

RESULTS

The results indicated for injuries of a given AIS severity, body region, and injury type, there were large variations in the TSMAIS. Overall results demonstrated higher TSMAIS values when injuries were internal, haemorrhagic, intracranial or of moderate severity (AIS 3-5). Specifically, injuries to the head possessed a TSMAIS that ranged from 0.000 to 0.889, with head injuries of AIS 3-5 severities being the most likely to be transferred.

DISCUSSION AND CONCLUSIONS

The analysis indicated that the TSMAIS is not solely correlated with AIS severity and therefore it captures other important aspects of injury such as predictability and trauma system capabilities. The TS and TSMAIS can be useful in advanced automatic crash notification (AACN) research for the detection of highly unpredictable injuries in MVCs that require direct transport to a TC.

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

OBJECTIVE

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.

METHODS

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 (MRMAIS) 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.

RESULTS

MR and MRMAIS 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 P <.05). Head and thoracic injuries imparted the greatest mortality risk in all age groups with median MRMAIS 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 MRMAIS than such injuries among 5- to 9-year-olds and 10- to 14-year-olds (P =.04; P <.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, MRMAIS in 0- to 18-year-olds was 0.4% for an AIS 3 radius fracture versus 1.4% for an AIS 2 vault fracture.

CONCLUSIONS

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.

Development of a computationally efficient full human body finite element model

INTRODUCTION

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

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

OBJECTIVE

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.

METHODS

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.

RESULTS

Linear regression of lumbar vBMD derived from the qCT versus phantomless calibrations showed excellent agreement (R(2) = 0.87, P <.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 (P <.0001) and CIREN occupants with less than 145 mg/cc vBMD sustained an average 1.7 additional rib/sternum fractures (P =.036).

CONCLUSIONS

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.

Age- and sex-specific thorax finite element model development and simulation

OBJECTIVE

The shape, size, bone density, and cortical thickness of the thoracic skeleton vary significantly with age and sex, which can affect the injury tolerance, especially in at-risk populations such as the elderly. Computational modeling has emerged as a powerful and versatile tool to assess injury risk. However, current computational models only represent certain ages and sexes in the population. The purpose of this study was to morph an existing finite element (FE) model of the thorax to depict thorax morphology for males and females of ages 30 and 70 years old (YO) and to investigate the effect on injury risk.

METHODS

Age- and sex-specific FE models were developed using thin-plate spline interpolation. In order to execute the thin-plate spline interpolation, homologous landmarks on the reference, target, and FE model are required. An image segmentation and registration algorithm was used to collect homologous rib and sternum landmark data from males and females aged 0-100 years. The Generalized Procrustes Analysis was applied to the homologous landmark data to quantify age- and sex-specific isolated shape changes in the thorax. The Global Human Body Models Consortium (GHBMC) 50th percentile male occupant model was morphed to create age- and sex-specific thoracic shape change models (scaled to a 50th percentile male size). To evaluate the thoracic response, 2 loading cases (frontal hub impact and lateral impact) were simulated to assess the importance of geometric and material property changes with age and sex.

RESULTS

Due to the geometric and material property changes with age and sex, there were observed differences in the response of the thorax in both the frontal and lateral impacts. Material property changes alone had little to no effect on the maximum thoracic force or the maximum percent compression. With age, the thorax becomes stiffer due to superior rotation of the ribs, which can result in increased bone strain that can increase the risk of fracture. For the 70-YO models, the simulations predicted a higher number of rib fractures in comparison to the 30-YO models. The male models experienced more superior rotation of the ribs in comparison to the female models, which resulted in a higher number of rib fractures for the males.

CONCLUSION

In this study, age- and sex-specific thoracic models were developed and the biomechanical response was studied using frontal and lateral impact simulations. The development of these age- and sex-specific FE models of the thorax will lead to an improved understanding of the complex relationship between thoracic geometry, age, sex, and injury risk.

Finite element model prediction of pulmonary contusion in vehicle-to-vehicle simulations of real-world crashes

OBJECTIVE

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.

METHOD

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.

RESULTS

When the thresholds were evaluated using volumetric criteria, first principal strain was the metric with the least variation in the FEM prediction of PC.

CONCLUSIONS

A preliminary threshold for maximum crush was calculated to predict a clinically significant volume of pulmonary contusion.

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

OBJECTIVE

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.

METHOD

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.

RESULTS

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.

CONCLUSIONS

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.

Mesh Smoothing Algorithm Applied to a Finite Element Model of the Brain for Improved Brain-Skull Interface

The brain-skull interface plays an important role in the strain and pressure response of the brain due to impact. In this study, a finite element (FE) model was developed from a brain atlas, representing an adult brain, by converting each 1mm isotropic voxel into a single element of the same size using a custom code developed in MATLAB. This model includes the brain (combined cerebrum and cerebellum), cerebrospinal fluid (CSF), ventricles, and a rigid skull. A voxel-based approach to develop a FE model causes the outer surface of each part to be stair-stepped, which may affect the stress and strain measurements at interfaces between parts. To improve the interaction between the skull, CSF, and brain surfaces, a previously developed mesh smoothing algorithm based on a Laplacian non-shrinking smoothing algorithm was applied to the FE model. This algorithm not only applies smoothing to the surface of the model, but also to the interfaces between the brain, CSF, and skull, while preserving volume and element quality. Warpage, jacobian, aspect ratio, and skew were evaluated and reveal that >99% of the elements retain good element quality. Future work includes implementation of contact definitions to accurately represent the brain-skull interface and to ultimately better understand and predict head injury.

Preliminary Development and Validation of an Atlas-Based Finite Element Brain Model

Traumatic brain injury (TBI) is a leading cause of disability and injury-related death, accounting for nearly one third of all injury-related deaths. To prevent and understand these types of injuries, finite element models can be employed. In this study, an anatomically accurate finite element model was developed from the International Consortium for Brain Mapping (ICBM) using a voxel-based mesh generation approach. The aim of this study was to compare relative brain displacement of the atlas-based brain model (ABM) to cadaveric data. In these experiments, neutral density targets (NDTs) were implanted in the brain and their relative motion with respect to the skull was recorded. The same boundary conditions were applied to ABM and the relative displacements of the nodes nearest to the physical location of each NDT were computed. Initial simulation and validation show good agreement with experimental data. The data obtained in this study and further development of this model will help us understand the biomechanics of head injury as well as provide a tool to predict and prevent brain injury.

New Methodology for an Expert-Designed Map From International Classification of Diseases (ICD) to Abbreviated Injury Scale (AIS) 3+ Severity Injury

OBJECTIVE

There has been a longstanding desire for a map to convert International Classification of Diseases (ICD) injury codes to Abbreviated Injury Scale (AIS) codes to reflect the severity of those diagnoses. The Association for the Advancement of Automotive Medicine (AAAM) was tasked by European Union representatives to create a categorical map classifying diagnoses codes as serious injury (Abbreviated Injury Scale [AIS] 3+), minor/moderate injury (AIS 1/2), or indeterminate. This study's objective was to map injury-related ICD-9-CM (clinical modification) and ICD-10-CM codes to these severity categories.

METHODS

Approximately 19,000 ICD codes were mapped, including injuries from the following categories: amputations, blood vessel injury, burns, crushing injury, dislocations/sprains/strains, foreign body, fractures, internal organ, nerve/spinal cord injury, intracranial, laceration, open wounds, and superficial injury/contusion. Two parallel activities were completed to create the maps: (1) An in-person expert panel and (2) an electronic survey. The panel consisted of expert users of AIS and ICD from North America, the United Kingdom, and Australia. The panel met in person for 5 days, with follow-up virtual meetings to create and revise the maps. Additional qualitative data were documented to resolve potential discrepancies in mapping. The electronic survey was completed by 95 injury coding professionals from North America, Spain, Australia, and New Zealand over 12 weeks. ICD-to-AIS maps were created for: ICD-9-CM and ICD-10-CM. Both maps indicated whether the corresponding AIS 2005/Update 2008 severity score for each ICD code was AIS 3+, 1/2, or indeterminable. Though some ICD codes could be mapped to multiple AIS codes, the maximum severity of all potentially mapped injuries determined the final severity categorization.

RESULTS

The in-person panel consisted of 13 experts, with 11 Certified AIS specialists (CAISS) with a median of 8 years and an average of 15 years of coding experience. Consensus was reached for AIS severity categorization for all injury-related ICD codes. There were 95 survey respondents, with a median of 8 years of injury coding experience. Approximately 15 survey responses were collected per ICD code. Results from the 2 activities were compared, and any discrepancies were resolved using additional qualitative and quantitative data from the in-person panel and survey results, respectively.

CONCLUSIONS

Robust maps of ICD-9-CM and ICD-10-CM injury codes to AIS severity categories (3+ versus <3) were successfully created from an in-person panel discussion and electronic survey. These maps provide a link between the common ICD diagnostic lexicons and the AIS severity coding system and are of value to injury researchers, public health scientists, and epidemiologists using large databases without available AIS coding.