Injury Probability Curves Research Articles

Human pelvis injury risk curves from underbody blast impact

IntroductionUnderbody blast loading can result in injuries to the pelvis and the lumbosacral spine. The purpose of this study was to determine human tolerance in this region based on survival...

Severe Calcaneus Injury Probability Curves Due to Under-Body Blast.

The lower extremity is the most frequently injured body region to mounted soldiers during underbody blast (UBB) events. UBB events often produce large deformations of the floor and subsequent acceleration of the lower limb that are not sufficiently mitigated by the combat boot, leaving the calcaneus bone vulnerable to injury. Biomechanical experiments simulating UBB loading scenarios were conducted in a laboratory environment using isolated postmortem human subject (PMHS) leg components. Each leg component was tested twice: one sub-injurious test followed by a injury-targeted test. This enabled the use of interval censoring for each specimen in the survival statistical analysis to generate the human injury probability curves (HIPCs). Foot contact forces were measured in both the hindfoot and forefoot. Strains and acoustic emission signals at the calcaneus and distal tibia were utilized to determine injury timing. The footplate velocities of the injury tests ranged 8-13 m/s with time-to-peak velocity of 1.8-2.5 ms while the velocities of non-injury tests ranged from 4 to 6 m/s with the same time-to-peak. The majority of the injuries were severe calcaneus fractures (Sanders III-IV). Secondary injuries included fractures to the distal tibia, talus, cuboid and cuneiform. These injury outcomes were found to be consistent with those reported in UBB injury literature. The HIPCs for the severe calcaneus fracture were developed using the vertical heel contact force as the injury correlation measure through survival analysis statistical method in the form of lognormal function. This work represents the first set of HIPCs dedicated to the severe calcaneus fracture using the biomechanical force measurement closest to the injury location. This injury probability curve will enable biomechanical response validation of computational models, development of ATD injury assessment reference curve, and injury prediction capability for computational models or ATDs in the UBB environment.

An Improved Method for Developing Injury Risk Curves Using the Brier Metric Score.

Many injury metrics are routinely proposed from measured or derived quantities from biomechanical experiments using post mortem human subjects (PMHS). The existing literature did not provide guidance on deciding between parameters collected in an experiment that would be best to use for the development of human injury probability curves (HIPC). The objective of this study was to use the Brier Metric Score (BMS) to identify the most appropriate metric from an experiment that predicts injury outcomes. The Brier Metric Score assesses how well a metric predicts the outcome for a censored data point (a lower BMS is better). Survival analysis was then conducted with the selected metric and the best distribution was selected using Akaike information criterion (AIC). Confidence intervals (CIs) and the normalized confidence interval width (NCIS) were calculated for the injury probability curve. The testing and validation of the methods described were performed using biomechanics data in the open literature. The methods for the HIPC development procedure detailed herein have been rigorously tested and used in the generation of WIAMan HIPCs and Injury Assessment Reference Curves (IARCs) for the WIAMan ATD, but can also be used in other ATD or PMHS injury risk curve development.

Human Pelvis Bayesian Injury Probability Curves From Whole Body Lateral Impact Experiments.

Injury criteria are used in military, automotive, and aviation environments to advance human safety. While injury risk curves (IRCs) for the human pelvis are published under vertical loading, there is a paucity of analysis that describe IRCs under lateral impact. The objective of the present study is to derive IRCs under this mode. Published data were used from 60 whole-body postmortem human surrogate (PMHS) tests that used repeated testing protocols. In the first analysis, from single impact tests, all injury data points were considered as left censored and noninjury points were considered as right censored, while repeated testing results were treated as interval censored data. In the second analysis, injury data were treated uncensored. Peak force was used as the response variable. Age, total body mass, gender, and body mass index (BMI) were used as covariates in different combinations. Bayesian survival analysis model was used to derive the IRCs. Plus-minus 95% credible intervals (CI) and their normalized CI sizes (NCIS) were obtained. This is the first study to develop IRCs in whole body PMHS tests to describe the human pelvic tolerance under lateral impact using Bayesian models.

Preliminary female cervical spine injury risk curves from PMHS tests.

The human cervical spine sustains compressive loading in automotive events and military operational activities, and the contact and noncontact loading are the two primary impact modes. Biomechanical and anatomical studies have shown differences between male and female cervical spines. Studies have been conducted to determine the human tolerance in terms of forces from postmortem human subject (PMHS) specimens from male and female spines; however, parametric risk curves specific to female spines are not available from contact loading to the head-neck complex under the axial mode. This study was conducted to develop female-spine based risk curves from PMHS tests. Data from experiments conducted by the authors using PMHS upright head-spines were combined with data from published studies using inverted head-spines. The ensemble consisted of 20 samples with ages ranging from 29 to 95 years. Except one, all specimens sustained neck injuries, consisting of fractures to cervical vertebrae, and disruptions to the intervertebral disc and facet joints, and ligaments. Parametric survival analysis was used to derive injury probability curves using the compressive force, uncensored for injury and right censored for noninjury data points. The specimen age was used as the covariate. Injury probability curves were derived using the best fit distribution, and the± 95% confidence interval limits were obtained. Results indicated that age is a significant covariate for injury for the entire ensemble. Peak forces were extracted for 35, 45, and 63 (mean) years of age, the former two representing the young (military) and the latter, the automobile occupant populations. The forces of 1.2 kN and 2.9 kN were associated with 5% and 50% probability of injury at 35 years. These values at 45 years were 1.0 kN and 2.4 kN, and at 63 years, they were 0.7 kN and 1.7 kN. The normalized widths of the confidence intervals at these probability levels for the mean age were 0.74 and 0.48. The preliminary injury risk curves presented should be used with appropriate caution. This is the first study to develop risk curves for females of different ages using parametric survival analysis, and can be used to advance human safety, and design and develop manikins for military and other environments.

Role of disc area and trabecular bone density on lumbar spinal column fracture risk curves under vertical impact

While studies have been conducted using human cadaver lumbar spines to understand injury biomechanics in terms of stability/energy to fracture, and physiological responses under pure-moment/follower loads, data are sparse for inferior-to-superior impacts. Injuries occur under this mode from underbody blasts. Objectives: determine role of age, disc area, and trabecular bone density on tolerances/risk curves under vertical loading from a controlled group of specimens. T12-S1 columns were obtained, pretest X-rays and CTs taken, load cells attached to both ends, impacts applied at S1-end using custom vertical accelerator device, and posttest X-ray, CT, and dissections done. BMD of L2-L4 vertebrae were obtained from QCT. Survival analysis-based Human Injury Probability Curves (HIPCs) were derived using proximal and distal forces. Age, area, and BMD were covariates. Forces were considered uncensored, representing the load carrying capacity. The Akaike Information Criterion was used to determine optimal distributions. The mean forces, ±95% confidence intervals, and Normalized Confidence Interval Size (NCIS) were computed. The Lognormal distribution was the optimal function for both forces. Age, area, and BMD were not significant (p > 0.05) covariates for distal forces, while only BMD was significant for proximal forces. The NCIS was the lowest for force-BMD covariate HIPC. The HIPCs for both genders at 35 and 45 years were based on population BMDs. These HIPCs serve as human tolerance criteria for automotive, military, and other applications. In this controlled group of samples, BMD is a better predictor-covariate that characterizes lumbar column injury under inferior-to-superior impacts.

Initial analysis of archived non-human primate frontal and rear impact data from the biodynamics data resource

ABSTRACTObjective: The research objective was to conduct an initial analysis of non-human primate (NHP) data from frontal and rear impact events archived in the Biodynamics Data Resource (BDR) records of the Naval Biodynamics Laboratory (NBDL). These rare data, collected between 1973 and 1989, will inform the safety community of upper-end tolerance limits of NHP and may be related to severe crash scenarios.Methods: Data from frontal and rear acceleration tests to 93 macaque NHP were examined. Each NHP was fully torso restrained, whereas the head–neck complex was unrestrained. Each NHP underwent between 1 and 21 total runs; 2 total runs was most common—a low-level run and then a high-level run. Following each impact exposure, the NHP was evaluated using a series of medical examinations. Now part of the legacy collection in the BDR, these evaluations were used to assess NHP exposures to be in one of 3 categories: noninjurious, injurious, or fatal. Using reported peak sled acceleration values, data were amenable to survival analysis statistical methodology to derive injury probability curves (IPCs). IPCs were derived for injury and fatality outcomes.Results: Fatal injuries for both frontal and rear impacts were mostly at the cranio-vertebral junction. In addition to hemorrhage, fatal frontal and rear impact tests both produced predominantly atlanto-occipital dislocations, with and without spinal cord transection. After exclusions, IPCs were derived for frontal and rear impact for both (1) fatal outcome and (2) injurious outcome (any injury including fatal injury). For frontal impact, 53 NHP qualified with 5, 25, and 50% risk for fatality at 89, 105, and 114 peak sled Gs, respectively, and for injurious outcome at 70, 92, and 106 Gs, respectively. For rear impact, 34 NHP qualified with 5, 25, and 50% risk for fatality at 96, 122, 138 peak sled Gs, respectively, and for injurious outcome at 75, 99, and 115 Gs, respectively.Conclusions: The majority of injuries were at the cranio-vertebral junction, indicating that the inertial head mass caused a tensile loading mechanism to the cervical spine. These data may be used in conjunction with finite element modeling to estimate risks to the human population. The most direct application in the automotive environment could be to the well-restrained child. The Nij neck injury criteria, currently based on data from piglet studies, could also benefit because the NHP is a more accurate human surrogate. These types of tests are likely to never be repeated and will form an upper bound of tolerance information valuable to safety system designers.

Survival Analysis-Based Human Head Injury Risk Curves: Focus on Skull Fracture.

Head contact-induced loads can result in skull fractures and/or brain injuries. While skull fractures have been produced from post-mortem human cadaver surrogates (PMHS), injury probability curves describing their structural responses have not been developed. The objectives of this study were to develop skull fracture-based injury risk curves and describe human tolerances using survival analysis. Published PMHS data in this journal were used. Mean age, stature, and weight of 12 PMHS were: 66.6 ± 2.3 years, 1.71 ± 2.9 m, and 76.4 ± 4.6 kg. A testing device applied contact loading to the head. Failure force, deflection, energy, and linear and secant stiffness variables were used to develop probability curves. Parametrical survival analysis included identifying most optimal distribution, ensuring that the chosen distribution is not significantly different from the nonparametrical model, determining ±95% confidence interval bounds and Normalized Confidence Interval Sizes (NICS), obtaining quality indices for each risk curve, and determining their hierarchical sequence using the Brier score metric (BSM). Lognormal distribution was the most optimal distribution for all variables, except failure force, for which Weibull distribution was optimal. Tightness-of-fit of risk curves for failure force, energy, and deflection were better than linear and secant stiffness variables. Force best represented skull fracture response based on BSM and NCIS, followed by deflection and energy, while two stiffness variables were least preferred metrics. These structural response-based set of risk curves, hitherto not reported, form a fundamental dataset for validating/assessing accuracy of outputs from computational models and serve as hierarchical skull fracture injury criteria under head contact loads.

Biomechanical tolerance of whole lumbar spines in straightened posture subjected to axial acceleration.

Quantification of biomechanical tolerance is necessary for injury prediction and protection of vehicular occupants. This study experimentally quantified lumbar spine axial tolerance during accelerative environments simulating a variety of military and civilian scenarios. Intact human lumbar spines (T12-L5) were dynamically loaded using a custom-built drop tower. Twenty-three specimens were tested at sub-failure and failure levels consisting of peak axial forces between 2.6 and 7.9 kN and corresponding peak accelerations between 7 and 57 g. Military aircraft ejection and helicopter crashes fall within these high axial acceleration ranges. Testing was stopped following injury detection. Both peak force and acceleration were significant (p < 0.0001) injury predictors. Injury probability curves using parametric survival analysis were created for peak acceleration and peak force. Fifty-percent probability of injury (95%CI) for force and acceleration were 4.5 (3.9-5.2 kN), and 16 (13-19 g). A majority of injuries affected the L1 spinal level. Peak axial forces and accelerations were greater for specimens that sustained multiple injuries or injuries at L2-L5 spinal levels. In general, force-based tolerance was consistent with previous shorter-segment lumbar spine testing (3-5 vertebrae), although studies incorporating isolated vertebral bodies reported higher tolerance attributable to a different injury mechanism involving structural failure of the cortical shell. This study identified novel outcomes with regard to injury patterns, wherein more violent exposures produced more injuries in the caudal lumbar spine. This caudal migration was likely attributable to increased injury tolerance at lower lumbar spinal levels and a faster inertial mass recruitment process for high rate load application. Published 2017. This article is a U.S. Government work and is in the public domain in the USA. J Orthop Res 36:1747-1756, 2018.

Role of age and injury mechanism on cervical spine injury tolerance from head contact loading

ABSTRACTObjective: The objective of this study was to determine the influence of age and injury mechanism on cervical spine tolerance to injury from head contact loading using survival analysis.Methods: This study analyzed data from previously conducted experiments using post mortem human subjects (PMHS). Group A tests used the upright intact head–cervical column experimental model. The inferior end of the specimen was fixed, the head was balanced by a mechanical system, and natural lordosis was removed. Specimens were placed on a testing device via a load cell. The piston applied loading at the vertex region. Spinal injuries were identified using medical images. Group B tests used the inverted head–cervical column experimental model. In one study, head–T1 specimens were fixed distally, and C7–T1 joints were oriented anteriorly, preserving lordosis. Torso mass of 16 kg was added to the specimen. In another inverted head–cervical column study, occiput–T2 columns were obtained, an artificial head was attached, T1–T2 was fixed, C4–C5 disc was maintained horizontal in the lordosis posture, and C7–T1 was unconstrained. The specimens were attached to the drop test carriage carrying a torso mass of 15 kg. A load cell at the inferior end measured neck loads in both studies. Axial neck force and age were used as the primary response variable and covariate to derive injury probability curves using survival analysis.Results: Group A tests showed that age is a significant (P < .05) and negative covariate; that is, increasing age resulted in decreasing force for the same risk. Injuries were mainly vertebral body fractures and concentrated at one level, mid-to-lower cervical spine, and were attributed to compression-related mechanisms. However, age was not a significant covariate for the combined data from group B tests. Both group B tests produced many soft tissue injuries, at all levels, from C1 to T1. The injury mechanism was attributed to mainly extension. Multiple and noncontiguous injuries occurred. Injury probability curves, ±95% confidence intervals, and normalized confidence interval sizes representing the quality of the mean curve are given for different data sets.Conclusions: For compression-related injuries, specimen age should be used as a covariate or individual specimen data may be prescaled to derive risk curves. For distraction- or extension-related injuries, however, specimen age need not be used as a covariate in the statistical analysis. The findings from these tests and survival analysis indicate that the age factor modulates human cervical spine tolerance to impact injury.

Foot-ankle complex injury risk curves using calcaneus bone mineral density data

ObjectiveBiomechanical data from post mortem human subject (PMHS) experiments are used to derive human injury probability curves and develop injury criteria. This process has been used in previous and current automotive crashworthiness studies, Federal safety standards, and dummy design and development. Human bone strength decreases as the individuals reach their elderly age. Injury risk curves using the primary predictor variable (e.g., force) should therefore account for such strength reduction when the test data are collected from PMHS specimens of different ages (age at the time of death). This demographic variable is meant to be a surrogate for fracture, often representing bone strength as other parameters have not been routinely gathered in previous experiments. However, bone mineral densities (BMD) can be gathered from tested specimens (presented in this manuscript). The objective of this study is to investigate different approaches of accounting for BMD in the development of human injury risk curves. MethodsUsing simulated underbody blast (UBB) loading experiments conducted with the PMHS lower leg-foot-ankle complexes, a comparison is made between the two methods: treating BMD as a covariate and pre-scaling test data based on BMD. Twelve PMHS lower leg-foot-ankle specimens were subjected to UBB loads. Calcaneus BMD was obtained from quantitative computed tomography (QCT) images. Fracture forces were recorded using a load cell. They were treated as uncensored data in the survival analysis model which used the Weibull distribution in both methods. The width of the normalized confidence interval (NCIS) was obtained using the mean and ± 95% confidence limit curves. Principal resultsThe mean peak forces of 3.9kN and 8.6kN were associated with the 5% and 50% probability of injury for the covariate method of deriving the risk curve for the reference age of 45 years. The mean forces of 5.4 kN and 9.2kN were associated with the 5% and 50% probability of injury for the pre-scaled method. The NCIS magnitudes were greater in the covariate-based risk curves (0.52–1.00) than in the risk curves based on the pre-scaled method (0.24–0.66). The pre-scaling method resulted in a generally greater injury force and a tighter injury risk curve confidence interval. Although not directly applicable to the foot-ankle fractures, when compared with the use of spine BMD from QCT scans to pre-scale the force, the calcaneus BMD scaled data produced greater force at the same risk level in general. ConclusionsPre-scaling the force data using BMD is an alternate, and likely a more accurate, method instead of using covariate to account for the age-related bone strength change in deriving risk curves from biomechanical experiments using PMHS. Because of the proximity of the calcaneus bone to the impacting load, it is suggested to use and determine the BMD of the foot-ankle bone in future UBB and other loading conditions to derive human injury probability curves for the foot-ankle complex.

Foot-Ankle Fractures and Injury Probability Curves from Post-mortem Human Surrogate Tests.

This purpose of this study was to replicate foot-ankle injuries seen in the military and derive human injury probability curves using the human cadaver model. Lower legs were isolated below knee from seventeen unembalmed human cadavers and they were aligned in a 90-90 posture (plantar surface orthogonal to leg). The specimens were loaded along the tibia axis by applying short-time duration pulses, using a repeated testing protocol. Injuries were documented using pre- and post-test X-rays, computed tomography scans, and dissection. Peak force-based risk curves were derived using survival analysis and accounted for data censoring. Fractures were grouped into all foot-ankle (A), any calcaneus (B), and any tibia injuries (C), respectively. Calcaneus and/or distal tibia/pilon fractures occurred in fourteen tests. Axial forces were the greatest and least for groups C and B, respectively. Times attainments of forces for all groups were within ten milliseconds. The Weibull function was the optimal probability distribution for all groups. Age was significant (p<0.05) for groups A and C. Survival analysis-based probability curves were derived for all groups. Data are given in the body of paper. Age-based, risk-specific, and continuous distribution probability curves/responses guide in the creation of an injury assessment capability for military blast environments.

Optimized Lower Leg Injury Probability Curves From Postmortem Human Subject Tests Under Axial Impacts

Objective: Derive optimum injury probability curves to describe human tolerance of the lower leg using parametric survival analysis.Methods: The study reexamined lower leg postmortem human subjects (PMHS) data from a large group of specimens. Briefly, axial loading experiments were conducted by impacting the plantar surface of the foot. Both injury and noninjury tests were included in the testing process. They were identified by pre- and posttest radiographic images and detailed dissection following the impact test. Fractures included injuries to the calcaneus and distal tibia–fibula complex (including pylon), representing severities at the Abbreviated Injury Score (AIS) level 2+. For the statistical analysis, peak force was chosen as the main explanatory variable and the age was chosen as the covariable. Censoring statuses depended on experimental outcomes. Parameters from the parametric survival analysis were estimated using the maximum likelihood approach and the dfbetas statistic was used to identify overly influential samples. The best fit from the Weibull, log-normal, and log-logistic distributions was based on the Akaike information criterion. Plus and minus 95% confidence intervals were obtained for the optimum injury probability distribution. The relative sizes of the interval were determined at predetermined risk levels. Quality indices were described at each of the selected probability levels.Results: The mean age, stature, and weight were 58.2 ± 15.1 years, 1.74 ± 0.08 m, and 74.9 ± 13.8 kg, respectively. Excluding all overly influential tests resulted in the tightest confidence intervals. The Weibull distribution was the most optimum function compared to the other 2 distributions. A majority of quality indices were in the good category for this optimum distribution when results were extracted for 25-, 45- and 65-year-olds at 5, 25, and 50% risk levels age groups for lower leg fracture. For 25, 45, and 65 years, peak forces were 8.1, 6.5, and 5.1 kN at 5% risk; 9.6, 7.7, and 6.1 kN at 25% risk; and 10.4, 8.3, and 6.6 kN at 50% risk, respectively.Conclusions: This study derived axial loading-induced injury risk curves based on survival analysis using peak force and specimen age; adopting different censoring schemes; considering overly influential samples in the analysis; and assessing the quality of the distribution at discrete probability levels. Because procedures used in the present survival analysis are accepted by international automotive communities, current optimum human injury probability distributions can be used at all risk levels with more confidence in future crashworthiness applications for automotive and other disciplines.

Real-World Injury Patterns Associated With Hybrid III Sternal Deflections in Frontal Crash Tests

Objective: This study investigated the relationship between the peak sternal deflection measurements recorded by the Hybrid III 50th percentile male anthropometric test device (ATD) in frontal crash tests and injury and fatality outcomes for drivers in field crashes. Methods: ATD sternal deflection data were obtained from the Insurance Institute for Highway Safety's 64 km/h, 40 percent overlap crashworthiness evaluation tests for vehicles with seat belt crash tensioners, load limiters, and good-rated structure. The National Automotive Sampling System Crashworthiness Data System (NASS-CDS) was queried for frontal crashes of these vehicles in which the driver was restrained by a seat belt and air bag. Injury probability curves were calculated by frontal crash type using the injuries coded in NASS-CDS and peak ATD sternal deflection data. Fatality Analysis Reporting System (FARS) front-to-front crashes with exactly one driver death were also studied to determine whether the difference in measured sternal deflections for the 2 vehicles was related to the odds of fatality. Results: For center impacts, moderate overlaps, and large overlaps in NASS-CDS, the probability of the driver sustaining an Abbreviated Injury Scale (AIS) score ≥ 3 thoracic injury, or any nonextremity AIS ≥ 3 injury, increased with increasing ATD sternal deflection measured in crash tests. For small overlaps, however, these probabilities decreased with increasing deflection. For FARS crashes, the fatally injured driver more often was in the vehicle with the lower measured deflection in crash tests (55 vs. 45%). After controlling for other factors, a 5-mm difference in measured sternal deflections between the 2 vehicles was associated with a fatality odds ratio of 0.762 for the driver in the vehicle with the greater deflection (95% confidence interval = 0.373, 1.449). Conclusions: Restraint systems that reduce peak Hybrid III sternal deflection in a moderate overlap crash test are beneficial in real-world crashes with similar or greater overlap but likely have a disbenefit in crashes with small overlap. This may occur because belt-force limiters employed to control deflections allow excursion that could produce contact with interior vehicle components in small overlaps, given the more oblique occupant motion and potential inboard movement of the air bag. Although based on a limited number of cases, this interpretation is supported by differences in skeletal fracture locations among drivers in crashes with different overlaps. Current restraint systems could be improved by designs that reduce sternal deflection in moderate and large overlap crashes without increasing occupant excursion in small overlap crashes. Supplemental materials are available for this article. Go to the publisher's online edition of Traffic Injury Prevention to view the supplemental file.