Use of postmortem human subjects to describe injury responses and tolerances

Yoganandan, Narayan; Stemper, Brian D.; Pintar, Frank A.; Maiman, Dennis J.

doi:10.1002/ca.21106

Cited by 18 publications

(7 citation statements)

References 97 publications

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“…Substantial work has been done in the blunt trauma community using cadaveric surrogates for brain strain measurements under impact loading 45 and pressure response for blast trauma. 85 Yoganandan et al 122 provides a recent review of cadaver studies in injury biomechanics including blast. Blast brain models have included mice, rats, rabbits, ferrets, and pigs.…”

Section: Experimental Animal Models and Scaling To Humansmentioning

confidence: 99%

Brain Injuries from Blast

et al. 2011

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Traumatic brain injury (TBI) from blast produces a number of conundrums. This review focuses on five fundamental questions including: (1) What are the physical correlates for blast TBI in humans? (2) Why is there limited evidence of traditional pulmonary injury from blast in current military field epidemiology? (3) What are the primary blast brain injury mechanisms in humans? (4) If TBI can present with clinical symptoms similar to those of Post-Traumatic Stress Disorder (PTSD), how do we clinically differentiate blast TBI from PTSD and other psychiatric conditions? (5) How do we scale experimental animal models to human response? The preponderance of the evidence from a combination of clinical practice and experimental models suggests that blast TBI from direct blast exposure occurs on the modern battlefield. Progress has been made in establishing injury risk functions in terms of blast overpressure time histories, and there is strong experimental evidence in animal models that mild brain injuries occur at blast intensities that are similar to the pulmonary injury threshold. Enhanced thoracic protection from ballistic protective body armor likely plays a role in the occurrence of blast TBI by preventing lung injuries at blast intensities that could cause TBI. Principal areas of uncertainty include the need for a more comprehensive injury assessment for mild blast injuries in humans, an improved understanding of blast TBI pathophysiology of blast TBI in animal models and humans, the relationship between clinical manifestations of PTSD and mild TBI from blunt or blast trauma including possible synergistic effects, and scaling between animals models and human exposure to blasts in wartime and terrorist attacks. Experimental methodologies, including location of the animal model relative to the shock or blast source, should be carefully designed to provide a realistic blast experiment with conditions comparable to blasts on humans. If traditional blast scaling is appropriate between species, many reported rodent blast TBI experiments using air shock tubes have blast overpressure conditions that are similar to human long-duration nuclear blasts, not high explosive blasts.

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Section: Experimental Animal Models and Scaling To Humansmentioning

confidence: 99%

Brain Injuries from Blast

et al. 2011

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“…The mechanics of the physical device (dummy) and the biomechanics of the human body and or body region are interrelated. From an automotive perspective, experiments using post-mortem human subjects (PMHSs) are used to reproduce field injuries, obtain biomechanical metrics, and correlate the two variables to achieve this goal (Yoganandan et al, 2007 , 2011 ). For example, the development of the human head injury tolerance criterion was based on this method (FMVSS-208, 2001 ).…”

Section: Current Knowledge and Advances In Dummy-based Injury Assessmmentioning

confidence: 99%

Age-Infusion Approach to Derive Injury Risk Curves for Dummies from Human Cadaver Tests

Yoganandan

Banerjee

Pintar

2015

Front. Bioeng. Biotechnol.

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Injury criteria and risk curves are needed for anthropomorphic test devices (dummies) to assess injuries for improving human safety. The present state of knowledge is based on using injury outcomes and biomechanical metrics from post-mortem human subject (PMHS) and mechanical records from dummy tests. Data from these models are combined to develop dummy injury assessment risk curves (IARCs)/dummy injury assessment risk values (IARVs). This simple substitution approach involves duplicating dummy metrics for PMHS tested under similar conditions and pairing with PMHS injury outcomes. It does not directly account for the age of each specimen tested in the PMHS group. Current substitution methods for injury risk assessments use age as a covariate and dummy metrics (e.g., accelerations) are not modified so that age can be directly included in the model. The age-infusion methodology presented in this perspective article accommodates for an annual rate factor that modifies the dummy injury risk assessment responses to account for the age of the PMHS that the injury data were based on. The annual rate factor is determined using human injury risk curves. The dummy metrics are modulated based on individual PMHS age and rate factor, thus “infusing” age into the dummy data. Using PMHS injuries and accelerations from side-impact experiments, matched-pair dummy tests, and logistic regression techniques, the methodology demonstrates the process of age-infusion to derive the IARCs and IARVs.

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“…Schematic of the setup used for axial loading of the lower leg using PMHS (see text for details, from (Yoganandan et al, 2011). …”

Section: Figurementioning

confidence: 99%

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

Yoganandan¹,

Arun²,

Pintar³

et al. 2014

Traffic Injury Prevention

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Objective Derive optimum injury probability curves to describe human tolerance of the lower leg using parametric survival analysis. Methods The study re-examined lower leg 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 non-injury 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 co-variable. 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: 58.2 ± 15.1 years, 1.74 ± 0.08 m and 74.9 ± 13.8 kg. Excluding all overly influential tests resulted in the tightest confidence intervals. The Weibull distribution was the most optimum function compared to the other two 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-old at five, 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.

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Use of postmortem human subjects to describe injury responses and tolerances

Cited by 18 publications

References 97 publications

Brain Injuries from Blast

Brain Injuries from Blast

Age-Infusion Approach to Derive Injury Risk Curves for Dummies from Human Cadaver Tests

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

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