Objective:​ Biomechanical 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.

Methods:​ Using 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 results:​ The mean peak forces of 3.9 kN 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 9.2 kN 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.

Conclusions:​ Pre-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.