Tissue-level distal tibia simulations to assess strain as a predictor of AIS 2 ankle injuries

Objective Ankle injury is one of the most common AIS 2 motor vehicle crash injury in the lower extremity. Prior work suggests females may be at greater risk for ankle fracture than males. Accurately predicting such ankle injuries using human body models (HBMs), particularly in frontal collisions, presents a unique challenge due to the complex loading mechanisms and differences in local geometry. Injury predictors derived from tissue level testing may be able to help overcome these challenges through strain-based injury prediction. This study aimed to provide tissue-level strain data for injury prediction through matched simulations with past Postmortem Human Subjects (PMHS) studies and morphed, subject-specific Total Human Model for Safety (THUMS) V6.1 tibiae.Methods Simulations were created for 17 PMHS tibiae subjected to inferomedial dynamic loading to generate medial malleolar fractures (previously published). THUMS tibiae were morphed to maintain baseline THUMS mesh size while generating accurate local geometry for each PMHS. Boundary and displacement loading conditions were matched to each subject-specific experimental test. Values of maximum principal strain (MPS) and 95th percentile maximum percentile strain (MPS95) of the tibia cortical bone were extracted from each simulation at the vertical force, vertical displacement, and energy at fracture from the matched experimental tests. Local injury risk curves were then developed with three functions (Weibull, log-normal, log-logistic) to generate potential curves to assess injury based on MPS and MPS95. Age and sex were considered as possible covariates.Results All simulations ran to completion and exhibited force and strain behavior consistent with the experimental work. Force-displacement curves displayed a softer response for the HBM compared to PMHS tests. Axial force at fracture, calculated at the ankle joint center, ranged from 1900 to 7500 N and shear force from 1100 to 4200 N. Max principal strain at fracture ranged from 1.9% to 9.2% and from 0.7% to 6.2% for MPS95. Specimen age and sex were initially considered as covariates but lacked statistically significance and were ultimately removed from these prediction metrics. The Weibull function was the best fit for the MPS and MPS95 risk functions. The Weibull function without covariates was used to generate fits of the cumulative distribution for MPS and MPS95.Conclusions This work used MPS and MPS95 to predict AIS 2 distal tibia injury using THUMS V6.1 simulations matched to past physical PMHS testing. These simulations demonstrated similar strain at fracture to typical failure values for cortical bone. Differences in HBM stiffness showed a potential challenge when applying untuned tissue-level injury metrics to the human body model. The curves generated in this study can be a useful foundation for approximating gross ankle injury based on MPS and MPS95 with THUMS V6.1.