Estimating the stabilizing function of ankle and subtalar ligaments via a morphology-specific three-dimensional dynamic model

Knowledge of the stabilizing role of the ankle and subtalar ligaments is important for improving clinical techniques such as ligament repair and reconstruction. However, this knowledge is incomplete. The goal of this study was to expand this knowledge by investigating the stabilizing function of the ligaments using multiple morphologically subject-specific computational models. Nine models were created from the lower extremities of nine donors. Each model consisted of the articulating bones, articular cartilage, and ligaments. Simulations were conducted in ADAMS (TM) - a dynamic simulation program. During simulation, tibia and fibula were fixed while cyclic moments in all three anatomical planes were applied to the calcaneus one-at-a-time. The resulting displacements between the bones and the forces in each ligament were computed. Simulations were conducted with all ligaments intact and after simulated ligament serial sectioning. Each model was validated by comparing the simulation results to experimental data obtained from the specimen used to construct the model. From the results the stabilizing role of each ligament was established and the effect of ligament sectioning on Range of Motion and Overall Laxity was identified. On the lateral side, ATFL provided stabilization in supination, CFL restrained inversion, external rotation and dorsiflexion and PTFL limited dorsiflexion and external rotation. On the medial side, PTTL restrained dorsiflexion and internal rotation, ATTL limited plantarflexion and external rotation, and TCL limited dorsiflexion, eversion and external rotation. At the subtalar joint, ITCL limited plantarflexion and its posterior-lateral bundle restrained subtalar inversion. CL restrained plantarflexion/dorsiflexion, and internal and external rotation. The large inter-model variability observed in the results indicate the importance of using multiple subject-specific models rather than relying on one "representative" model. (C) 2019 Elsevier Ltd. All rights reserved.