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Updated: Sep 10, 2025
Subject-specific Musculoskeletal Model for Studying Bone Strain During Dynamic Motion
Published on: April 11, 2018
A Pilot Validation Study of a Biomechanical Simulation Model for Rotational Ankle Injuries Using Robotic Cadaveric
Mohammad Amin Shayestehpour1,2, Martin G Gregersen3,4, Ola Saatvedt5,6
1Department of Orthopaedic Surgery, Østfold Hospital Trust, Grålum, Norway.
Background:
Deltoid ligament injuries occur in specific sequences during rotational ankle trauma, yet the current understanding of these sequences may be flawed. Computer modeling offers a new method for assessing ligament behavior under rotational injury mechanisms.
Methods:
A biomechanical computer simulation model was developed using AnyBody Modeling Software to evaluate ligament strain in rotational ankle injuries. Experimental data from a cadaveric study involving 15 human ankle specimens subjected to various loading conditions were used to identify the model parameters. After parameter identification from uninjured cadaveric data, we simulated Supination-External Rotation (SER) stage 2-4b injury model by removing the corresponding ligaments. Validation was performed by comparing the model predictions against the biomechanical experimental data.
Results:
The computer model replicated experimental findings, with correlation coefficients ranging from 0.81 to 0.99 across all injury stages and loading conditions. Furthermore, tension in the deep posterior tibiotalar ligament (DPTTL) progressively increased from SER2 to SER4a but remained unchanged in the SER2 phase. The model effectively captured progressive ligament strain and changes in medial clear space during injury progression.
Conclusion:
This study presents and validates an early-stage biomechanical simulation model for rotational ankle injuries, providing a novel tool for examining ligament biomechanics and injury mechanisms.
Clinical Relevance:
Our model offers insights that were previously unattainable through cadaveric or clinical studies by simulating ligament strain during injuries. This can assist in generating hypotheses, enhance injury detection, refine treatment strategies, and may challenge existing classification systems.
