Multibody modelling of ligamentous and bony stabilizers in the human elbow

Abstract

The elbow ligamentous and bony structures play essential roles in the joint stability. Nevertheless, the contribution of different structures to joint stability is not yet clear and a comprehensive experimental investigation into the ligament and osseous constraints changes in relation to joint motions would be uphill and somehow unattainable, due to the impossibility of obtaining all the possible configurations on the same specimen. Therefore, a predictive tool of the joint behavior after the loss of retentive structures would be helpful in designing reconstructive surgeries and in pre-operative planning. In this work, a multibody model consisting of bones and non-linear ligamentous structures is presented and validated through comparison with experimental data. An accurate geometrical model was equipped with non-linear ligaments bundles between optimized origin and insertion points. The joint function was simulated according to maneuvers accomplished in published experimental studies which explored the posteromedial rotatory in-stability (PMRI) in coronoid and posterior medial collateral ligament (PB) deficient elbows. Moreover, a complete design of experiments (DOE) was explored, investigating the influence of the elbow flexion degree, of the coronoid process and of the medial collateral ligaments (MCL) structures (anterior and posterior bundles) in the elbow joint opening. The implemented computational model accurately predicted the joint behavior with intact and deficient stabilizing structures at each flexion degree, and highlighted the statistically significant influence of the MCL structures (P<0.05) on the elbow stability. The predictive ability of this multibody elbow joint model let foresee that future investigations under different loading scenarios and injured or surgically reconstructed states could be effectively simulated, helping the ligaments reconstruction optimization in terms of bone tunnel localizations and grafts pre-loading. Level of evidence: V.

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