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  • Title: Computational model of the lower leg and foot/ankle complex: application to arch stability.
    Author: Iaquinto JM, Wayne JS.
    Journal: J Biomech Eng; 2010 Feb; 132(2):021009. PubMed ID: 20370246.
    Abstract:
    The aim of this work was the design and evaluation of a computational model to predict the functional behavior of the lower leg and foot/ankle complex whereby joint behavior was dictated by three-dimensional articular contact, ligamentous constraints, muscle loading, and external perturbation. Three-dimensional bony anatomy was generated from stacked CT images after which ligament mimicking elements were attached and muscle/body loading added to recreate the experimental conditions of selected cadaveric studies. Comparisons of model predictions to results from two different experimental studies were performed for the function of the medial arch in weight bearing stance and the contributions of soft tissue structures to arch stability. Sensitivity simulations evaluated selected in situ strain and stiffness values for ligament tissue. The greatest contributor to arch stability was the plantar fascia, which provided 79.5% of the resistance to arch collapse, followed by the plantar ligaments (12.5%), and finally the spring ligament (8.0%). Strains measured after plantar fasciotomy increased in the remaining plantar ligament by approximately 300% and spring ligament by approximately 200%. Sensitivity tests varying both in situ strain and stiffness across reported standard deviations showed that functional trends remained the same and true to experimental data, although absolute magnitudes changed. While not measured experimentally, the model also predicted that load can increase dramatically in the remaining plantar tissues when one of such tissues is removed. Overall, computational predictions of stability and soft tissue load sharing compared well with experimental findings. The strength of this simulation approach lies in its capacity to predict biomechanical behavior of modeled structures and to capture physical parameters of interest not measurable in experimental simulations or in vivo.
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