Dataset Information

Subject-specific models of the hindfoot reveal a relationship between morphology and passive mechanical properties.

ABSTRACT: The morphology of the bones, articular surfaces and ligaments and the passive mechanical characteristics of the ankle complex were reported to vary greatly among individuals. The goal of this study was to test the hypothesis that the variations observed in the passive mechanical properties of the healthy ankle complex are strongly influenced by morphological variations. To evaluate this hypothesis six numerical models of the ankle joint complex were developed from morphological data obtained from MRI of six cadaveric lower limbs, and from average reported data on the mechanical properties of ligaments and articular cartilage. The passive mechanical behavior of each model, under a variety of loading conditions, was found to closely match the experimental data obtained from each corresponding specimen. Since all models used identical material properties and were subjected to identical loads and boundary conditions, it was concluded that the observed variations in passive mechanical characteristics were due to variations in morphology, thus confirming the hypothesis. In addition, the average and large variations in passive mechanical behavior observed between the models were similar to those observed experimentally between cadaveric specimens. The results suggest that individualized subject-specific treatment procedures for ankle complex disorders are potentially superior to a one-size-fits-all approach.

SUBMITTER: Imhauser CW

PROVIDER: S-EPMC2601557 | biostudies-literature | 2008

REPOSITORIES: biostudies-literature

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Subject-specific models of the hindfoot reveal a relationship between morphology and passive mechanical properties.

Imhauser Carl W CW Siegler Sorin S Udupa Jayaram K JK Toy Jason R JR

Journal of biomechanics 20080307 6

The morphology of the bones, articular surfaces and ligaments and the passive mechanical characteristics of the ankle complex were reported to vary greatly among individuals. The goal of this study was to test the hypothesis that the variations observed in the passive mechanical properties of the healthy ankle complex are strongly influenced by morphological variations. To evaluate this hypothesis six numerical models of the ankle joint complex were developed from morphological data obtained fro ...[more]

PMID: 18316088

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Project description:Musculoskeletal modelling is an important platform on which to study the biomechanics of morphological structures in vertebrates and is widely used in clinical, zoological and palaeontological fields. The popularity of this approach stems from the potential to non-invasively quantify biologically important but difficult-to-measure functional parameters. However, while it is known that model predictions are highly sensitive to input values, it is standard practice to build models by combining musculoskeletal data from different sources resulting in 'generic' models for a given species. At present, there are little quantitative data on how merging disparate anatomical data in models impacts the accuracy of these functional predictions. This issue is addressed herein by quantifying the accuracy of both subject-specific human limb models containing individualised muscle force-generating properties and models built using generic properties from both elderly and young individuals, relative to experimental muscle torques obtained from an isokinetic dynamometer. The results show that subject-specific models predict isokinetic muscle torques to a greater degree of accuracy than generic models at the ankle (root-mean-squared error - 7.9% vs. 49.3% in elderly anatomy-based models), knee (13.2% vs. 57.3%) and hip (21.9% vs. 32.8%). These results have important implications for the choice of musculoskeletal properties in future modelling studies, and the relatively high level of accuracy achieved in the subject-specific models suggests that such models can potentially address questions about inter-subject variations of muscle functions. However, despite relatively high levels of overall accuracy, models built using averaged generic muscle architecture data from young, healthy individuals may lack the resolution and accuracy required to study such differences between individuals, at least in certain circumstances. The results do not wholly discourage the continued use of averaged generic data in musculoskeletal modelling studies but do emphasise the need for to maximise the accuracy of input values if studying intra-species form-function relationships in the musculoskeletal system.

Project description:Subject-specific musculoskeletal modeling can be applied to study musculoskeletal disorders, allowing inclusion of personalized anatomy and properties. Independent of the tools used for model creation, there are unavoidable uncertainties associated with parameter identification, whose effect on model predictions is still not fully understood. The aim of the present study was to analyze the sensitivity of subject-specific model predictions (i.e., joint angles, joint moments, muscle and joint contact forces) during walking to the uncertainties in the identification of body landmark positions, maximum muscle tension and musculotendon geometry. To this aim, we created an MRI-based musculoskeletal model of the lower limbs, defined as a 7-segment, 10-degree-of-freedom articulated linkage, actuated by 84 musculotendon units. We then performed a Monte-Carlo probabilistic analysis perturbing model parameters according to their uncertainty, and solving a typical inverse dynamics and static optimization problem using 500 models that included the different sets of perturbed variable values. Model creation and gait simulations were performed by using freely available software that we developed to standardize the process of model creation, integrate with OpenSim and create probabilistic simulations of movement. The uncertainties in input variables had a moderate effect on model predictions, as muscle and joint contact forces showed maximum standard deviation of 0.3 times body-weight and maximum range of 2.1 times body-weight. In addition, the output variables significantly correlated with few input variables (up to 7 out of 312) across the gait cycle, including the geometry definition of larger muscles and the maximum muscle tension in limited gait portions. Although we found subject-specific models not markedly sensitive to parameter identification, researchers should be aware of the model precision in relation to the intended application. In fact, force predictions could be affected by an uncertainty in the same order of magnitude of its value, although this condition has low probability to occur.

Dataset Information

Subject-specific models of the hindfoot reveal a relationship between morphology and passive mechanical properties.

Publications

Subject-specific models of the hindfoot reveal a relationship between morphology and passive mechanical properties.

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