Dataset Information

Subject-specific muscle properties from diffusion tensor imaging significantly improve the accuracy of musculoskeletal models.

ABSTRACT: 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.

SUBMITTER: Charles JP

PROVIDER: S-EPMC7542200 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Subject-specific muscle properties from diffusion tensor imaging significantly improve the accuracy of musculoskeletal models.

Charles James P JP Grant Barbara B D'Août Kristiaan K Bates Karl T KT

Journal of anatomy 20200629 5

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 mus ...[more]

PMID: 32598483

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Dataset Information

Subject-specific muscle properties from diffusion tensor imaging significantly improve the accuracy of musculoskeletal models.

Publications

Subject-specific muscle properties from diffusion tensor imaging significantly improve the accuracy of musculoskeletal models.

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