ArticleJournal of biomechanical engineering2017
Multiscale Strain as a Predictor of Impact-Induced Fissuring in Articular Cartilage.
Article in Journal of biomechanical engineering, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 20 citations in OpenAlex.
- Time-dependent computational model of post-traumatic osteoarthritis to estimate how mechanoinflammatory mechanisms impact cartilage aggrecan content.PLoS computational biology · 2025Article
- STRAINS: A big data method for classifying cellular response to stimuli at the tissue scale.PloS one · 2022Article
- Relaxation capacity of cartilage is a critical factor in rate- and integrity-dependent fracture.Scientific reports · 2021Article
- Characterization and finite element validation of transchondral strain in the human hip during static and dynamic loading.Journal of biomechanics · 2021Article
- Mitoprotective therapy prevents rapid, strain-dependent mitochondrial dysfunction after articular cartilage injury.Journal of orthopaedic research : official publication of the Orthopaedic Research Society · 2020Article
- A novel mechanobiological model can predict how physiologically relevant dynamic loading causes proteoglycan loss in mechanically injured articular cartilage.Scientific reports · 2018Article
- Local and global measurements show that damage initiation in articular cartilage is inhibited by the surface layer and has significant rate dependence.Journal of biomechanics · 2018Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Mechanical damage is central to both initiation and progression of osteoarthritis (OA). However, specific causal links between mechanics and cartilage damage are incompletely understood, which results in an inability to predict failure. The lack of understanding is primarily due to the difficulty in simultaneously resolving the high rates and small length scales relevant to the problem and in correlating such measurements to the resulting fissures. This study leveraged microscopy and high-speed imaging to resolve mechanics on the previously unexamined time and length scales of interest in cartilage damage, and used those mechanics to develop predictive models. The specific objectives of this study were to: first, quantify bulk and local mechanics during impact-induced fissuring; second, develop predictive models of fissuring based on bulk mechanics and local strain; and third, evaluate the accuracy of these models in predicting fissures. To achieve these three objectives, bovine tibial cartilage was impacted using a custom spring-loaded device mounted on an inverted microscope. The occurrence of fissures was modulated by varying impact energy. For the first objective, during impact, deformation was captured at 10,000 frames per second and bulk and local mechanics were analyzed. For the second objective, data from samples impacted with a 1.2 mm diameter rod were fit to logistic regression functions, creating models of fissure probability based on bulk and local mechanics. Finally, for the third objective, data from samples impacted with a 0.8 mm diameter rod were used to test the accuracy of model predictions. This study provides a direct comparison between bulk and local mechanical thresholds for the prediction of fissures in cartilage samples, and demonstrates that local mechanics provide more accurate predictions of local failure than bulk mechanics provide. Bulk mechanics were accurate predictors of fissure for the entire sample cohort, but poor predictors of fissure for individual samples. Local strain fields were highly heterogeneous and significant differences were determined between fissured and intact samples, indicating the presence of damage thresholds. In particular, first principal strain rate and maximum shear strain were the best predictors of local failure, as determined by concordance statistics. These data provide an important step in establishing causal links between local mechanics and cartilage damage; ultimately, data such as these can be used to link macro- and micro-scale mechanics and thereby predict mechanically mediated disease on a subject-specific basis.
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Registered trials
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