Periodic Reporting for period 2 - TENDON_MECHBIO (A multimodal approach to tendon mechanobiology)
Reporting period: 2022-11-01 to 2024-04-30
The Achilles tendon connects the calf muscle to the heel bone and is the largest and the most frequently injured tendon in humans. Injuries, or tendinopathies, include rupture of the tendon and degeneration of the tissue giving rise to inflammation and pain. The tendon healing process is extremely slow, often resulting in reduced range of motion and inferior tissue quality. Moreover, more than 50% of the tendons heal unsuccessfully. Tendons respond to mechanical load over time and loading is fundamental for good mechanical performance. However, the mechanoregulatory mechanisms and the levels of beneficial loading are unknown, leading to inconsistency in treatments of ruptures.
The main objective of the project is to clarify how tendons as biomaterials and biological tissues adapt to mechanical loading. The hypothesis is that we can further clarify the tendon’s response to mechanical loading by using a multimodal approach that combines novel experimental and numerical models on several length scales. Well-controlled and uniquely characterized animal experimental data is used to develop and validate novel adaptive computational models (in silico) that can comprehensively predict the full biomechanical behavior (fluid flow, elasticity and viscoelasticity) of healthy intact and ruptured healing tendons.
The specific aims are to characterize how different in vivo loading schemes affect composition, inhomogeneity, collagen structure and viscoelastic mechanical function of both intact tendons and ruptured tendons undergoing healing. Secondly, the project aims to develop and validate spatial and temporal adaptive mechanoregulatory computational tendon healing models, with a focus on the tendon heterogeneity.
The main objective of the project is to clarify how tendons as biomaterials and biological tissues adapt to mechanical loading. The hypothesis is that we can further clarify the tendon’s response to mechanical loading by using a multimodal approach that combines novel experimental and numerical models on several length scales. Well-controlled and uniquely characterized animal experimental data is used to develop and validate novel adaptive computational models (in silico) that can comprehensively predict the full biomechanical behavior (fluid flow, elasticity and viscoelasticity) of healthy intact and ruptured healing tendons.
The specific aims are to characterize how different in vivo loading schemes affect composition, inhomogeneity, collagen structure and viscoelastic mechanical function of both intact tendons and ruptured tendons undergoing healing. Secondly, the project aims to develop and validate spatial and temporal adaptive mechanoregulatory computational tendon healing models, with a focus on the tendon heterogeneity.
Experimentally, an in vivo animal model was set up and several animal experiments were conducted to investigate the effect of reduced and unloading on the Achilles tendon, both in intact tendons and in healing tendons at various timepoints.
The main findings on intact tendons are that in vivo unloading results in a more disorganized microstructure and an impaired viscoelastic response. Additionally, unloading also altered the nanoscale fibril mechanical response, possibly through alterations in the strain partitioning between hierarchical levels. Overall, the findings pointed to the importance of spatial heterogeneity within the tissue, where the main response to altered load is altered microstructural arrangement of the collagen. The main findings on healing ruptured tendons are that in vivo unloading during the early healing process resulted in a delayed and more disorganized collagen structure and a larger presence of adipose tissue. Unloading also delayed the remodelling of the stumps as well as callus maturation. Additionally, the nanoscale fibril mechanical response was altered, with unloaded tendons exhibiting a low degree of fibril recruitment as well as a decreased ability for fibril extension. The amount of elastin and collagen I and II is spatial and temporal and effected by unloading of the tissue. We have further developed new methodology where we apply high-resolution synchrotron tissue characterization techniques, combined with in situ mechanical loading, allowing to elucidate the intricate connection between hierarchical scales.
Currently, a numerical framework is being developed to investigate the mechanobiology of intact and healing tendon by utilizing and developing advanced numerical models. Our recently presented finite element mechanobiological framework for Achilles tendon healing is used together with different levels of external loading from the experiments. Predictions of the spatio-temporal evolution of tissue distribution, collagen alignment and mechanical properties overall agreed well with experimental data. Interestingly, both strain-dependent and cell density-dependent tissue production were identified as possible explanations for decreased tissue production in the tendon core during healing. The healing framework was expanded to predict formation of different tissue types during healing. Different mechanobiological factors were explored to regulate the formation of different tissue types, i.e. tendon-, cartilage-, fat- and bone-like tissue. This framework is the first to reproduce experimental observations of these tissues. It provides several potential mechanisms of mechanobiological regulation of the formation of different tissue types during tendon healing.
The main findings on intact tendons are that in vivo unloading results in a more disorganized microstructure and an impaired viscoelastic response. Additionally, unloading also altered the nanoscale fibril mechanical response, possibly through alterations in the strain partitioning between hierarchical levels. Overall, the findings pointed to the importance of spatial heterogeneity within the tissue, where the main response to altered load is altered microstructural arrangement of the collagen. The main findings on healing ruptured tendons are that in vivo unloading during the early healing process resulted in a delayed and more disorganized collagen structure and a larger presence of adipose tissue. Unloading also delayed the remodelling of the stumps as well as callus maturation. Additionally, the nanoscale fibril mechanical response was altered, with unloaded tendons exhibiting a low degree of fibril recruitment as well as a decreased ability for fibril extension. The amount of elastin and collagen I and II is spatial and temporal and effected by unloading of the tissue. We have further developed new methodology where we apply high-resolution synchrotron tissue characterization techniques, combined with in situ mechanical loading, allowing to elucidate the intricate connection between hierarchical scales.
Currently, a numerical framework is being developed to investigate the mechanobiology of intact and healing tendon by utilizing and developing advanced numerical models. Our recently presented finite element mechanobiological framework for Achilles tendon healing is used together with different levels of external loading from the experiments. Predictions of the spatio-temporal evolution of tissue distribution, collagen alignment and mechanical properties overall agreed well with experimental data. Interestingly, both strain-dependent and cell density-dependent tissue production were identified as possible explanations for decreased tissue production in the tendon core during healing. The healing framework was expanded to predict formation of different tissue types during healing. Different mechanobiological factors were explored to regulate the formation of different tissue types, i.e. tendon-, cartilage-, fat- and bone-like tissue. This framework is the first to reproduce experimental observations of these tissues. It provides several potential mechanisms of mechanobiological regulation of the formation of different tissue types during tendon healing.
The goals are addressed through an extensive combined experimental and computational approach, where small animal studies of mechanobiology are evaluated through experiments at large scale facilities in combination with computational modeling to describe the mechanical behavior of the tissue and its response to loading.
Experimentally, the developed new methodology where we use high-resolution synchrotron tissue characterization techniques, combined with in situ mechanical loading, allows us to elucidate the intricate connection between hierarchical scales in a manner earlier not possible. In detail, we have performed 2D and 3D spectroscopy, scattering and imaging at synchrotron facilities to quantify and assess structure and composition of the tissue. Also, concurrent in situ mechanical and structural characterization experiments were performed, using tomography and scattering techniques simultaneously with mechanical testing.
Computationally, we presented a novel mechano-regulated adaptive model of tendon healing that were able to predict tissue regeneration spatially and temporally, its mechanobiological effect, and also accounting for tissue differentiation, with high similarity to the mentioned experimental data.
By exploring if mechanical functional markers are linked to long-term successful healing, we are identifying essential mechanisms for restoring tendons’ mechanical function early and effectively.
Our combined approach with in situ experiments and computational modeling has gained a lot of attention and new collaborations are being established with the goal to extend the technical expertise towards other soft load bearing tissues, and translate the findings on the tendon to the human.
Experimentally, the developed new methodology where we use high-resolution synchrotron tissue characterization techniques, combined with in situ mechanical loading, allows us to elucidate the intricate connection between hierarchical scales in a manner earlier not possible. In detail, we have performed 2D and 3D spectroscopy, scattering and imaging at synchrotron facilities to quantify and assess structure and composition of the tissue. Also, concurrent in situ mechanical and structural characterization experiments were performed, using tomography and scattering techniques simultaneously with mechanical testing.
Computationally, we presented a novel mechano-regulated adaptive model of tendon healing that were able to predict tissue regeneration spatially and temporally, its mechanobiological effect, and also accounting for tissue differentiation, with high similarity to the mentioned experimental data.
By exploring if mechanical functional markers are linked to long-term successful healing, we are identifying essential mechanisms for restoring tendons’ mechanical function early and effectively.
Our combined approach with in situ experiments and computational modeling has gained a lot of attention and new collaborations are being established with the goal to extend the technical expertise towards other soft load bearing tissues, and translate the findings on the tendon to the human.