scholarly journals Predicting cortical bone adaptation to axial loading in the mouse tibia

2015 ◽  
Author(s):  
Andre F Pereira ◽  
Behzad Javaheri ◽  
Andrew Pitsillides ◽  
Sandra Shefelbine
Keyword(s):  
Cortical Bone ◽  
Computational Models ◽  
Mechanical Load ◽  
Fluid Velocity ◽  
Structural Response ◽  
Axial Loading ◽  
Mechanical Stimulus ◽  
Bone Adaptation ◽  
Mouse Tibia ◽  
Efficient Loading

The development of predictive mathematical models can contribute to a deeper understanding of the specific stages of bone mechanobiology and the process by which bone adapts to mechanical forces. The objective of this work was to predict, with spatial accuracy, cortical bone adaptation to mechanical load, in order to better understand the mechanical cues that might be driving adaptation. The axial tibial loading model was used to trigger cortical bone adaptation in C57BL/6 mice and provide relevant biological and biomechanical information. A method for mapping cortical thickness in the mouse tibia diaphysis was developed, allowing for a thorough spatial description of where bone adaptation occurs. Poroelastic finite-element (FE) models were used to determine the structural response of the tibia upon axial loading and interstitial fluid velocity as the mechanical stimulus. FE models were coupled with mechanobiological governing equations, which accounted for non-static loads and assumed that bone responds instantly to local mechanical cues in an on-off manner. The presented formulation was able to simulate the areas of adaptation and accurately reproduce the distributions of cortical thickening observed in the experimental data with a statistically significant positive correlation (Kendall's tau rank coefficient \(\tau = 0.51\), \(p<0.001\)). This work demonstrates that computational models can spatially predict cortical bone mechanoadaptation to time variant stimulus. Such models could be used in the design of more efficient loading protocols and drugs therapies that target the relevant physiological mechanisms.

scholarly journals Predicting cortical bone adaptation to axial loading in the mouse tibia

2015 ◽  
Vol 12 (110) ◽  
pp. 20150590 ◽  
Author(s):  
A. F. Pereira ◽  
B. Javaheri ◽  
A. A. Pitsillides ◽  
S. J. Shefelbine
Keyword(s):  
Cortical Bone ◽  
Computational Models ◽  
Mechanical Load ◽  
Fluid Velocity ◽  
Structural Response ◽  
Axial Loading ◽  
Mechanical Stimulus ◽  
Bone Adaptation ◽  
Mouse Tibia ◽  
Efficient Loading

The development of predictive mathematical models can contribute to a deeper understanding of the specific stages of bone mechanobiology and the process by which bone adapts to mechanical forces. The objective of this work was to predict, with spatial accuracy, cortical bone adaptation to mechanical load, in order to better understand the mechanical cues that might be driving adaptation. The axial tibial loading model was used to trigger cortical bone adaptation in C57BL/6 mice and provide relevant biological and biomechanical information. A method for mapping cortical thickness in the mouse tibia diaphysis was developed, allowing for a thorough spatial description of where bone adaptation occurs. Poroelastic finite-element (FE) models were used to determine the structural response of the tibia upon axial loading and interstitial fluid velocity as the mechanical stimulus. FE models were coupled with mechanobiological governing equations, which accounted for non-static loads and assumed that bone responds instantly to local mechanical cues in an on–off manner. The presented formulation was able to simulate the areas of adaptation and accurately reproduce the distributions of cortical thickening observed in the experimental data with a statistically significant positive correlation (Kendall's τ rank coefficient τ = 0.51, p < 0.001). This work demonstrates that computational models can spatially predict cortical bone mechanoadaptation to a time variant stimulus. Such models could be used in the design of more efficient loading protocols and drug therapies that target the relevant physiological mechanisms.

scholarly journals Predicting cortical bone adaptation to axial loading in the mouse tibia

2015 ◽  
Author(s):  
Andre F Pereira ◽  
Behzad Javaheri ◽  
Andrew Pitsillides ◽  
Sandra Shefelbine
Keyword(s):  
Cortical Bone ◽  
Computational Models ◽  
Mechanical Load ◽  
Fluid Velocity ◽  
Structural Response ◽  
Axial Loading ◽  
Mechanical Stimulus ◽  
Bone Adaptation ◽  
Mouse Tibia ◽  
Efficient Loading

The development of predictive mathematical models can contribute to a deeper understanding of the specific stages of bone mechanobiology and the process by which bone adapts to mechanical forces. The objective of this work was to predict, with spatial accuracy, cortical bone adaptation to mechanical load, in order to better understand the mechanical cues that might be driving adaptation. The axial tibial loading model was used to trigger cortical bone adaptation in C57BL/6 mice and provide relevant biological and biomechanical information. A method for mapping cortical thickness in the mouse tibia diaphysis was developed, allowing for a thorough spatial description of where bone adaptation occurs. Poroelastic finite-element (FE) models were used to determine the structural response of the tibia upon axial loading and interstitial fluid velocity as the mechanical stimulus. FE models were coupled with mechanobiological governing equations, which accounted for non-static loads and assumed that bone responds instantly to local mechanical cues in an on-off manner. The presented formulation was able to simulate the areas of adaptation and accurately reproduce the distributions of cortical thickening observed in the experimental data with a statistically significant positive correlation (Kendall's tau rank coefficient \(\tau = 0.51\), \(p<0.001\)). This work demonstrates that computational models can spatially predict cortical bone mechanoadaptation to time variant stimulus. Such models could be used in the design of more efficient loading protocols and drugs therapies that target the relevant physiological mechanisms.

scholarly journals Predicting cortical bone adaptation to axial loading in the mouse tibia

2015 ◽  
Author(s):  
Andre F Pereira ◽  
Behzad Javaheri ◽  
Andrew Pitsillides ◽  
Sandra Shefelbine
Keyword(s):  
Cortical Bone ◽  
Mechanical Load ◽  
Fluid Velocity ◽  
Structural Response ◽  
Axial Loading ◽  
Mechanical Stimulus ◽  
Bone Adaptation ◽  
Static Loads ◽  
Tibia Diaphysis ◽  
Mouse Tibia

The development of predictive mathematical models can contribute to a deeper understanding of the specific stages of bone mechanobiology and the process by which bone adapts to mechanical forces. The objective of this work was to predict, with spatial accuracy, cortical bone adaptation to mechanical load, in order to better understand the mechanical cues that might be driving adaptation. The axial tibial loading model was used to trigger cortical bone adaptation in C57BL/6 mice and provide relevant biological and biomechanical information. A method for mapping cortical thickness in the mouse tibia diaphysis was developed, allowing for a thorough spatial description of where bone adaptation occurs. Poroelastic finite-element (FE) models were used to determine the structural response of the tibia upon axial loading and interstitial fluid velocity as the mechanical stimulus. FE models were coupled with mechanobiological governing equations, which accounted for non-static loads and assumed that bone responds instantly to local mechanical cues in an on-off manner.

scholarly journals Predicting cortical bone adaptation to axial loading in the mouse tibia

2015 ◽  
Author(s):  
Andre F Pereira ◽  
Behzad Javaheri ◽  
Andrew Pitsillides ◽  
Sandra Shefelbine
Keyword(s):  
Cortical Bone ◽  
Mechanical Load ◽  
Fluid Velocity ◽  
Structural Response ◽  
Axial Loading ◽  
Mechanical Stimulus ◽  
Bone Adaptation ◽  
Static Loads ◽  
Tibia Diaphysis ◽  
Mouse Tibia

The development of predictive mathematical models can contribute to a deeper understanding of the specific stages of bone mechanobiology and the process by which bone adapts to mechanical forces. The objective of this work was to predict, with spatial accuracy, cortical bone adaptation to mechanical load, in order to better understand the mechanical cues that might be driving adaptation. The axial tibial loading model was used to trigger cortical bone adaptation in C57BL/6 mice and provide relevant biological and biomechanical information. A method for mapping cortical thickness in the mouse tibia diaphysis was developed, allowing for a thorough spatial description of where bone adaptation occurs. Poroelastic finite-element (FE) models were used to determine the structural response of the tibia upon axial loading and interstitial fluid velocity as the mechanical stimulus. FE models were coupled with mechanobiological governing equations, which accounted for non-static loads and assumed that bone responds instantly to local mechanical cues in an on-off manner.

scholarly journals Effects of Loading Duration and Short Rest Insertion on Cancellous and Cortical Bone Adaptation in the Mouse Tibia

PLoS ONE ◽  
2017 ◽  
Vol 12 (1) ◽  
pp. e0169519 ◽  
Author(s):  
Haisheng Yang ◽  
Rachel E. Embry ◽  
Russell P. Main
Keyword(s):  
Cortical Bone ◽  
Bone Adaptation ◽  
Mouse Tibia

An Improved In Vivo Rat Tail Vertebra Model for the Study of Trabecular Bone Adaptation

1999 ◽  
Author(s):  
Mark J. Eichler ◽  
Chi Hyun Kim ◽  
X. Edward Guo
Keyword(s):  
Trabecular Bone ◽  
Large Scale ◽  
Bone Fractures ◽  
Mechanical Load ◽  
Bone Adaptation ◽  
Surgical Trauma ◽  
Micro Computed Tomography ◽  
Age Related ◽  
Rat Tail

Abstract The role of mechanical loading in trabecular bone adaptation is important for the understanding of bone integrity in different loading scenarios such as microgravity and for the etiology of age-related bone fractures. There have been numerous in vivo animal studies of bone adaptation, most of which are related to cortical bone remodeling, aimed at the investigation of Wolff’s Law [4], An interesting experimental model for trabecular bone adaptation has been developed in the rat tail vertebrae [2,3]. This model is attractive for trabecular bone adaptation studies because a controlled mechanical load can be applied to a whole vertebra with minimal surgical trauma, using a relatively inexpensive animal model. In addition, with advanced micro computed tomography (micro-CT) or micro magnetic resonance imaging (micro-MRI) coupled with large scale finite element modeling techniques, it is possible to characterize the three-dimensional (3D) stress/strain environment in the bone tissue close to a cellular level (∼25μm) [1]. Therefore, this in vivo rat tail model has a tremendous potential for quantification of the relationship between mechanical stimulation and biological response in trabecular bone adaptation.

scholarly journals Using Dissipative Particle Dynamics to Model Effects of Chemical Reactions Occurring within Hydrogels

Nanomaterials ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 2764
Author(s):  
Ya Liu ◽  
Joanna Aizenberg ◽  
Anna C. Balazs
Keyword(s):  
Computational Models ◽  
Structural Changes ◽  
Dissipative Particle Dynamics ◽  
Chemical Species ◽  
Structural Response ◽  
Particle Dynamics ◽  
Multi Stage ◽  
Chemical Stimuli ◽  
Chemical Events ◽  
Collapsed States

Computational models that reveal the structural response of polymer gels to changing, dissolved reactive chemical species would provide useful information about dynamically evolving environments. However, it remains challenging to devise one computational approach that can capture all the interconnected chemical events and responsive structural changes involved in this multi-stage, multi-component process. Here, we augment the dissipative particle dynamics (DPD) method to simulate the reaction of a gel with diffusing, dissolved chemicals to form kinetically stable complexes, which in turn cause concentration-dependent deformation of the gel. Using this model, we also examine how the addition of new chemical stimuli and subsequent reactions cause the gel to exhibit additional concentration-dependent structural changes. Through these DPD simulations, we show that the gel forms multiple latent states (not just the “on/off”) that indicate changes in the chemical composition of the fluidic environment. Hence, the gel can actuate a range of motion within the system, not just movements corresponding to the equilibrated swollen or collapsed states. Moreover, the system can be used as a sensor, since the structure of the layer effectively indicates the presence of chemical stimuli.

scholarly journals Pelvic Construct Prediction of Trabecular and Cortical Bone Structural Architecture

2018 ◽  
Vol 140 (9) ◽  
Author(s):  
Dan T. Zaharie ◽  
Andrew T. M. Phillips
Keyword(s):  
Cortical Bone ◽  
Structural Model ◽  
Thickness Distribution ◽  
Bone Adaptation ◽  
The Body ◽  
Lower Limbs ◽  
Fe Model ◽  
Adaptation Algorithm ◽  
Modeling Framework ◽  
Good Agreement

The pelvic construct is an important part of the body as it facilitates the transfer of upper body weight to the lower limbs and protects a number of organs and vessels in the lower abdomen. In addition, the importance of the pelvis is highlighted by the high mortality rates associated with pelvic trauma. This study presents a mesoscale structural model of the pelvic construct and the joints and ligaments associated with it. Shell elements were used to model cortical bone, while truss elements were used to model trabecular bone and the ligaments and joints. The finite element (FE) model was subjected to an iterative optimization process based on a strain-driven bone adaptation algorithm. The bone model was adapted to a number of common daily living activities (walking, stair ascent, stair descent, sit-to-stand, and stand-to-sit) by applying onto it joint and muscle loads derived using a musculoskeletal modeling framework. The cortical thickness distribution and the trabecular architecture of the adapted model were compared qualitatively with computed tomography (CT) scans and models developed in previous studies, showing good agreement. The sensitivity of the model to changes in material properties of the ligaments and joint cartilage and changes in parameters related to the adaptation algorithm was assessed. Changes to the target strain had the largest effect on predicted total bone volumes. The model showed low sensitivity to changes in all other parameters. The minimum and maximum principal strains predicted by the structural model compared to a continuum CT-derived model in response to a common test loading scenario showed good agreement with correlation coefficients of 0.813 and 0.809, respectively. The developed structural model enables a number of applications such as fracture modeling, design, and additive manufacturing of frangible surrogates.

Loading conditions and cortical bone construction of an artiodactyl calcaneus

1999 ◽  
Vol 202 (22) ◽  
pp. 3239-3254 ◽  
Author(s):  
S.C. Su ◽  
J.G. Skedros ◽  
K.N. Bachus ◽  
R.D. Bloebaum
Keyword(s):  
Cortical Bone ◽  
Compressive Strain ◽  
Mechanical Strain ◽  
Bone Adaptation ◽  
Principal Strain ◽  
Flexor Muscle ◽  
The Mean ◽  
Shear Strains ◽  
Tensile Strains ◽  
Principal Strains

Customary nonuniform distributions of physiological bone strains are thought to evoke heterogeneous material adaptation in diaphyseal cortices of some limb bones. Recent studies of artiodactyl calcanei have suggested that the regional prevalence of specific mechanical strain features such as mode and magnitude correlate with specific variations in cortical bone ultrastructure, microstructure and mineralization. These data are also consistent with predictions of current algorithms of mechanically induced bone adaptation. However, detailed characterization of the customary functional strain environment of these bones is needed to understand better the mechanisms of these adaptations. An in vitro loading method and rosette strain gauges were used to record principal strains, maximum shear strains and principal strain angles at multiple locations on ten calcanei of adult male mule deer (Odocoileus hemionus hemionus). Each hind limb was fixed in an apparatus to mimic the mid-support phase of the gait and loaded via the Achilles tendon over a broad range of functional loads (0 to 2943 N). Strains were recorded on the craniolateral, craniomedial, caudal, medial and lateral cortices at mid-diaphysis. Loading variations included the progressive elimination of the ligament and tendon along the caudal calcaneus. The results showed that the cranial cortex experiences longitudinal compressive strains that are nearly equal to the principal minimum strains and that the caudal cortex receives longitudinal tensile strains that are nearly equal to the principal maximum strains. With a 981 N load, the mean principal compressive strain on the cranial cortex was −636+/−344 micro(ε) (mean +/− s.d., N=9) and the mean principal tensile strain on the caudal cortex was 1112+/−68 micro;(ε)x (N=9). In contrast to the cranial and caudal cortices, principal strains in the medial and lateral cortices displayed relatively large deviations from the longitudinal axis (medial, 24 degrees cranial; lateral, 27 degrees caudal). Although shear strains predominated at all gauge sites, variations in maximum shear strains showed no apparent regional pattern or consistent regional predominance. The plantar ligament and tendon of the superficial digital flexor muscle were shown to have important load-sharing functions. These results demonstrate that the functionally loaded artiodactyl calcaneus generally behaves like a cantilevered beam with longitudinal compression and tension strains predominating in opposing cranial and caudal cortices, respectively. Differences in osteon remodeling rates, osteon morphology and mineral content reported previously between the cranial and caudal cortices correlate, in part, with the magnitudes of the principal compressive and tensile strains, respectively. However, material differences that distinguish the medial and lateral cortices from the cranial and caudal cortices could not be primarily attributed to locally increased shear strains as previously suggested. Variations in osteon and/or collagen fiber orientation may correlate more strongly with principal strain direction.

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