Beam theory for rapid strain estimation in the mouse tibia compression model

Pickering, Edmund; Trichilo, Silvia; Delisser, Peter J; Pivonka, Peter

doi:10.1007/s10237-021-01546-1

Cited by 3 publications

(4 citation statements)

References 47 publications

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“…A previously validated beam theory approach was used to determine the axial strain in cortical bone (Pickering et al. 2022 ). For the beam theory approach the ankle was treated as a pin supported joint and an axial compressive load F applied at the tibial plateau at position , replicating the experimental procedure (Pickering et al.…”

Section: Methodsmentioning

confidence: 99%

“…While accurate in calculating mechanical signals, performing calculations across millions of voxel-derived elements is a time-consuming procedure that may take several hours to complete (Pickering et al. 2022 ). Mechanical beam theory presents itself as an alternative method of performing stress/strain analysis in cortical bone analysis, with solutions obtained in seconds as opposed to hours (Miller et al.…”

Section: Introductionmentioning

confidence: 99%

“… 2019 ); this approach has been validated against finite element modelling, proving to be an equivalent strain modelling tool (Pickering et al. 2022 ).…”

Section: Introductionmentioning

confidence: 99%

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Cortical bone adaptation response is region specific, but not peak load dependent: insights from $$\mu$$CT image analysis and mechanostat simulations of the mouse tibia loading model

Miller,

Pickering,

Martelli

et al. 2023

Biomech Model Mechanobiol

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The two major aims of the present study were: (i) quantify localised cortical bone adaptation at the surface level using contralateral endpoint imaging data and image analysis techniques, and (ii) investigate whether cortical bone adaptation responses are universal or region specific and dependent on the respective peak load. For this purpose, we re-analyse previously published $$\mu$$ μ CT data of the mouse tibia loading model that investigated bone adaptation in response to sciatic neurectomy and various peak load magnitudes (F = 0, 2, 4, 6, 8, 10, 12 N). A beam theory-based approach was developed to simulate cortical bone adaptation in different sections of the tibia, using longitudinal strains as the adaptive stimuli. We developed four mechanostat models: universal, surface-based, strain directional-based, and combined surface and strain direction-based. Rates of bone adaptation in these mechanostat models were computed using an optimisation procedure (131,606 total simulations), performed on a single load case (F = 10 N). Subsequently, the models were validated against the remaining six peak loads. Our findings indicate that local bone adaptation responses are quasi-linear and bone region specific. The mechanostat model which accounted for differences in endosteal and periosteal regions and strain directions (i.e. tensile versus compressive) produced the lowest root mean squared error between simulated and experimental data for all loads, with a combined prediction accuracy of 76.6, 55.0 and 80.7% for periosteal, endosteal, and cortical thickness measurements (in the midshaft of the tibia). The largest root mean squared errors were observed in the transitional loads, i.e. F = 2 to 6 N, where inter-animal variability was highest. Finally, while endpoint imaging studies provide great insights into organ level bone adaptation responses, the between animal and loaded versus control limb variability make simulations of local surface-based adaptation responses challenging.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Cortical bone adaptation response is region specific, but not peak load dependent: insights from $$\mu$$CT image analysis and mechanostat simulations of the mouse tibia loading model

Miller,

Pickering,

Martelli

et al. 2023

Biomech Model Mechanobiol

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“…The geometric complexity of the FE model influences the accuracy of the solution. Pickering et al [ 91 ] compared beam theory and FE model of a mouse tibia to investigate load-induced strain distribution. They reported that by correcting the beam theory model with a loading correction factor, the estimation of strain distribution was comparable to the FE model.…”

Section: How Complex Does the Model Need To Be?mentioning

confidence: 99%

Using Finite Element Modeling in Bone Mechanoadaptation

Meslier

Shefelbine

2023

Curr Osteoporos Rep

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Purpose of the Review Bone adapts structure and material properties in response to its mechanical environment, a process called mechanoadpatation. For the past 50 years, finite element modeling has been used to investigate the relationships between bone geometry, material properties, and mechanical loading conditions. This review examines how we use finite element modeling in the context of bone mechanoadpatation. Recent Findings Finite element models estimate complex mechanical stimuli at the tissue and cellular levels, help explain experimental results, and inform the design of loading protocols and prosthetics. Summary FE modeling is a powerful tool to study bone adaptation as it complements experimental approaches. Before using FE models, researchers should determine whether simulation results will provide complementary information to experimental or clinical observations and should establish the level of complexity required. As imaging technics and computational capacity continue increasing, we expect FE models to help in designing treatments of bone pathologies that take advantage of mechanoadaptation of bone.

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