scholarly journals In Vivo Axial Loading of the Mouse Tibia

2014 ◽  
pp. 99-115 ◽  
Author(s):  
Katherine M. Melville ◽  
Alexander G. Robling ◽  
Marjolein C. H. van der Meulen
Keyword(s):  
Axial Loading ◽  
Mouse Tibia

EXOSKELETAL STRAIN: EVIDENCE FOR A TROT-GALLOP TRANSITION IN RAPIDLY RUNNING GHOST CRABS

1993 ◽  
Vol 179 (1) ◽  
pp. 301-321
Author(s):  
R. Blickhan ◽  
R. J. Full ◽  
L. Ting
Keyword(s):  
Axial Loading ◽  
Maximum Load ◽  
Strain Gauges ◽  
Bone Strain ◽  
Muscular Tension ◽  
Ocypode Quadrata ◽  
Ghost Crabs ◽  
Leg Design ◽  
Treadmill Locomotion

Equivalent gaits may be present in pedestrians that differ greatly in leg number, leg design and skeletal type. Previous studies on ghost crabs found that the transition from a slow to a fast run may resemble the change from a trot to a gallop in quadrupedal mammals. One indication of the trot-gallop gait change in quadrupedal mammals is a distinct alteration in bone strain. To test the hypothesis that ghost crabs (Ocypode quadrata) change from a trot to a gallop, we measured in vivo strains of the meropodite of the second trailing leg with miniature strain gauges. Exoskeletal strains changed significantly (increased fivefold) during treadmill locomotion at the proposed trot-gallop transition. Maximum strains attained during galloping and jumping (1000×10-6-3000×10-6) were similar to the values reported for mammals. Comparison of the maximum load possible on the leg segment (caused by muscular tension) with the strength of the segment under axial loading revealed a safety factor of 2.7, which is similar to values measured for jumping and running mammals. Equivalent gaits may result from similarities in the operation of pedestrian locomotory systems.

scholarly journals Influence of Comprehensive Joint Loads on Tibial Implant Micromotion in Total Ankle Arthroplasty

2020 ◽  
Vol 5 (4) ◽  
pp. 2473011420S0008
Author(s):  
Brett D. Steineman ◽  
Constantine A. Demetracopoulos ◽  
Jonathan T. Deland ◽  
Brett D. Steineman ◽  
Fernando Quevedo Gonzalez ◽  
...  
Keyword(s):  
Finite Element ◽  
Ankle Joint ◽  
Compressive Load ◽  
Compressive Force ◽  
Axial Loading ◽  
Loading Conditions ◽  
Bone Implant ◽  
Level Walking ◽  
Joint Loads

Category: Ankle Introduction/Purpose: Biologic fixation of total joint replacements by bone ingrowth requires minimal bone-implant micromotion [1]. Computational finite element (FE) models used to evaluate the interaction between implant and bone typically only consider simplified loading conditions based on the peak compressive force which occurs near toe-off [2,3]. However, a previous study focused on cementless knee replacements demonstrated that peak micromotion during activity cycles occurred with sub-maximal forces and moments [4]. Our objective was to calculate multi-axial loading at the ankle joint throughout level walking and evaluate tibial fixation of ankle replacements under these loading conditions. We hypothesized that peak micromotion would occur with sub-maximal loads and moments instead of at the instant of peak compressive load. Methods: Our validated six-degree-of-freedom robotic simulator utilizes in vivo data from human subjects to replicate the individual bone kinematics in cadaveric specimen throughout activity [5]. We rigidly fixed retro-reflective markers using bone pins to the tibia, talus, and calcaneus bones of three cadaveric specimens to record individual bone kinematics using motion capture cameras. We recorded the ground reaction and muscle-tendon forces during the simulated stance phase of level walking. Musculoskeletal models were then developed in OpenSim using the specimen-specific morphology and implant position from CT- scans and from the simulator outputs to determine the loading profile at the ankle joint during stance. The calculated loads were then applied to specimen-specific finite element models to evaluate the bone-implant interaction. Peak micromotion at each time point of loading was measured and compared to the loading profile to determine if it corresponded with the peak compressive load. Results: For all specimens, the peak compressive load at the ankle joint was accompanied by multi-axial moments and relatively small shear forces (Figure 1). The peak compressive load for each specimens was between 750 N and 850 N and occurred during 75-80% of gait. The largest moment experienced by all specimens was an internal moment late in stance. The peak micromotion for each specimen did not correspond to the instance of peak compressive load, as indicated in Figure 1. Instead, peak micromotion occurred at 54%, 88%, and 96% of gait. For each specimen, these instances corresponded to the combination of a sub-maximal compressive load with high eversion and internal moments. Conclusion: We have developed a workflow to calculate ankle joint loads corresponding to cadaveric simulations that reproduce a daily activity based on in vivo data. The specimen-specific, multi-axial loading profile at the ankle for our initial results suggests that peak micromotion at the bone-implant interface of the tibial implant does not coincide with the peak compressive force. The instant of peak compressive load may not capture the worst-case scenario for the interaction between the implant and the bone. Instead, the multi-axial forces and moments at the ankle joint throughout activity should be considered when evaluating implant fixation.

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.

The effect of axial loading and spine position on intervertebral disc hydration: An in vivo pilot study

2005 ◽  
Vol 18 (1-2) ◽  
pp. 15-20 ◽  
Author(s):  
Shi-Uk Lee ◽  
Michael Fredericson ◽  
Kim Butts ◽  
Philipp Lang
Keyword(s):  
Pilot Study ◽  
Intervertebral Disc ◽  
Axial Loading

Bulging of the Inner and Outer Annulus During In Vivo Axial Loading of Normal and Degenerated Discs

2009 ◽  
Vol 22 (3) ◽  
pp. 214-218 ◽  
Author(s):  
Gregory N. Kawchuk ◽  
Allison M. Kaigle Holm ◽  
Lars Ekström ◽  
Tommy Hansson ◽  
Sten H. Holm
Keyword(s):  
Axial Loading ◽  
Outer Annulus

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 Effect of repeated in vivo microCT imaging on the properties of the mouse tibia

PLoS ONE ◽  
2019 ◽  
Vol 14 (11) ◽  
pp. e0225127 ◽  
Author(s):  
Sara Oliviero ◽  
Mario Giorgi ◽  
Peter J. Laud ◽  
Enrico Dall’Ara
Keyword(s):  
Mouse Tibia ◽  
Microct Imaging

In Vivo Measurement of Lumbar Foramen During Axial Loading Using a Compression Device and Computed Tomography

2013 ◽  
Vol 26 (5) ◽  
pp. E177-E182 ◽  
Author(s):  
Takahiro Iwata ◽  
Kei Miyamoto ◽  
Akira Hioki ◽  
Minoru Ohashi ◽  
Nozomu Inoue ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Axial Loading ◽  
In Vivo Measurement ◽  
Compression Device

scholarly journals EVALUATING THE THEORY OF BONE MECHANOREGULATION IN THE PHYSIOLOGICAL LOADING SCENARIO

2018 ◽  
Vol 18 (02) ◽  
pp. 1850011 ◽  
Author(s):  
YONGTAO LU ◽  
WENYING ZHAO ◽  
JUNYAN LI ◽  
CHENGWEI WU
Keyword(s):  
Bone Mineral ◽  
Strain Energy ◽  
Mineral Content ◽  
Imaging System ◽  
Wild Type ◽  
Mineral Density ◽  
Physiological Loading ◽  
Subject Specific ◽  
Mouse Tibia

In this paper, the theory of bone mechanoregulation under physiological loading was evaluated. The entire right tibiae of wild type (WT, [Formula: see text]) and parathyroid hormone (PTH, [Formula: see text]) treated C57BL/6J female mice were scanned using an in vivo [Formula: see text]CT imaging system at 14, 16, 17, 18, 19, 20, 21, and 22 weeks. The PTH intervention started from week 18 until week 22. Subject-specific finite element (FE) models were created from the [Formula: see text]CT images and physiological loading condition was defined in the FE models. The rates of changes in bone mineral content (BMC), bone mineral density (BMD), and bone tissue density (TMD) were quantified over 40 anatomical compartments across the entire mouse tibia. The resulting values were then correlated to the average 1st principal tensile strain ([Formula: see text]) and the strain energy density (SED) for every compartment at weeks 18, 20, and 22. It was found that: in both groups, [Formula: see text] had a minimal effect on the variability of [Formula: see text]BMC ([Formula: see text]); SED had a significant effect on the variability of [Formula: see text]BMC only in the WT group ([Formula: see text]); [Formula: see text] had a significant effect on the variability of [Formula: see text]BMD only in the PTH group ([Formula: see text]); SED had a significant effect on the variability of [Formula: see text]BMD in both groups ([Formula: see text]); neither SED nor [Formula: see text] had a significant effect on the variability of [Formula: see text]TMD ([Formula: see text]). These results are the first to reveal the mechanism of bone mechanoregulation in the physiological loading scenario.

In Vivo Effects of Axial Loading on Healthy, Adolescent Spines

1979 ◽  
Vol &NA; (139) ◽  
pp. 17???27
Author(s):  
Jeffrey D. Reuben ◽  
Richard H. Brown ◽  
Clyde L. Nash ◽  
Eleanor M. Brower
Keyword(s):  
Axial Loading ◽  
Healthy Adolescent ◽  
In Vivo Effects
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