Interstitial fluid velocity is decreased around cortical bone vascular pores and depends on osteocyte position in a rat model of disuse osteoporosis

2021 ◽  
Author(s):  
Vittorio Gatti ◽  
Michelle J. Gelbs ◽  
Rodrigo B. Guerra ◽  
Michael B. Gerber ◽  
Susannah P. Fritton
Keyword(s):  
Cortical Bone ◽  
Rat Model ◽  
Interstitial Fluid ◽  
Fluid Velocity ◽  
Disuse Osteoporosis

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 Effect of 1alpha-vitamin D3 and estrogen therapy on cortical bone mechanical properties in the ovariectomized rat model.

Endocrinology ◽  
1996 ◽  
Vol 137 (4) ◽  
pp. 1358-1364 ◽  
Author(s):  
J Aerssens ◽  
R van Audekercke ◽  
M Talalaj ◽  
P Geusens ◽  
E Bramm ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Cortical Bone ◽  
Vitamin D3 ◽  
Rat Model ◽  
Estrogen Therapy ◽  
Ovariectomized Rat ◽  
Bone Mechanical Properties

Porohyperelastic Finite Element Modeling of Abdominal Aortic Aneurysms

2010 ◽  
Vol 132 (10) ◽  
Author(s):  
Avinash Ayyalasomayajula ◽  
Jonathan P. Vande Geest ◽  
Bruce R. Simon
Keyword(s):  
Finite Element ◽  
Interstitial Fluid ◽  
Fluid Velocity ◽  
Aortic Aneurysms ◽  
Maximum Diameter ◽  
Hydraulic Permeability ◽  
Infrarenal Aorta ◽  
Standard Deviation Increase ◽  
Fluid Velocities ◽  
Abdominal Aortic

Abdominal aortic aneurysm (AAA) is the gradual weakening and dilation of the infrarenal aorta. This disease is progressive, asymptomatic, and can eventually lead to rupture—a catastrophic event leading to massive internal bleeding and possibly death. The mechanical environment present in AAA is currently thought to be important in disease initiation, progression, and diagnosis. In this study, we utilize porohyperelastic (PHE) finite element models (FEMs) to investigate how such modeling can be used to better understand the local biomechanical environment in AAA. A 3D hypothetical AAA was constructed with a preferential anterior bulge assuming both the intraluminal thrombus (ILT) and the AAA wall act as porous materials. A parametric study was performed to investigate how physiologically meaningful variations in AAA wall and ILT hydraulic permeabilities affect luminal interstitial fluid velocities and wall stresses within an AAA. A corresponding hyperelastic (HE) simulation was also run in order to be able to compare stress values between PHE and HE simulations. The effect of AAA size on local interstitial fluid velocity was also investigated by simulating maximum diameters (5.5 cm, 4.5 cm, and 3.5 cm) at the baseline values of ILT and AAA wall permeability. Finally, a cyclic PHE simulation was utilized to study the variation in local fluid velocities as a result of a physiologic pulsatile blood pressure. While the ILT hydraulic permeability was found to have minimal affect on interstitial velocities, our simulations demonstrated a 28% increase and a 20% decrease in luminal interstitial fluid velocity as a result of a 1 standard deviation increase and decrease in AAA wall hydraulic permeability, respectively. Peak interstitial velocities in all simulations occurred on the luminal surface adjacent to the region of maximum diameter. These values increased with increasing AAA size. PHE simulations resulted in 19.4%, 40.1%, and 81.0% increases in peak maximum principal wall stresses in comparison to HE simulations for maximum diameters of 35 mm, 45 mm, and 55 mm, respectively. The pulsatile AAA PHE FEM demonstrated a complex interstitial fluid velocity field the direction of which alternated in to and out of the luminal layer of the ILT. The biomechanical environment within both the aneurysmal wall and the ILT is involved in AAA pathogenesis and rupture. Assuming these tissues to be porohyperelastic materials may provide additional insight into the complex solid and fluid forces acting on the cells responsible for aneurysmal remodeling and weakening.

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 ◽  
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.

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