In silico modeling of bone adaptation to rest-inserted loading: Strain energy density versus fluid flow as stimulus

Tiwari, Abhishek Kumar; Kumar, Rakesh; Tripathi, Dharmendra; Badhyal, Subham

doi:10.1016/j.jtbi.2018.03.009

Cited by 23 publications

(9 citation statements)

References 70 publications

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“…While SED is widely used as a mathematical term to describe the mechanical signal influencing bone (re)modeling ( Huiskes et al, 2000 ; Schulte et al, 2013 ; Birkhold et al, 2017 ; Cheong et al, 2020 ), other mechanical signals, such as interstitial fluid flow through the lacuna-canalicular network (LCN), are also known to play a major role in determining the local mechanical environment surrounding osteocytes, the main mechanosensors in bone ( Fritton and Weinbaum, 2008 ; Weinbaum et al, 2011 ; Klein-Nulend et al, 2013 ). In this respect, it has been suggested that measures of fluid flow, such as the gradient in SED, would allow improved predictions of adaptive bone (re)modeling events ( Webster et al, 2015 ; Tiwari et al, 2018 ). In this study, we therefore aimed to (1) investigate the effects of varying loading frequencies on the mechano-regulation of trabecular bone in mouse caudal vertebrae, (2) assess whether adaptive bone (re)modeling can be linked to mechanical signals in the local in vivo environment and (3) compare the modeling performance of SED and the gradient in SED for the prediction of local bone formation and resorption events on the tissue level.…”

Section: Introductionmentioning

confidence: 99%

Mechano-Regulation of Trabecular Bone Adaptation Is Controlled by the Local in vivo Environment and Logarithmically Dependent on Loading Frequency

Scheuren

Vallaster

Kuhn

et al. 2020

Front. Bioeng. Biotechnol.

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It is well-established that cyclic, but not static, mechanical loading has anabolic effects on bone. However, the function describing the relationship between the loading frequency and the amount of bone adaptation remains unclear. Using a combined experimental and computational approach, this study aimed to investigate whether trabecular bone mechano-regulation is controlled by mechanical signals in the local in vivo environment and dependent on loading frequency. Specifically, by combining in vivo micro-computed tomography (micro-CT) imaging with micro-finite element (micro-FE) analysis, we monitored the changes in microstructural as well as the mechanical in vivo environment [strain energy density (SED) and SED gradient] of mouse caudal vertebrae over 4 weeks of either cyclic loading at varying frequencies of 2, 5, or 10 Hz, respectively, or static loading. Higher values of SED and SED gradient on the local tissue level led to an increased probability of trabecular bone formation and a decreased probability of trabecular bone resorption. In all loading groups, the SED gradient was superior in the determination of local bone formation and resorption events as compared to SED. Cyclic loading induced positive net (re)modeling rates when compared to sham and static loading, mainly due to an increase in mineralizing surface and a decrease in eroded surface. Consequently, bone volume fraction increased over time in 2, 5, and 10 Hz (+15%, +21% and +24%, p ≤ 0.0001), while static loading led to a decrease in bone volume fraction (−9%, p ≤ 0.001). Furthermore, regression analysis revealed a logarithmic relationship between loading frequency and the net change in bone volume fraction over the 4 week observation period ( R 2 = 0.74). In conclusion, these results suggest that trabecular bone adaptation is regulated by mechanical signals in the local in vivo environment and furthermore, that mechano-regulation is logarithmically dependent on loading frequency with frequencies below a certain threshold having catabolic effects, and those above anabolic effects. This study thereby provides valuable insights toward a better understanding of the mechanical signals influencing trabecular bone formation and resorption in the local in vivo environment.

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Section: Introductionmentioning

confidence: 99%

Mechano-Regulation of Trabecular Bone Adaptation Is Controlled by the Local in vivo Environment and Logarithmically Dependent on Loading Frequency

Scheuren

Vallaster

Kuhn

et al. 2020

Front. Bioeng. Biotechnol.

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“…While SED is widely used as a mathematical term to describe the mechanical signal influencing bone remodeling [15,[19][20][21], other mechanical signals, such as interstitial fluid flow through the lacuna-canalicular network (LCN), are also known to play a major role in determining the local mechanical environment surrounding osteocytes, the main mechanosensors in bone [22][23][24]. In this respect, it has been suggested that measures of fluid flow, such as the gradient in SED, would allow improved predictions of adaptive bone remodeling events [16,25]. In this study, we therefore aimed to 1) investigate the effects of varying loading frequencies on the mechano-regulation of trabecular bone in mouse caudal vertebrae, 2) assess whether adaptive bone remodeling can be linked to mechanical signals in the local in vivo environment and 3) compare the modeling performance of SED and the gradient in SED for the prediction of local bone formation and resorption events on the tissue level.…”

Section: Introductionmentioning

confidence: 99%

Mechano-regulation of bone adaptation is controlled by the local in vivo environment and logarithmically dependent on loading frequency

Scheuren

Vallaster

Kuhn

et al. 2020

Preprint

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15It is well established that cyclic, but not static, mechanical loading has anabolic effects on bone. 16 However, the function describing the relationship between the loading frequency and the 17 amount of bone adaptation remains unclear. Using a combined experimental and computational 18 approach, this study aimed to investigate whether bone mechano-regulation is controlled by 19 mechanical signals in the local in vivo environment and dependent on loading frequency. 20Specifically, by combining in vivo micro-computed tomography (micro-CT) imaging with 21 micro-finite element (micro-FE) analysis, we monitored the changes in microstructural as well 22 of the mechanical signals influencing bone formation and resorption in the local in vivo 39 environment. 40 Keywords: 41Bone adaptation, mechanical loading, in vivo micro-CT imaging, frequency dependency 42

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“…Student’s t -test and Watson U 2 goodness of fit test results showed in Table 8 support that the model has been able to closely predict the site-specific new bone formation at periosteal surface. The prediction is also improved at the endocoritcal surface in comparison to the models available in the literature (Tiwari and Prasad, 23 Prasad and Goyal, 27 and Tiwari et al 42 ). In addition, this study in fact validates the relation between spatial distribution of strain gradients and site-specific new bone distribution for different loading cases which was suggested as a future work in Gross et al 22 These findings may be useful in explaining how site-specific osteogenesis is regulated through mechanical environment.…”

Section: Discussionmentioning

confidence: 77%

Modeling cortical bone adaptation using strain gradients

Tiwari

Goyal

Prasad

2021

Proc Inst Mech Eng H

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Cyclic and low-magnitude loading promotes osteogenesis (i.e. new bone formation). Normal strain, strain energy density and fatigue damage accumulation are typically considered as osteogenic stimuli in computer models to predict site-specific new bone formation. These models however had limited success in explaining osteogenesis near the sites of minimal normal strain, for example, neutral axis of bending. Other stimuli such as fluid motion or strain gradient also stimulate bone formation. In silico studies modeled the new bone formation as a function of fluid motion, however, computation of fluid motion involves complex mathematical calculations. Strain gradients drive fluid flow and thus can also be established as the stimulus. Osteogenic potential of strain gradients is however not well established. The present study establishes strain gradients as osteogenic stimuli. Bending-induced strain gradients are computed at cortical bone cross-sections reported in animal loading in vivo studies. Correlation analysis between strain gradients and site of osteogenesis is analyzed. In silico model is also developed to test the osteogenic potential of strain gradients. The model closely predicts in vivo new bone distribution as a function of strain gradients. The outcome establishes strain gradient as computationally easy and robust stimuli to predict site-specific osteogenesis. The present study may be useful in the development of biomechanical approaches to mitigate bone loss.

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In silico modeling of bone adaptation to rest-inserted loading: Strain energy density versus fluid flow as stimulus

Cited by 23 publications

References 70 publications

Mechano-Regulation of Trabecular Bone Adaptation Is Controlled by the Local in vivo Environment and Logarithmically Dependent on Loading Frequency

Mechano-Regulation of Trabecular Bone Adaptation Is Controlled by the Local in vivo Environment and Logarithmically Dependent on Loading Frequency

Mechano-regulation of bone adaptation is controlled by the local in vivo environment and logarithmically dependent on loading frequency

Modeling cortical bone adaptation using strain gradients

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