Static Preload Inhibits Loading-Induced Bone Formation

Periosteum response to static forces stimulates cortical drifting: A new orthopedic target

BACKGROUND

The mechanism of cortical bone adaptation to static forces is not well understood. This is an important process because static forces are applied to the cortical bone in response to the growth of soft tissues and during Orthodontic and Orthopedic corrections. The aim of this study was to investigate the cortical bone response to expanding forces applied to the maxilla.

METHODS

Overall, 375 adult Sprague-Dawley rats were divided into three groups: 1) static force group, 2) static force plus stimulation group, and 3) sham group. In addition to static force across the maxilla, some animals were exposed to anti-inflammatory medication. Samples were collected at different time points and evaluated by micro-computed tomography, fluorescence microscopy, immunohistochemistry, and gene and protein analyses.

RESULTS

The application of expansion forces to the maxilla increased inflammation in the periosteum and activated osteoclasts on the surface of the cortical plate. This activation was independent of the magnitude of tooth movement but followed the pattern of skeletal displacement. Bone formation on the surface of the cortical plate occurred at a later stage and resulted in the relocation of the cortical boundary of the maxilla and cortical drifting.

CONCLUSIONS

This study demonstrates that cortical bone adaptation to static forces originates from the periosteum, and it is an inflammatory-based phenomenon that can be manipulated by the clinician. Our findings support a new theory for cortical adaptation to static forces and an innovative clinical approach to promote cortical drifting through periosteal stimulation. Being able to control cortical drift can have a significant impact on clinical orthodontic and dentofacial orthopedics by allowing corrections of severe deformities without the need for maxillofacial surgery.

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

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 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.

Using Finite Element Modeling in Bone Mechanoadaptation

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. 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.

Manipulating load-induced fluid flow in vivo to promote bone adaptation

Mechanical stimulation is critical to maintaining bone mass and strength. Strain has been commonly thought of as the mechanical stimulus driving bone adaptation. However, numerous studies have hypothesized that fluid flow in the lacunar-canalicular system plays a role in mechanoadaptation. The role of fluid flow compared to strain magnitude on bone remodeling has yet to be characterized. This study aimed to determine the contribution of fluid flow velocity compared to strain on bone adaptation. We used finite element modeling to design in vivo experiments, manipulating strain and fluid flow contributions. Using a uniaxial compression tibia model in mice, we demonstrated that high fluid flow velocity results in significant bone adaptation even under low strain magnitude. In contrast, high strain magnitude paired with low fluid velocity does not trigger a bone response. These findings support previous hypotheses stating that fluid flow is the principal mechanical stimulus driving bone adaptation. Moreover, they give new insights regarding bone adaptative response and provide new pathways toward treatment against age-related mechanosensitivity loss in bone.

Murine Axial Compression Tibial Loading Model to Study Bone Mechanobiology: Implementing the Model and Reporting Results

In vivo, tibial loading in mice is increasingly used to study bone adaptation and mechanotransduction. To achieve standardized and defined experimental conditions, loading parameters and animal-related factors must be considered when performing in vivo loading studies. In this review, we discuss these loading and animal-related experimental conditions, present methods to assess bone adaptation, and suggest reporting guidelines. This review originated from presentations by each of the authors at the workshop "Developing Best Practices for Mouse Models of In Vivo Loading" during the Preclinical Models Section at the Orthopaedic Research Society Annual Meeting, San Diego, CA, March 2017. Following the meeting, the authors engaged in detailed discussions with consideration of relevant literature. The guidelines and recommendations in this review are provided to help researchers perform in vivo loading experiments in mice, and thus further our knowledge of bone adaptation and the mechanisms involved in mechanotransduction. © 2019 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 38:233-252, 2020.