Corroboration of computational models for mechanoregulated stem cell differentiation

Systemic versus local patterns of limb joint articular morphology inferred from relative distances from morphological centroid

Joint morphogenesis is a complex process known to require the interaction of developmental cascades and mechanical loading, yet many details of this interaction are incompletely understood. While prior work has established populational patterns of joint morphological (co)variance, exploring how these patterns manifest within the individual provides information on the deployment of morphogenic processes as either systemic or local influences on joint shape. To better identify the patterns of variance-generating morphogenic processes, this study investigates the degree to which individual joint shapes deviate from population averages systematically across the body. Using three-dimensional landmark data from 200 adult skeletons, we ranked individuals based on their distances from morphological centroids for eight major joints. Spearman correlations assessed associations between ranks across various articular pairings, testing hypotheses regarding systemic versus localized variance. Results reveal low coordination between deviations observed in conarticular surfaces, functional analogs, and same-bone surfaces; however strong associations exist between antimeres, suggesting the left-right deployment of variance-generating morphogenic patterns is highly consistent. These results support a model of localized rather than systemic processes driving variation in joint shape. While more remains to be elucidated about the specifics of articular surface morphogenesis, these findings advance our understanding of the systems of variance generation at play during development and growth of our definitive joint morphology.

Biomechanical models: key considerations in study design

This manuscript summarizes presentations of a symposium on key considerations in design of biomechanical models at the 2019 Basic Science Focus Forum of the Orthopaedic Trauma Association. The first section outlines the most important characteristics of a high-quality biomechanical study. The second section considers choices associated with designing experiments using finite element modeling versus synthetic bones versus human specimens. The third section discusses appropriate selection of experimental protocols and finite element analyses. The fourth section considers the pros and cons of use of biomechanical research for implant design. Finally, the fifth section examines how results from biomechanical studies can be used when clinical evidence is lacking or contradictory. When taken together, these presentations emphasize the critical importance of biomechanical research and the need to carefully consider and optimize models when designing a biomechanical study.

Bone fracture healing in mechanobiological modeling: A review of principles and methods

Bone fracture is a very common body injury. The healing process is physiologically complex, involving both biological and mechanical aspects. Following a fracture, cell migration, cell/tissue differentiation, tissue synthesis, and cytokine and growth factor release occur, regulated by the mechanical environment. Over the past decade, bone healing simulation and modeling has been employed to understand its details and mechanisms, to investigate specific clinical questions, and to design healing strategies. The goal of this effort is to review the history and the most recent work in bone healing simulations with an emphasis on both biological and mechanical properties. Therefore, we provide a brief review of the biology of bone fracture repair, followed by an outline of the key growth factors and mechanical factors influencing it. We then compare different methodologies of bone healing simulation, including conceptual modeling (qualitative modeling of bone healing to understand the general mechanisms), biological modeling (considering only the biological factors and processes), and mechanobiological modeling (considering both biological aspects and mechanical environment). Finally we evaluate different components and clinical applications of bone healing simulation such as mechanical stimuli, phases of bone healing, and angiogenesis.

Mechanobiological modelling of tendons: Review and future opportunities

Tendons are adapted to carry large, repeated loads and are clinically important for the maintenance of musculoskeletal health in an increasing, actively ageing population, as well as in elite athletes. Tendons are known to adapt to mechanical loading. Also, their healing and disease processes are highly sensitive to mechanical load. Computational modelling approaches developed to capture this mechanobiological adaptation in tendons and other tissues have successfully addressed many important scientific and clinical issues. The aim of this review is to identify techniques and approaches that could be further developed to address tendon-related problems. Biomechanical models are identified that capture the multi-level aspects of tendon mechanics. Continuum whole tendon models, both phenomenological and microstructurally motivated, are important to estimate forces during locomotion activities. Fibril-level microstructural models are documented that can use these estimated forces to detail local mechanical parameters relevant to cell mechanotransduction. Cell-level models able to predict the response to such parameters are also described. A selection of updatable mechanobiological models is presented. These use mechanical signals, often continuum tissue level, along with rules for tissue change and have been applied successfully in many tissues to predict in vivo and in vitro outcomes. Signals may include scalars derived from the stress or strain tensors, or in poroelasticity also fluid velocity, while adaptation may be represented by changes to elastic modulus, permeability, fibril density or orientation. So far, only simple analytical approaches have been applied to tendon mechanobiology. With the development of sophisticated computational mechanobiological models in parallel with reporting more quantitative data from in vivo or clinical mechanobiological studies, for example, appropriate imaging, biochemical and histological data, this field offers huge potential for future development towards clinical applications.

Strains caused by daily loading might be responsible for delayed healing of an incomplete atypical femoral fracture

Atypical femoral fractures are insufficiency fractures in the lateral femoral diaphysis or subtrochanteric region that mainly affect older patients on bisphosphonate therapy. Delayed healing is often seen in patients with incomplete fractures (cracks), and histology of bone biopsies shows mainly necrotic material inside the crack. We hypothesized that the magnitude of the strains produced in the soft tissue inside the crack during normal walk exceeds the limit for new bone formation, and thereby inhibit healing. A patient specific finite element model was developed, based on clinical CT images and high resolution μCT images of a biopsy from the crack site. Strain distributions in the femur and inside the crack were calculated for load cases representing normal walk. The models predicted large strains inside the crack, with strain levels above 10% in more than three quarters of the crack volume. According to two different tissue differentiation theories, bone would only form in less than 1-5% of the crack volume. This can explain the impaired healing generally seen in incomplete atypical fractures. Furthermore, the microgeometry of the crack highly influenced the strain distributions. Hence, a realistic microgeometry needs to be considered when modeling the crack. Histology of the biopsy showed signs of remodeling in the bone tissue adjacent to the fracture line, while the crack itself contained mainly necrotic material and signs of healing only in portions that seemed to have been widened by resorption. In conclusion, the poor healing capacity of incomplete atypical femoral fractures can be explained by biomechanical factors, and daily low impact activities are enough to cause strain magnitudes that prohibit bone formation.

Computational techniques for the assessment of fracture repair

The combination of high-resolution three-dimensional medical imaging, increased computing power, and modern computational methods provide unprecedented capabilities for assessing the repair and healing of fractured bone. Fracture healing is a natural process that restores the mechanical integrity of bone and is greatly influenced by the prevailing mechanical environment. Mechanobiological theories have been proposed to provide greater insight into the relationships between mechanics (stress and strain) and biology. Computational approaches for modelling these relationships have evolved from simple tools to analyze fracture healing at a single point in time to current models that capture complex biological events such as angiogenesis, stochasticity in cellular activities, and cell-phenotype specific activities. The predictive capacity of these models has been established using corroborating physical experiments. For clinical application, mechanobiological models accounting for patient-to-patient variability hold the potential to predict fracture healing and thereby help clinicians to customize treatment. Advanced imaging tools permit patient-specific geometries to be used in such models. Refining the models to study the strain fields within a fracture gap and adapting the models for case-specific simulation may provide more accurate examination of the relationship between strain and fracture healing in actual patients. Medical imaging systems have significantly advanced the capability for less invasive visualization of injured musculoskeletal tissues, but all too often the consideration of these rich datasets has stopped at the level of subjective observation. Computational image analysis methods have not yet been applied to study fracture healing, but two comparable challenges which have been addressed in this general area are the evaluation of fracture severity and of fracture-associated soft tissue injury. CT-based methodologies developed to assess and quantify these factors are described and results presented to show the potential of these analysis methods.