The spatio-temporal mechanical environment of healthy and injured human cartilage during sustained activity and its role in cartilage damage

New experimental methodology to evaluate lubrication properties of synovial fluid containing worn tissue particles in osteoarthritis patients

Studying the lubrication properties of osteoarthritis (OA) synovial fluid (SF) enables an understanding of the boundary lubrication joint, mobility, and friction. However, tribology has never been combined with the clinical reality of the presence of worn particles within the synovial fluid and how they affect the osteoarthritic joints. Part of the problem relates to the tribology methods studying friction by applying inadequate pin-on-disc techniques. In this study, synovial fluid with and without worn particles was studied using a customized tribometer. This method enables opening the contact at the end of each cycle and simulates better contact conditions of a natural knee joint and can thus be applied for evaluating the severity of joint OA and the treatment given to the patient.

Osteochondral junction leakage and cartilage joint lubrication

BACKGROUND AND OBJECTIVES

Previous studies have shown that there is potentially interstitial fluid exchange between cartilage tissue and the subarticular spongiosa region in the case of injury or disease (e.g., osteoarthritis and osteoporosis). Interstitial flow is also required for cartilage lubrication under joint load. A key question then is how cartilage lubrication is modified by increased interstitial fluid leakage across the osteochondral junction. Thus, the purpose of this study is to develop a numerical model to investigate changes in cartilage lubrication with changes in osteochondral junction leakage.

METHODS

The multi-phase coupled model includes domains corresponding to the contact gap, cartilage tissue and subchondral bone plate region (ScBP). Each of these domains are treated as poroelastic systems, with their coupling implemented through mass and pressure continuity. The effects of osteochondral junction leakage on lubrication were investigated with a parametric study on the relative permeability between the ScBP and cartilage tissue.

RESULTS

Significant effects of ScBP permeability were predicted, especially during the early stage of the junction leakage development (early stage of the disease). There is a significant reduction in mixed-mode lubrication duration under the effect of increased junction leakage (the cartilage tissue mixed-mode lubrication duration is about 33% decrease for a relative permeability ratio of 0.1 between ScBP and cartilage tissue, and about 52% decrease under the osteoarthritis condition). In addition, the time for cartilage to reach steady-state consolidation is significantly reduced when ScBP permeability increases (the consolidation time reduces from roughly 2 h to 1.2 h when the relative permeability ratio increases from 0.001 to 0.1, and it reduces to 0.8 h for an advanced osteoarthritis condition). It is predicted that the initial friction coefficient could increase by over 60% when the ScBP permeability is consistent with an advanced osteoarthritis (OA) condition.

CONCLUSION

Increased osteochondral junction leakage induced by joint injury and disease could result in increased cartilage surface wear rates due to more rapid interstitial fluid depressurization within articular cartilage.

A review on design of scaffold for osteoinduction: Toward the unification of independent design variables

Biophysical stimulus quantifies the osteoinductivity of the scaffold concerning the mechanoregulatory mathematical models of scaffold-assisted cellular differentiation. Consider a set of independent structural variables ($) that comprises bulk porosity levels ([Formula: see text]) and a set of morphological features of the micro-structure ([Formula: see text]) associated with scaffolds, i.e., [Formula: see text]. The literature suggests that biophysical stimulus ([Formula: see text]) is a function of independent structural variables ($). Limited understanding of the functional correlation between biophysical stimulus and structural features results in the lack of the desired osteoinductivity in a scaffold. Consequently, it limits their broad applicability to assist bone tissue regeneration for treating critical-sized bone fractures. The literature indicates the existence of multi-dimensional independent design variable space as a probable reason for the general lack of osteoinductivity in scaffolds. For instance, known morphological features are the size, shape, orientation, continuity, and connectivity of the porous regions in the scaffold. It implies that the number of independent variables ([Formula: see text]) is more than two, i.e., [Formula: see text], which interact and influence the magnitude of [Formula: see text] in a unified manner. The efficiency of standard engineering design procedures to analyze the correlation between dependent variable ([Formula: see text]) and independent variables ($) in 3D mutually orthogonal Cartesian coordinate system diminishes proportionally with the increase in the number of independent variables ([Formula: see text]) (Deb in Optimization for engineering design-algorithms and examples, PHI Learning Private Limited, New Delhi, 2012). Therefore, there is an immediate need to devise a framework that has the potential to quantify the micro-structural's morphological features in a unified manner to increase the prospects of scaffold-assisted bone tissue regeneration.

Injury-related cell death and proteoglycan loss in articular cartilage: Numerical model combining necrosis, reactive oxygen species, and inflammatory cytokines

Osteoarthritis (OA) is a common musculoskeletal disease that leads to deterioration of articular cartilage, joint pain, and decreased quality of life. When OA develops after a joint injury, it is designated as post-traumatic OA (PTOA). The etiology of PTOA remains poorly understood, but it is known that proteoglycan (PG) loss, cell dysfunction, and cell death in cartilage are among the first signs of the disease. These processes, influenced by biomechanical and inflammatory stimuli, disturb the normal cell-regulated balance between tissue synthesis and degeneration. Previous computational mechanobiological models have not explicitly incorporated the cell-mediated degradation mechanisms triggered by an injury that eventually can lead to tissue-level compositional changes. Here, we developed a 2-D mechanobiological finite element model to predict necrosis, apoptosis following excessive production of reactive oxygen species (ROS), and inflammatory cytokine (interleukin-1)-driven apoptosis in cartilage explant. The resulting PG loss over 30 days was simulated. Biomechanically triggered PG degeneration, associated with cell necrosis, excessive ROS production, and cell apoptosis, was predicted to be localized near a lesion, while interleukin-1 diffusion-driven PG degeneration was manifested more globally. Interestingly, the model also showed proteolytic activity and PG biosynthesis closer to the levels of healthy tissue when pro-inflammatory cytokines were rapidly inhibited or cleared from the culture medium, leading to partial recovery of PG content. The numerical predictions of cell death and PG loss were supported by previous experimental findings. Furthermore, the simulated ROS and inflammation mechanisms had longer-lasting effects (over 3 days) on the PG content than localized necrosis. The mechanobiological model presented here may serve as a numerical tool for assessing early cartilage degeneration mechanisms and the efficacy of interventions to mitigate PTOA progression.

Computational Modelling for Managing Pathways to Cartilage Failure

Over several decades the perception and therefore description of articular cartilage changed substantially. It has transitioned from being described as a relatively inert tissue with limited repair capacity, to a tissue undergoing continuous maintenance and even adaption, through a range of complex regulatory processes. Even from the narrower lens of biomechanics, the engagement with articular cartilage has changed from it being an interesting, slippery material found in the hostile mechanical environment between opposing long bones, to an intriguing example of mechanobiology in action. The progress revealing this complexity, where physics, chemistry, material science and biology are merging, has been described with increasingly sophisticated computational models. Here we describe how these computational models of cartilage as an integrated system can be combined with the approach of structural reliability analysis. That is, causal, deterministic models placed in the framework of the probabilistic approach of structural reliability analysis could be used to understand, predict, and mitigate the risk of cartilage failure or pathology. At the heart of this approach is seeing cartilage overuse and disease processes as a 'material failure', resulting in failure to perform its function, which is largely mechanical. One can then describe pathways to failure, for example, how homeostatic repair processes can be overwhelmed leading to a compromised tissue. To illustrate this 'pathways to failure' approach, we use the interplay between cartilage consolidation and lubrication to analyse the increase in expected wear rates associated with cartilage defects or meniscectomy.

Post-traumatic Osteoarthritis in Rabbits Following Traumatic Injury and Surgical Reconstruction of the Knee

Post-traumatic osteoarthritis (PTOA) of the knee is often attributed to anterior cruciate ligament (ACL) and meniscus injury. The development of PTOA, however, does not seem to depend on whether or not the damaged ACL is reconstructed. There has been a need to develop animal models to study the mechanisms of PTOA following reconstruction of a traumatized knee. Eighteen rabbits underwent closed-joint trauma to produce ACL rupture and meniscus damage. Then, for the first time, the traumatized knee was surgically repaired in this animal model. Upon euthanasia at 1-, 3- or 6-month post-trauma, joint stability, cartilage morphology and mechanical properties, as well as histology of the cartilage and subchondral bone were evaluated. Trauma-induced knee injury involved 72% mid-substance ACL rupture, 28% partial ACL tear and 56% concurrent medial meniscal damage. ACL reconstruction effectively restored joint stability by reducing joint laxity to a level similar to that in the contralateral intact knee. Compared to their contralateral controls, reconstructed limbs showed osteoarthritic changes to the cartilage and subchondral bone as early as 1-month post-trauma. The degeneration progressed over time up to 6-month. Overall, the medial compartments had more tissue damage than their corresponding lateral counterparts. Damage patterns to the ACL, the frequency of observed concurrent meniscal injury, and reductions in cartilage integrity and health were consistent with clinical observations of human patients who undergo ACL injury and reconstruction. Thus, we believe the combined closed-joint injury and surgical repair lapine model of PTOA, being first-ever and clinically relevant, shows promise to evaluate well-targeted therapeutics and other interventions for this chronic disease.

Role of TNF-α in early-stage fracture healing under normal and diabetic conditions

BACKGROUND AND OBJECTIVE

Inflammatory response plays a crucial role in the early stage of fracture healing. Immediately after fracture, the debris and immune cells (e.g., macrophages), recruited into the fracture callus, lead to the secretion of inflammatory cytokines, such as tumor necrosis factor-alpha (TNF-α), which governs the mesenchymal stem cells (MSCs) mediated healing processes. However, it is still unclear how chronic inflammatory diseases (e.g., diabetes) affect the level of TNF-α in fracture callus, ultimately the healing outcomes at the early stage of healing. Therefore, the purpose of this study is to develop a numerical model for investigating TNF-α mediated bone fracture healing.

METHODS

A mathematical model consisting of a system of partial differential equations that represent the reactive transport of cells and cytokines in the fracture callus is developed in this study. The model is first calibrated by using available experimental data and then implemented to study the effect of TNF-α on the early stage of fracture healing under normal and diabetic conditions.

RESULTS

There is a significant elevation of TNF-α level in facture callus during the first 24 h post-fracture in normal condition, and its influence in the concentration of MSCs and cell differentiation becomes significant three days post-fracture (e.g., the absence of TNF-α signaling could reduce the concentration of MSCs more than 20% in cortical callus). In addition, the excessive secretion of TNF-α induced by diabetes could decrease the concentration of MSCs at the initial stage of healing, particularly reduce the concentration of MSCs in cortical callus by around 25%.

CONCLUSION

The model predictions suggested that there should be an optimal concentration of TNF-α in fracture callus, which enhances the early stage of healing, and excessive or insufficient secretion of TNF-α might significantly hinder the healing process.

A deep-learning framework for metacarpal-head cartilage-thickness estimation in ultrasound rheumatological images

OBJECTIVE

Rheumatoid arthritis (RA) is a chronic disease characterized by erosive symmetrical polyarthritis. Bone and cartilage are the main joint targets of this disease. Cartilage damage is one of the most relevant determinants of physical disability in RA patients. Cartilage damage is nowadays assessed by clinicians, which manually measure cartilage thickness in ultrasound (US) imaging. This poses issues relevant to intra-and inter-observer variability. Relying on the acquisition of metacarpal-head US images from 38 subjects, this work addresses the problem of automatic cartilage-thickness measurement by designing a new deep-learning (DL) framework.

METHODS

The framework consists of a Convolutional Neural Network (CNN), responsible for regressing cartilage-interface distance fields, followed by a post-processing step to delineate the two cartilage interfaces from the predicted distance fields and compute the cartilage thickness.

RESULTS

Our framework achieved encouraging results with a mean absolute difference (ADF) of 0.032 (±0.026) mm against manual thickness annotation by an expert clinician. When evaluating the intra-observer variability, we obtained an ADF = 0.036 (±0.028) mm.

CONCLUSION

The proposed framework achieved an ADF against manual annotation that was comparable to the intra-observer variability, proving the potential of DL in the field.

SIGNIFICANCE

This work is the first to address the problem of automatic cartilage-thickness estimation in US rheumatological images with DL, paving the way for future research in the field. From a clinical perspective, the proposed framework proved to be a valuable tool to support the clinical routine increasing the reproducibility of cartilage thickness measurements.

Study on the poroelastic behaviors of the defected articular cartilage

This article presented the possible mechanism of arthritis damaged changes in cartilage's interstitial fluid flowing behavior. Firstly, the analytical solutions for the pore fluid pressure and velocity in the idealized cartilage defect model were obtained, which are employed to validate the finite element (FE) method. Then according to the MRI data, an articular cartilage FE model was developed to study the effects of defect characteristics on its poroelastic behaviors. The results showed the interstitial fluid pressure and velocity in defected articular cartilage is diminished, moreover, this trend is even more severe as the defect radius or thickness increased. As the development of osteoarthritis goes, the fluid velocity is decreased and cause the even serious nutrients loss.

Balance Between Mechanical Stability and Mechano-Biology of Fracture Healing Under Volar Locking Plate

The application of volar locking plate (VLP) is promising in the treatment of dorsally comminuted and displaced fracture. However, the optimal balance between the mechanical stability of VLP and the mechanobiology at the fracture site is still unclear. The purpose of this study is to develop numerical models in conjunction with experimental studies to identify the favourable mechanical microenvironment for indirect healing, by optimizing VLP configuration and post-operative loadings for different fracture geometries. The simulation results show that the mechanical behaviour of VLP is mainly governed by the axial compression. In addition, the model shows that, under relatively large gap size (i.e., 3-5 mm), the increase of FWL could enhance chondrocyte differentiation while a large BPD could compromise the mechanical stability of VLP. Importantly, bending moment produced by wrist flexion/extension and torsion moment produced from forearm rotation could potentially hinder endochondral ossification at early stage of healing. The developed model could potentially assist orthopaedic surgeons in surgical pre-planning and designing post-operation physical therapy for treatment of distal radius fractures.

A Probabilistic Failure Risk Approach to The Problem of Articular Cartilage Lubrication

BACKGROUND AND OBJECTIVE

The geometrical and mechanical properties that characterise the cartilage contact gap are uncertain and spatially varied. To date the effects of such uncertainties on cartilage lubrication have not been explored. Using a probabilistic approach, the purpose of this study is to numerically investigate the influence of surficial cartilage glycoaminoglycan (GAG) content on joint lubrication behaviour. Gap asperity stiffness and polymer brush border (PBB) thickness are affected by the uncertainty of surficial GAG concentration, and so their correlated effects in maintaining hydrodynamic joint lubrication are investigated.

METHODS

Correlated sampling data are first generated by Monte Carlo simulation. These data are used as inputs for the cartilage contact model, which includes three distinctive features of cartilage tissue (tension-compression nonlinearity, aggrecan dependent permeability and compressive modulus) and fluid flow resistance effects of PBB on cartilage surface. The degree of hydrodynamic lubrication after thirty minutes of constant loading is used as an indicator for assessing the lubrication performance at the contact interface.

RESULTS

The increase of PBB thickness with GAG concentration enhances the hydrodynamic lubrication component in the cartilage contact gap, whereas increasing the asperity stiffness with GAG concentration impairs hydrodynamic lubrication. GAG loss rate increases with the rise of GAG concentration. More aggrecan shedding through the surface could result in a thicker and denser PBB, and therefore enhance the lubrication performance in mixed-mode regime. On the other hand, higher GAG content makes the asperities stiffer, which may impede contact gap closure, and thus encourage gap fluid loss and impair the lubrication performance of cartilage.

CONCLUSION

The lubrication performance of cartilage varies with the physiological conditions of the joint. Since a range of variables are internally related, the outcomes on joint lubrication are difficult to predict. A probabilistic approach accounting for the uncertainties can potentially result in more accurate evaluations of joint lubrication performance.

Cartilage rehydration: The sliding-induced hydrodynamic triggering mechanism

Loading-induced cartilage exudation causes loss of fluid from the tissue, joint space thinning and, in a long term prospective, the insurgence of osteoarthritis. Fortunately, experiments show that joints recover interstitial fluid and thicken during articulation after static loading, thus reversing the exudation process. Here, we provide the first original theoretical explanation to this crucial phenomenon, by implementing a numerical model capable of accounting for the multiscale porous lubrication occurring in joints. We prove that sliding-induced rehydration occurs because of hydrodynamic reasons and is specifically related to a wedge effect at the contact inlet. Furthermore, numerically predicted rehydration rates are consistent with experimentally measured rates and corroborate the robustness of the model here proposed. The paper provides key information, in terms of fundamental lubrication multiscale mechanisms, to understand the rehydration of cartilage and, more generally, of any biological tissue exhibiting a significant porosity: such a theoretical framework is, thus, crucial to inform the design of new effective cartilage-mimicking biomaterials. STATEMENT OF SIGNIFICANCE: Motion and, precisely, joints articulation ensures that cartilage tissues preserve adequate level of hydration and, thus, maintain excellent mechanical properties in terms of high resilience, considerable load-carrying capacity and remarkably low friction. Conversely, when statically loaded, cartilage starts to exudate, causing joint space thinning and, in the long term, possible osteoarthritis; joints motion is, thus, the key to prevent the degradation of the tissues. By developing a numerical multiscale lubrication theory, and by corroborating this approach with experiments, we provide the first original theoretical explanation to this motion-induced cartilage rehydration mechanism. Assessing the rehydration hydrodynamic origin is, in fact, fundamental not only to understand the joints physiology, but also to highlight a key requirement for cartilage-mimicking biomaterials.

The Effect of High-Intensity Intermittent Training on the Acute Gait Plantar Pressure in Healthy Young Adults

High-intensity intermittent training (HIIT) has been successfully applied in various sports activities, as HIIT was considered as one of the most efficient training methods of exercise for improving physical performance and reducing the weight of overweight individuals. However, its acute effects of HIIT on gait and balance performance were not addressed. Thus, in this study we examined the acute effects of HIIT on dynamic postural control compared with steady-state training (SST) by analyzing plantar pressure parameters. In this study, sixteen healthy male adults were examined in 3 days. After exhaustive ramp-like cycle ergometer testing, the maximal heart rate (HRmax) of each participant was determined on the first day, then either a 20 minutes HIIT at 80–90% of HRmax or a 20 minutes SST at 60% of HRmax was randomly performed on the second and third day, respectively. Plantar pressure parameters were collected at comfortable walking velocity immediately after HIIT and SST respectively, and compared with the baseline data of plantar pressure gathered before maximal ramp test on the first day. The results showed significant differences in the plantar pressure in these three conditions of gait. Compared to pre-intervention and pre-SST, peak pressure and maximum force in the middle and lateral metatarsal increased significantly in post-HIIT. Meanwhile, the foot balance data indicate that post-HIIT exhibits more foot pronation than baseline. The center of pressure (COP) trajectory was medially shifted during the stance phase in post-SST, and noticeably in post-HIIT. The displacement and velocity of medial-lateral COP in the initial contact phase were greater in post-HIIT; while during the forefoot contact phase, post-HIIT showed fewer time percentages and greater velocity of medial-lateral COP. In conclusion, a single high-intensity intermittent training session adversely affected the acute dynamic postural control than steady-state training in healthy male adults.

Melatonin: Effects on Cartilage Homeostasis and Therapeutic Prospects in Cartilage-related Diseases

Cartilage is a relatively simple connective tissue that plays a variety of roles in the human body, including joint support and protection, load bearing of the intervertebral discs, joint lubrication, formation of the external structure of the ears and nose and support of the trachea. The maintenance of cartilage homeostasis is therefore crucial. Cartilage-related diseases are difficult to diagnose and treat because their molecular and pathological mechanisms are not fully understood. Melatonin, which has a wide range of physiological effects, is an endocrine hormone mainly secreted by the pineal gland. Its biological effects include its antioxidant, antiaging, analgesic, and hypnotic effects and its ability to stabilize the circadian rhythm. In recent years, research on cartilage homeostasis and melatonin has been increasing, and melatonin has gradually been used in the treatment of cartilage-related diseases. Therefore, this article will briefly review the role of melatonin in cartilage homeostasis, including its anti-inflammatory effects and effects in protecting cartilage from damage by other factors and promoting chondrocyte growth and the expression of cartilage-related genes. Based on the above, the current status and future developmental direction of melatonin in the treatment of cartilage-related diseases are also discussed, demonstrating the broad prospects of melatonin in maintaining cartilage homeostasis and treating cartilage injury-related diseases.

The investigation of bone fracture healing under intramembranous and endochondral ossification

After trauma, fractured bone starts healing directly through bone union or indirectly through callus formation process. Intramembranous and endochondral ossification are two commonly known mechanisms of indirect healing. The present study investigated the bone fracture healing under intramembranous and endochondral ossification by developing theoretical models in conjunction with performing a series of animal experiments. Using experimentally determined mean bone densities in sheep tibia stabilized by the Locking Compression Plate (LCP) fixation system, the research outcomes showed that intramembranous and endochondral ossification can be described by Hill Function with two unique sets of function parameters in mechanical stimuli mediated fracture healing. Two different thresholds exist within the range of mechanical simulation index which could trigger significant intramembranous and endochondral ossification, with a relatively higher bone formation rate of endochondral ossification than that of intramembranous ossification. Furthermore, the increase of flexibility of the LCP system and the use of titanium LCP could potentially promote uniform bone formation across the fracture gap, ultimately better healing outcomes.

Compressive stress relaxation behavior of articular cartilage and its effects on fluid pressure and solid displacement due to non-Newtonian flow

In this study, we investigate the effects of the power-law index and permeability parameter on the deformation of soft tissue (articular cartilage) which is bathed in the non-Newtonian fluid under stress-relaxation in compression. Ramp displacement is imposed on the surface of hydrated soft tissue. Deformation of the tissue and the fluid pressure is examined for the fast and slow rate of compression. We have employed a linear biphasic mixture theory to develop a mathematical model for compressive stress-relaxation behavior of articular cartilage for non-Newtonian flow. Numerical results indicate that shear-thinning fluids induce less solid deformation and exhibit more fluid pressure as compared to shear-thickening fluids for fast and slow rate of compression. The results also show that linear permeability induces more deformation as compared to strain-dependent nonlinear permeability due to viscoelastic nature of articular cartilage.

Clinical Contrast-Enhanced Computed Tomography With Semi-Automatic Segmentation Provides Feasible Input for Computational Models of the Knee Joint

Computational models can provide information on joint function and risk of tissue failure related to progression of osteoarthritis (OA). Currently, the joint geometries utilized in modeling are primarily obtained via manual segmentation, which is time-consuming and hence impractical for direct clinical application. The aim of this study was to evaluate the applicability of a previously developed semi-automatic method for segmenting tibial and femoral cartilage to serve as input geometry for finite element (FE) models. Knee joints from seven volunteers were first imaged using a clinical computed tomography (CT) with contrast enhancement and then segmented with semi-automatic and manual methods. In both segmentations, knee joint models with fibril-reinforced poroviscoelastic (FRPVE) properties were generated and the mechanical responses of articular cartilage were computed during physiologically relevant loading. The mean differences in the absolute values of maximum principal stress, maximum principal strain, and fibril strain between the models generated from semi-automatic and manual segmentations were <1 MPa, <0.72% and <0.40%, respectively. Furthermore, contact areas, contact forces, average pore pressures, and average maximum principal strains were not statistically different between the models (p >0.05). This semi-automatic method speeded up the segmentation process by over 90% and there were only negligible differences in the results provided by the models utilizing either manual or semi-automatic segmentations. Thus, the presented CT imaging-based segmentation method represents a novel tool for application in FE modeling in the clinic when a physician needs to evaluate knee joint function.

The status and challenges of replicating the mechanical properties of connective tissues using additive manufacturing

The ability to fabricate complex structures via precise and heterogeneous deposition of biomaterials makes additive manufacturing (AM) a leading technology in the creation of implants and tissue engineered scaffolds. Connective tissues (CTs) remain attractive targets for manufacturing due to their "simple" tissue compositions that, in theory, are replicable through choice of biomaterial(s) and implant microarchitecture. Nevertheless, characterisation of the mechanical and biological functions of 3D printed constructs with respect to their host tissues is often limited and remains a restriction towards their translation into clinical practice. This review aims to provide an update on the current status of AM to mimic the mechanical properties of CTs, with focus on arterial tissue, articular cartilage and bone, from the perspective of printing platforms, biomaterial properties, and topological design. Furthermore, the grand challenges associated with the AM of CT replacements and their subsequent regulatory requirements are discussed to aid further development of reliable and effective implants.

A probabilistic-based approach for computational simulation of bone fracture healing

BACKGROUND AND OBJECTIVE

It is widely known that bone fracture healing is affected by mechanical factors such as fracture geometry, fixation configuration and post-operative weight bearing loading. However, there are several uncertainties associated with the magnitude of the mechanical factors affecting bone healing as it is challenging to adjust and control them in clinical practice. The current bone fracture healing investigations mainly adopt a deterministic approach for identifying the optimal mechanical conditions for a favourable bone healing outcome. However, a probabilistic approach should be used in the analysis to incorporate such uncertainties for prediction of bone healing.

METHODS

In this study we developed a probabilistic-based computational model to predict the probability of delayed healing or non-union under different fracture treatment mechanical conditions for fractures stabilised by locking plates.

RESULTS

The results show that there is a strong positive linear correlation between the mechanical stimulations (S) in the fracture gap and the magnitude of weight bearing, the bone-plate distance (BPD) and the plate working length (WL), whereas the fracture gap size has a highly negative and nonlinear correlation with S. While the results show that fracture mechanical microenvironment is more sensitive to the uncertainties in WL compared to BPD, the uncertainty associated with the magnitude of WL is very low and can be resulted from implant manufacturing tolerance. However, there is a high uncertainty associated with the magnitude of BPD as it cannot be accurately adjusted during the surgery. The results show that the tissue differentiation at the far cortex of fracture gap is more sensitive to the variation of BPD compared with that at the near cortex. The probability of delayed healing (fibrous tissue formation) at far cortex is increased from 0% to 40% when coefficient of variation (COV) of BPD rises from 0.1 to 0.9 (for average BPD = 2 mm, WL = 65 mm, fracture gap size = 3 mm and Weight bearing = 150 N). Further, both near and far cortex of fracture site are sensitive to the variation in weight bearing loading.

CONCLUSIONS

The developed probabilistic model may lead to useful guidelines that could help orthopaedic surgeons identify how reliable a specific fracture treatment strategy is.

A Novel Method of Analysis for Prolonged-Standing Data: Accounting for Joint and Muscle Discomfort

Background

The typical American worker spends about two-thirds of their work day standing. Prolonged standing has been found to be associated with acute and chronic adverse health outcomes. There is considerable variability among existing methods of analysis for prolonged-standing data, and therefore difficulty interpreting and comparing results across studies.

Purpose

The purpose of this study is to develop a bodyweight transfer analysis method that incorporates factors of both time and amplitude of loading. This method was then applied to actual prolonged-standing data, to understand how the results of this method are impacted by time spent standing, and how the results relate to previously-reported methods of analysis for weight shifting data.

Methods

Seven subjects (six male, one female) stood with each foot on one of two force plates for 6 h with a 5-min seated rest break between hours. Our new method identified two different types of events: fidgets and weight shifts. Center-of-pressure data were analyzed with the proposed method and three existing methods of analysis.

Results

Subjects utilized different quantities of fidgets and weight shifts over the course of the trials. Existing methods of analysis identified a wide range in number of events, with some methods consistently identifying more events than others. These existing methods significantly differed from the proposed method. Fidgets, weight shifts, and fidgets + weight shifts, as identified using the proposed method, had significant interactions with time, while only one of the existing methods showed a significant time interaction.

Conclusions

The conclusions drawn from analysis of prolonged standing center-of-pressure data can differ significantly depending on the method of analysis used. The method proposed here accounts for the different sources of discomfort and the tissue characteristics of these sources. Future work should explore the relationships between physiologic parameters and fidgets and weight shifts, so that appropriate clinical interventions can be identified.

Analysis of the mechanical effects of defect shape on damage evolution of articular cartilage under rolling load

To study the mechanical effects of defect shape on the damage evolution of knee cartilage and find the causes of fragments, so as to obtain damage evolution rules and determine the most appropriate shape used in a clinical repair. A porous viscoelasticity fiber-reinforced 2D numerical model with different micro-defect shapes was established which considered the depth-dependent Young's modulus, fiber distribution, porosity and permeability. The stress-strain relationship, interstitial hydraulic and interstitial flow velocity was obtained under rolling load. The results showed that damage developed at the bottom corner of the defect, preferentially deep within the cartilage tangential to the fibers direction, and then extended to the surface along adjacent fibers, finally forming fragments. In the early stages of damage, the shear stress and interstitial flow velocity within cartilage with a rectangular cross-sectional defect were the lowest, while interstitial hydraulic pressure was the highest, followed by 100° trapezoid and semicircle, and finally 80° trapezoid defects. In the later stage of damage, the results were very similar. The shear strain, interstitial flow velocity and interstitial hydraulic pressure decreased with increasing defect depth. Therefore, defect shape only affected damage evolution in the early stages. The fragments in cartilage were the result of the damage evolution which sizes were correlated with the initial defect depth. The damage velocity of cartilage with a rectangular section-incision was the slowest. Finally, we concluded that cylindrical incisions are optimal in clinical surgery. These results provide a theoretical basis for the clinical interpretation of pathological degeneration and repair therapy.

A computational algorithm to simulate disorganization of collagen network in injured articular cartilage

Cartilage defects are a known risk factor for osteoarthritis. Estimation of structural changes in these defects could help us to identify high risk defects and thus to identify patients that are susceptible for the onset and progression of osteoarthritis. Here, we present an algorithm combined with computational modeling to simulate the disorganization of collagen fibril network in injured cartilage. Several potential triggers for collagen disorganization were tested in the algorithm following the assumption that disorganization is dependent on the mechanical stimulus of the tissue. We found that tensile tissue stimulus alone was unable to preserve collagen architecture in intact cartilage as collagen network reoriented throughout the cartilage thickness. However, when collagen reorientation was based on both tensile tissue stimulus and tensile collagen fibril strains or stresses, the collagen network architecture was preserved in intact cartilage. Using the same approach, substantial collagen reorientation was predicted locally near the cartilage defect and particularly at the cartilage-bone interface. The developed algorithm was able to predict similar structural findings reported in the literature that are associated with experimentally observed remodeling in articular cartilage. The proposed algorithm, if further validated, could help to predict structural changes in articular cartilage following post-traumatic injury potentially advancing to impaired cartilage function.