Predicting Knee Osteoarthritis

The future of in-field sports biomechanics: wearables plus modelling compute real-time in vivo tissue loading to prevent and repair musculoskeletal injuries

This paper explores the use of biomechanics in identifying the mechanistic causes of musculoskeletal tissue injury and degeneration. It appraises how biomechanics has been used to develop training programmes aiming to maintain or recover tissue health. Tissue health depends on the functional mechanical environment experienced by tissues during daily and rehabilitation activities. These environments are the result of the interactions between tissue motion, loading, biology, and morphology. Maintaining health of and/or repairing musculoskeletal tissues requires targeting the "ideal" in vivo tissue mechanics (i.e., loading and deformation), which may be enabled by appropriate real-time biofeedback. Recent research shows that biofeedback technologies may increase their quality and effectiveness by integrating a personalised neuromusculoskeletal modelling driven by real-time motion capture and medical imaging. Model personalisation is crucial in obtaining physically and physiologically valid predictions of tissue biomechanics. Model real-time execution is crucial and achieved by code optimisation and artificial intelligence methods. Furthermore, recent work has also shown that laboratory-based motion capture biomechanical measurements and modelling can be performed outside the laboratory with wearable sensors and artificial intelligence. The next stage is to combine these technologies into well-designed easy to use products to guide training to maintain or recover tissue health in the real-world.

Study of adiponectin gene (rs1501299) polymorphism and serum adiponectin level in patients with primary knee osteoarthritis

BACKGROUND

We aimed to study, for the first time in the Egyptian population, the relationship between the serum adiponectin level in knee osteoarthritis (KOA) patients and its correlation with clinical, radiological, and ultrasonographic characteristics. Additionally, investigate the relationship between the adiponectin (ADIPOQ) gene rs1501299 (+ 276G/T) polymorphism and KOA susceptibility and severity.

METHODS

This case-control study enrolled 40 patients with primary KOA and 40 matched controls. All patients underwent physical examination of the knee, pain assessment using the visual analogue scale (VAS), and functional evaluation by Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Severity of KOA was assessed by Kellgren Lawrence (KL) grading scale and ultrasonography grading systems. Serum adiponectin levels and adiponectin (ADIPOQ) gene single nucleotide polymorphism (SNP) (rs1501299) genotyping were done for all patients and controls.

RESULTS

The study included 40 patients with primary symptomatic KOA and 40 controls with comparable age, sex, and body mass index. The genotype of the rs1501299 (+ 276G/T) polymorphism of the ADIPOQ gene was determined using TaqMan allelic discrimination. An enzyme-linked immunosorbent test was used to measure the level of serum adiponectin. The Western Ontario and McMaster Universities Osteoarthritis (WOMAC) score was used to assess functional capability, while the visual analogue scale was utilised to assess knee pain. Using the Kellgren-Lawrence (KL) grading method and global femoral cartilage (GFC) ultrasound grading, the severity of KOA was assessed. No significant differences between patients and controls as regards the genotype distributions and allele frequencies (p = 0.400, p = 0.507, respectively) of ADIPOQ gene rs1501299 (+ 276G/T) polymorphism. Furthermore, serum adiponectin level was significantly higher in the patients compared to healthy subjects (p < 0.001). Additionally, adiponectin level had a significant negative correlation with disease severity as evaluated by KL and GFC grading (r=-0.351, p = 0.027 and r=-0.397, p = 0.011, respectively).

CONCLUSIONS

The ADIPOQ gene rs1501299 (+ 276G/T) polymorphism was not associated with KOA severity or vulnerability. The level of adiponectin considerably reduced as the severity of KOA rose, indicating that adiponectin may have a preventive effect in KOA.

A synoptic literature review of animal models for investigating the biomechanics of knee osteoarthritis

Osteoarthritis (OA) is a common chronic disease largely driven by mechanical factors, causing significant health and economic burdens worldwide. Early detection is challenging, making animal models a key tool for studying its onset and mechanically-relevant pathogenesis. This review evaluate current use of preclinical in vivo models and progressive measurement techniques for analysing biomechanical factors in the specific context of the clinical OA phenotypes. It categorizes preclinical in vivo models into naturally occurring, genetically modified, chemically-induced, surgically-induced, and non-invasive types, linking each to clinical phenotypes like chronic pain, inflammation, and mechanical overload. Specifically, we discriminate between mechanical and biological factors, give a new explanation of the mechanical overload OA phenotype and propose that it should be further subcategorized into two subtypes, post-traumatic and chronic overloading OA. This review then summarises the representative models and tools in biomechanical studies of OA. We highlight and identify how to develop a mechanical model without inflammatory sequelae and how to induce OA without significant experimental trauma and so enable the detection of changes indicative of early-stage OA in the absence of such sequelae. We propose that the most popular post-traumatic OA biomechanical models are not representative of all types of mechanical overloading OA and, in particular, identify a deficiency of current rodent models to represent the chronic overloading OA phenotype without requiring intraarticular surgery. We therefore pinpoint well standardized and reproducible chronic overloading models that are being developed to enable the study of early OA changes in non-trauma related, slowly-progressive OA. In particular, non-invasive models (repetitive small compression loading model and exercise model) and an extra-articular surgical model (osteotomy) are attractive ways to present the chronic natural course of primary OA. Use of these models and quantitative mechanical behaviour tools such as gait analysis and non-invasive imaging techniques show great promise in understanding the mechanical aspects of the onset and progression of OA in the context of chronic knee joint overloading. Further development of these models and the advanced characterisation tools will enable better replication of the human chronic overloading OA phenotype and thus facilitate mechanically-driven clinical questions to be answered.

Predicting ankle and knee sagittal kinematics and kinetics using an ankle-mounted inertial sensor

The purpose of this study was to develop a machine learning model to reconstruct time series kinematic and kinetic profiles of the ankle and knee joint across six different tasks using an ankle-mounted IMU. Four male collegiate basketball players performed repeated tasks, including walking, jogging, running, sidestep cutting, max-height jumping, and stop-jumping, resulting in a total of 102 movements. Ankle and knee flexion-extension angles and moments were estimated using motion capture and inverse dynamics and considered 'actual data' for the purpose of model fitting. Synchronous acceleration and angular velocity data were collected from right ankle-mounted IMUs. A time-series feature extraction model was used to determine a set of features used as input to a random forest regression model to predict the ankle and knee kinematics and kinetics. Five-fold cross-validation was performed to verify the model accuracy, and statistical parametric mapping was used to determine the difference between the predicted and experimental time series. The random forest regression model predicted the time-series profiles of the ankle and knee flexion-extension angles and moments with high accuracy (Kinematics: R2 ranged from 0.782 to 0.962, RMSE ranged from 2.19° to 11.58°; Kinetics: R2 ranged from 0.711 to 0.966, RMSE ranged from 0.10 Nm/kg to 0.41 Nm/kg). There were differences between predicted and actual time series for the knee flexion-extension moment during stop-jumping and walking. An appropriately trained feature-based regression model can predict time series knee and ankle joint angles and moments across a wide range of tasks using a single ankle-mounted IMU.

Prognostic model to predict the incidence of radiographic knee osteoarthritis

OBJECTIVE

Early diagnosis of knee osteoarthritis (KOA) in asymptomatic stages is essential for the timely management of patients using preventative strategies. We develop and validate a prognostic model useful for predicting the incidence of radiographic KOA (rKOA) in non-radiographic osteoarthritic subjects and stratify individuals at high risk of developing the disease.

METHODS

Subjects without radiographic signs of KOA according to the Kellgren and Lawrence (KL) classification scale (KL=0 in both knees) were enrolled in the OA initiative (OAI) cohort and the Prospective Cohort of A Coruña (PROCOAC). Prognostic models were developed to predict rKOA incidence during a 96-month follow-up period among OAI participants based on clinical variables and serum levels of the candidate protein biomarkers APOA1, APOA4, ZA2G and A2AP. The predictive capability of the biomarkers was assessed based on area under the curve (AUC), and internal validation was performed to correct for overfitting. A nomogram was plotted based on the regression parameters. Model performance was externally validated in the PROCOAC.

RESULTS

282 participants from the OAI were included in the development dataset. The model built with demographic, anthropometric and clinical data (age, sex, body mass index and WOMAC pain score) showed an AUC=0.702 for predicting rKOA incidence during the follow-up. The inclusion of ZA2G, A2AP and APOA1 data significantly improved the model's sensitivity and predictive performance (AUC=0.831). The simplest model, including only clinical covariates and ZA2G and A2AP serum levels, achieved an AUC=0.826. Both models were internally cross-validated. Predictive performance was externally validated in an independent dataset of 100 individuals from the PROCOAC (AUC=0.713).

CONCLUSION

A novel prognostic model based on common clinical variables and protein biomarkers was developed and externally validated to predict rKOA incidence over a 96-month period in individuals without any radiographic signs of disease. The resulting nomogram is a useful tool for stratifying high-risk populations and could potentially lead to personalised medicine strategies for treating OA.

Evaluation of an Unloading Concept for Knee Osteoarthritis: A Pilot Study in a Small Patient Group

Joint compressive forces have been identified as a risk factor for osteoarthritis disease progression. Therefore, unloader braces are a common treatment with the aim of relieving pain, but their effects are not clearly documented in the literature. A knee brace concept was tested with the aim of reducing joint loads and pain in knee osteoarthritis patients by applying an extension moment exclusively during the stance phase. The ideal effects were evaluated during gait based on musculoskeletal modeling of six patients, and experimental tests with a prototype brace were conducted on one patient. The effects were evaluated using electromyography measurements and musculoskeletal models to evaluate the muscle activation and knee compressive forces, respectively. The ideal brace simulations revealed a varying reduction of the first peak knee force between 3.5% and 33.8% across six patients whereas the second peak was unaffected. The prototype reduced the peak vasti muscle activation with 7.9% and musculoskeletal models showed a reduction of the first peak knee compressive force of up to 26.3%. However, the prototype brace increased the knee joint force impulse of up to 17.1% and no immediate pain reduction was observed. The reduction of the first peak knee compressive force, using a prototype on a single patient, indicates a promising effect from an applied knee extension moment for reducing knee joint loads during normal gait. However, further clinical experiments with this brace method are required to evaluate the long-term effects on both pain and disease progression in knee osteoarthritis patients.

Towards a Transferable Modeling Method of the Knee to Distinguish Between Future Healthy Joints from Osteoarthritic Joints: Data from the Osteoarthritis Initiative

Computational models can be used to predict the onset and progression of knee osteoarthritis. Ensuring the transferability of these approaches among computational frameworks is urgent for their reliability. In this work, we assessed the transferability of a template-based modeling strategy, based on the finite element (FE) method, by implementing it on two different FE softwares and comparing their results and conclusions. For that, we simulated the knee joint cartilage biomechanics of 154 knees using healthy baseline conditions and predicted the degeneration that occurred after 8 years of follow-up. For comparisons, we grouped the knees using their Kellgren-Lawrence grade at the 8-year follow-up time and the simulated volume of cartilage tissue that exceeded age-dependent thresholds of maximum principal stress. We considered the medial compartment of the knee in the FE models and used ABAQUS and FEBio FE softwares for simulations. The two FE softwares detected different volumes of overstressed tissue in corresponding knee samples (p < 0.01). However, both programs correctly distinguished between the joints that remained healthy and those that developed severe osteoarthritis after the follow-up (AUC = 0.73). These results indicate that different software implementations of a template-based modeling method similarly classify future knee osteoarthritis grades, motivating further evaluations using simpler cartilage constitutive models and additional studies on the reproducibility of these modeling strategies.

Prediction of progression rate and fate of osteoarthritis: Comparison of machine learning algorithms

Appropriate prediction models can assist healthcare systems in delaying or reversing osteoarthritis (OA) progression. We aimed to identify a reliable algorithm for predicting the progression rate and fate of OA based on patient-specific information. From May 2003 to 2019, 83,280 knees were collected. Age, sex, body mass index, bone mineral density, physical demands for occupation, comorbidities, and initial Kellgren-Lawrence (K-L) grade were used as variables for the prediction models. The prediction targets were divided into dichotomous groups for even distribution. We compared the performances of logistic regression (LR), random forest (RF), and extreme gradient boost (XGB) algorithms. Each algorithm had the best precision when the model used all variables. XGB showed the best results in accuracy, recall, F1 score, specificity, and error rates (progression rate/fate of OA: 0.710/0.877, 0.542/0.637, 0.637/0.758, 0.859/0.981, and 0.290/0.123, respectively). The feature importance of RF and XGB had the same order up to the top six for each prediction target. Age and initial K-L grade had the highest feature importance in RF and XGB for the progression rate and fate of OA, respectively. The XGB and RF machine learning algorithms showed better performance than conventional LR in predicting the progression rate and fate of OA. The best performance was obtained when all variables were combined using the XGB algorithm. For each algorithm, the initial K-L grade and physical demand for occupation were the greatest contributors with superior feature importance compared with the others.

What Influences Proprioceptive Impairments in Patients with Rheumatic Diseases? Analysis of Different Factors

Rheumatic diseases lead to postural problems, which increase the risk of falls and lead to greater disability. The aim of the present work is to evaluate posture disorders in patients with osteoarthritis (OA) and rheumatoid arthritis (RA), as well as to evaluate the influence of other factors. A total of 71 subjects were enrolled in this study. Joint position sense (JPS) and the functional assessment of proprioception on a balance platform for both lower limbs were examined. The Average Trace Error (ATE), test time (t), and Average Platform Force Variation (AFV) were calculated. Additionally, an equilibrium test was carried out in the one-legged standing position (Single Leg Stance-SLS). The results were compared in several ways and revealed the following: (1) A JPS of 10° plantar flexion in RA obtained significantly worse results when repeating the movement than OA; the ATEs were significantly lower in RA; and RA needed more support during SLS assessment. (2) RA patients with higher DAS28 had statistically significantly higher values in JPS, with 5° plantar flexion and 10° dorsal flexion, SLS assessment, and stabilometric rates. A statistically significant correlation between DAS28 and RA was found in a JPS of 10° plantar flexion. The VAS ruler demonstrated a significant moderate correlation with t. (3) Patients who experienced at least one fall demonstrated higher JPS and t. Our study shows that proprioception is the most influenced by the nature of the disease and the level of disease activity. We can see that the stability and balance functions are also greatly influenced by the patient's falling experience and the level of pain. These findings may be useful in designing an optimal proprioception-enhancing movement training plan.

High tibiofemoral contact and muscle forces during gait are associated with radiographic knee OA progression over 3 years

BACKGROUND

The objective of this study was to investigate differences in tibiofemoral joint contact forces between individuals with moderate medial OA who exhibit radiographic knee OA progression within 3 years versus those who do not, and to understand the relationship between model-predicted contact forces and net external moments for this population.

METHODS

27 individuals with moderate medial compartment knee OA underwent baseline instrumented gait analysis. OA progressors were defined as those who experienced at least a one grade increase in medial joint space narrowing at three years. An electromyography-driven musculoskeletal model was used to estimate muscle and tibiofemoral contact forces at baseline, which were compared between progressors and non-progressors using t-tests.

RESULTS

Seven individuals experienced radiographic OA progression by 3 years. Progressors walked with significantly higher peaks of medial and total tibiofemoral contact forces, and higher impulse of medial contact forces. Significant and high correlations were found between: first peaks of medial and total contact forces with first peak of the knee adduction moment (R² = 0.74; R² = 0.59); second peaks of medial and total knee contact forces with second peaks of knee adduction and flexion moments (R² = 0.71; R² = 0.68); medial knee contact force impulse with knee adduction moment impulse (R² = 0.76).

CONCLUSIONS

Higher tibiofemoral joint contact forces during walking were associated with three-year radiographic knee OA progression based on medial joint space narrowing. These results support the need for strategies that reduce compressive knee contact forces through the reduction of adduction and flexion moments during walking.

Do Individualized Patient-Specific Situations Predict the Progression Rate and Fate of Knee Osteoarthritis? Prediction of Knee Osteoarthritis

Factors affecting the progression rate and fate of osteoarthritis need to be analyzed when considering patient-specific situation. This study aimed to identify the rate of remarkable progression and fate of primary knee osteoarthritis based on patient-specific situations. Between May 2003 and May 2019, 83,280 patients with knee pain were recruited for this study from the clinical data warehouse. Finally, 2492 knees with pain that were followed up for more than one year were analyzed. For analyzing affecting factors, patient-specific information was categorized and classified as demographic, radiologic, social, comorbidity disorders, and surgical intervention data. The degree of contribution of factors to the progression rate and the fate of osteoarthritis was analyzed. Bone mineral density (BMD), Kellgren-Lawrence (K-L) grade, and physical occupational demands were major contributors to the progression rate of osteoarthritis. Hypertension, initial K-L grade, and physical occupational demands were major contributors to the outcome of osteoarthritis. The progression rate and fate of osteoarthritis were mostly affected by the initial K-L grade and physical occupational demands. Patients who underwent surgical intervention for less than five years had the highest proportion of initial K-L grade 2 (49.0%) and occupations with high physical demand (41.3%). In identifying several contributing factors, the initial K-L grade and physical occupational demands were the most important factors. BMD and hypertension were also major contributors to the progression and fate of osteoarthritis, and the degree of contribution was lower compared to the two major factors.

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.

Development of a personalized shared decision-making tool for knee osteoarthritis and user-testing with African American and Latina women

Background

Patients with chronic knee pain are often unaware of treatment options and likely outcomes-information that is critical to decision-making. A consistent framework for communicating patient-personalized information enables clinicians to provide consistent, targeted, and relevant information. Our objective was to user-test a shared decision-making (SDM) tool for chronic knee pain.

Methods

A cross-functional team developed a Markov-based health economics model and tested the model outputs with patient panels, patient and clinician focus groups, and clinical specialists. The resulting SDM tool was user-tested in a parallel-designed, randomized controlled study with 52 African American and 52 Latina women from geographically representative areas of the US. Participants were randomized to counseling with or without the SDM tool. Feedback was collected at intervention and at 1 month after intervention and analyzed with Student's t-tests and Chi-squared analyses (alpha = 0.05).

Results

Qualitative results indicated patients understood the material, rated the overall experience highly, and were likely to recommend the physician. The SDM group reported high satisfaction with the tool. A greater proportion of the SDM group (56%) reported increased physical activity over baseline at 1 month compared with the control group (33%) (P = 0.0005). New use of medications for knee pain (58% SDM; 49% control) did not differ significantly between groups (P = 0.15).

Conclusion

Use of this innovative SDM tool was associated with high satisfaction and a significant increase in self-reported physical activity level at 1 month. The SDM tool may elicit behavioral changes to promote musculoskeletal health.

Subject-specific biomechanical analysis to estimate locations susceptible to osteoarthritis-Finite element modeling and MRI follow-up of ACL reconstructed patients

The aims of this case-control study were to: (1) Identify cartilage locations and volumes at risk of osteoarthritis (OA) using subject-specific finite element (FE) models; (2) Quantify the relationships between the simulated biomechanical parameters and T₂ and T_1ρ relaxation times of magnetic resonance imaging (MRI). We created subject-specific FE models for seven patients with anterior cruciate ligament (ACL) reconstruction and six controls based on a previous proof-of-concept study. We identified locations and cartilage volumes susceptible to OA, based on maximum principal stresses and absolute maximum shear strains in cartilage exceeding thresholds of 7 MPa and 32%, respectively. The locations and volumes susceptible to OA were compared qualitatively and quantitatively against 2-year longitudinal changes in T₂ and T_1ρ relaxation times. The degeneration volumes predicted by the FE models, based on excessive maximum principal stresses, were significantly correlated (r = 0.711, p < 0.001) with the degeneration volumes determined from T₂ relaxation times. There was also a significant correlation between the predicted stress values and changes in T₂ relaxation time (r = 0.649, p < 0.001). Absolute maximum shear strains and changes in T_1ρ relaxation time were not significantly correlated. Five out of seven patients with ACL reconstruction showed excessive maximum principal stresses in either one or both tibial cartilage compartments, in agreement with follow-up information from MRI. Expectedly, for controls, the FE models and follow-up information showed no degenerative signs. Our results suggest that the presented modelling methodology could be applied to prospectively identify ACL reconstructed patients at risk of biomechanically driven OA, particularly by the analysis of maximum principal stresses of cartilage.

Consequences of Progressive Full-Thickness Focal Chondral Defects Involving the Medial and Lateral Femoral Condyles After Meniscectomy: A Biomechanical Study Using a Goat Model

Background:

Full-thickness chondral defects alter tibiofemoral joint homeostasis and, if left untreated, have the potential to progress to osteoarthritis.

Purpose:

To assess the effects of isolated and dual full-thickness chondral defect size and location on the biomechanical properties of the lateral femoral condyle (LFC) and medial femoral condyle (MFC) during dynamic knee flexion in goat knees without menisci.

Methods:

In 12 goat knees, we created progressively increasing full-thickness circular chondral defects (3-, 5-, and 7.5-mm diameter) in the weightbearing contact area of flexion and extension in the MFC, the LFC, or both. Each knee was fixed into a custom steel frame and attached to a motor with sensors inserted intra-articularly. For each testing condition, the knee was loaded to 100 N and underwent a dynamic range of motion between 90° of flexion and 30° of extension. The following parameters were collected: contact area, contact pressure, contact force, peak area, and peak pressure.

Study Design:

Controlled laboratory study.

Results:

The peak pressure at the defect rim of the MFC at full extension increased by 51.51% from no defect (1.887 MPa) to a 7.5-mm defect (2.859 MPa) (P < .001), and the peak pressure at the defect rim of the LFC at full extension increased by 139.14% from no defect (1.704 MPa) to a 7.5-mm defect (4.075 MPa) (P < .001). The peak pressures for LFC defects at all 3 diameters were significantly greater when compared with dual defects consisting of increasing LFC defect diameter and constant MFC defect diameter (P < .001 for all).

Conclusion:

Extremely large increases in peak pressure were seen at the rim of articular cartilage defects when evaluated under dynamic loading conditions. Isolated LFC defects experienced a greater increase in defect rim stress concentrations when compared with isolated MFC defects for equivalent increases in defect size. Defect size played a significant role independent of location for peak pressures on the MFC and LFC.

Clinical Relevance:

Significant rim-loading effects increase with defect size under dynamic loading and may result in increasingly rapid progression of articular cartilage lesions. Within the context of this goat model, findings suggest that lateral compartment chondral lesions are more likely to progress than medial compartment lesions of equivalent size.

Development and Functional Testing of An Unloading Concept for Knee Osteoarthritis Patients: A Pilot Study

This paper presents a knee brace design that applies an extension moment to unload the muscles in stance phase during gait, and thereby the knee, as alternative to conventional valgus braces for knee osteoarthritis patients. The concept was tested on one healthy subject during normal gait with a prototype, which was designed to activate and deactivate in order to apply the extension moment in the stance phase only and hereby avoid any interference during the swing phase. Electromyography measurements and musculoskeletal models were used to evaluate the brace effects on muscle activation and knee compressive forces respectively. Simulations predicted an ideal reduction of up to 36%, whereas experimental tests revealed a reduction of up to 24% with the current prototype. The prototype brace also reduced the knee joint force impulse up to 9% and EMG peak signal of the vasti muscles with up to 19%. Due to these reductions on a healthy subject, this bracing approach seem promising for reducing knee loads during normal gait. However, further clinical experiments on knee osteoarthritis patients are required to evaluate the effect on both pain and disease progression.

Risk Assessment of the Progression of Early Knee Osteoarthritis by Collagen Neoepitope C2C: A Longitudinal Study of an Estonian Middle-Aged Cohort

One of the unmet needs to be addressed is prognostic biomarkers for early knee osteoarthritis (kOA). We aimed to study the association of urinary collagen type-II C-terminal cleavage neoepitope (uC2C) with the emergence and progression of kOA. The longitudinal data of 330 subjects (aged 32-60 years) from an Estonian population-based cohort were used. The radiographic progression was evaluated by the grading system of Nagaosa et al. of knee compartments at baseline and three years later. The emerging kOA consisted of subjects with developing osteophytes or joint space narrowing, whereas kOA progressors showed aggravation of radiographic grade. Baseline uC2C levels were measured by the IBEX-uC2C assay. At baseline, the subjects were middle-aged (mean age, 47.6 years) and overweight (mean BMI, 28.0 kg/m2), and the majority of them (51.2%) had a diagnosis of kOA grade 1. Multiple logistic regression models adjusted for sex, age, and BMI were used for risk calculations. We demonstrate that increased uC2C accurately predicted the risk of emerging of kOA (OR = 5.87 (1.71-20.22); AUC = 0.79) compared with controls without radiographic kOA over 12 years. However, the most accurate prediction of progression by the biomarker was found in women (OR = 23.0 (2.2-245), AUC = 0.91). In conclusion, uC2C may be a promising candidate as a prognostic biomarker for kOA progression, particularly of emerging kOA in women.

An in silico Framework of Cartilage Degeneration That Integrates Fibril Reorientation and Degradation Along With Altered Hydration and Fixed Charge Density Loss

Injurious mechanical loading of articular cartilage and associated lesions compromise the mechanical and structural integrity of joints and contribute to the onset and progression of cartilage degeneration leading to osteoarthritis (OA). Despite extensive in vitro and in vivo research, it remains unclear how the changes in cartilage composition and structure that occur during cartilage degeneration after injury, interact. Recently, in silico techniques provide a unique integrated platform to investigate the causal mechanisms by which the local mechanical environment of injured cartilage drives cartilage degeneration. Here, we introduce a novel integrated Cartilage Adaptive REorientation Degeneration (CARED) algorithm to predict the interaction between degenerative variations in main cartilage constituents, namely collagen fibril disorganization and degradation, proteoglycan (PG) loss, and change in water content. The algorithm iteratively interacts with a finite element (FE) model of a cartilage explant, with and without variable depth to full-thickness defects. In these FE models, intact and injured explants were subjected to normal (2 MPa unconfined compression in 0.1 s) and injurious mechanical loading (4 MPa unconfined compression in 0.1 s). Depending on the mechanical response of the FE model, the collagen fibril orientation and density, PG and water content were iteratively updated. In the CARED model, fixed charge density (FCD) loss and increased water content were related to decrease in PG content. Our model predictions were consistent with earlier experimental studies. In the intact explant model, minimal degenerative changes were observed under normal loading, while the injurious loading caused a reorientation of collagen fibrils toward the direction perpendicular to the surface, intense collagen degradation at the surface, and intense PG loss in the superficial and middle zones. In the injured explant models, normal loading induced intense collagen degradation, collagen reorientation, and PG depletion both on the surface and around the lesion. Our results confirm that the cartilage lesion depth is a crucial parameter affecting tissue degeneration, even under physiological loading conditions. The results suggest that potential fibril reorientation might prevent or slow down fibril degradation under conditions in which the tissue mechanical homeostasis is perturbed like the presence of defects or injurious loading.

Hybrid fluorescence-AFM explores articular surface degeneration in early osteoarthritis across length scales

Atomic force microscopy (AFM) has become a powerful tool for the characterization of materials at the nanoscale. Nevertheless, its application to hierarchical biological tissue like cartilage is still limited. One reason is that such samples are usually millimeters in size, while the AFM delivers much more localized information. Here a combination of AFM and fluorescence microscopy is presented where features on a millimeter sized tissue sample are selected by fluorescence microscopy on the micrometer scale and then mapped down to nanometer precision by AFM under native conditions. This served us to show that local changes in the organization of fluorescent stained cells, a marker for early osteoarthritis, correlate with a significant local reduction of the elastic modulus, local thinning of the collagen fibers, and a roughening of the articular surface. This approach is not only relevant for cartilage, but in general for the characterization of native biological tissue from the macro- to the nanoscale. STATEMENT OF SIGNIFICANCE: Different length scales have to be studied to understand the function and dysfunction of hierarchically organized biomaterials or tissues. Here we combine a highly stable AFM with fluorescence microscopy and precisely motorized movement to correlate micro- and nanoscopic properties of articular cartilage on a millimeter sized sample under native conditions. This is necessary for unraveling the relationship between microscale organization of chondrocytes, micrometer scale changes in articular cartilage properties and nanoscale organization of collagen (including D-banding). We anticipate that such studies pave the way for a guided design of hierarchical biomaterials.

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.

Acacetin Suppresses IL-1β-Induced Expression of Matrix Metalloproteinases in Chondrocytes and Protects against Osteoarthritis in a Mouse Model by Inhibiting NF-κB Signaling Pathways

Osteoarthritis (OA) is a very common chronic joint dysfunction, and there is currently a poor understanding of its etiology and pathogenesis. Therefore, there are no active disease-modifying drugs currently available for clinical treatment. Several natural compounds have been shown to play a role in inhibiting OA progression. The present study is aimed at investigating the curative effects of acacetin, a natural flavonoid compound, against OA. Our results demonstrated that MMP-1, MMP-3, and MMP-13 were highly expressed in OA specimens. Acacetin inhibited the interleukin-1β- (IL-1β-) induced expression of MMP-1, MMP-3, and MMP-13in chondrocytes by blocking nuclear factor-κB (NF-κB) signaling pathways. Furthermore, we found that acacetin suppressed OA progression and inhibited the expression of MMP-1, MMP-3, and MMP-13 in ACLT-induced OA mice. Taken together, our study revealed that acacetin may serve as a potential drug for treating OA.

Identification of locations susceptible to osteoarthritis in patients with anterior cruciate ligament reconstruction: Combining knee joint computational modelling with follow-up T1ρ and T2 imaging

BACKGROUND

Finite element modelling can be used to evaluate altered loading conditions and failure locations in knee joint tissues. One limitation of this modelling approach has been experimental comparison. The aims of this proof-of-concept study were: 1) identify areas susceptible to osteoarthritis progression in anterior cruciate ligament reconstructed patients using finite element modelling; 2) compare the identified areas against changes in T₂ and T_1ρ values between 1-year and 3-year follow-up timepoints.

METHODS

Two patient-specific finite element models of knee joints with anterior cruciate ligament reconstruction were created. The knee geometry was based on clinical magnetic resonance imaging and joint loading was obtained via motion capture. We evaluated biomechanical parameters linked with cartilage degeneration and compared the identified risk areas against T₂ and T_1ρ maps.

FINDINGS

The risk areas identified by the finite element models matched the follow-up magnetic resonance imaging findings. For Patient 1, excessive values of maximum principal stresses and shear strains were observed in the posterior side of the lateral tibial and femoral cartilage. For Patient 2, high values of maximum principal stresses and shear strains of cartilage were observed in the posterior side of the medial joint compartment. For both patients, increased T₂ and T_1ρ values between the follow-up times were observed in the same areas.

INTERPRETATION

Finite element models with patient-specific geometries and motions and relatively simple material models of tissues were able to identify areas susceptible to post-traumatic knee osteoarthritis. We suggest that the methodology presented here may be applied in large cohort studies.

Medial knee cartilage is unlikely to withstand a lifetime of running without positive adaptation: a theoretical biomechanical model of failure phenomena

Runners on average do not have a high risk of developing knee osteoarthritis, even though running places very high loads on the knee joint. Here we used gait analysis, musculoskeletal modeling, and a discrete-element model of knee contact mechanics to estimate strains of the medial knee cartilage in walking and running in 22 young adults (age 23 ± 3 years). A phenomenological model of cartilage damage, repair, and adaptation in response to these strains then estimated the failure probability of the medial knee cartilage over an adult lifespan (age 23-83 years) for 6 km/day of walking vs. walking and running 3 km/day each. With no running, by age 55 the cumulative probability of medial knee cartilage failure averaged 36% without repair and 13% with repair, similar to reports on incidence of knee osteoarthritis in non-obese adults with no knee injuries, but the probability for running was very high without repair or adaptation (98%) and remained high after including repair (95%). Adaptation of the cartilage compressive modulus, cartilage thickness, and the tibiofemoral bone congruence in response to running (+1.15 standard deviations of their baseline values) was necessary for the failure probability of walking and running 3 km/day each to equal the failure probability of walking 6 km/day. The model results suggest two conclusions for further testing: (i) unlike previous findings on the load per unit distance, damage per unit distance on the medial knee cartilage is greater in running vs. walking, refuting the "cumulative load" hypothesis for long-term joint health; (ii) medial knee cartilage is unlikely to withstand a lifetime of mechanical loading from running without a natural adaptation process, supporting the "cartilage conditioning" hypothesis for long-term joint health.

Single-leg forward hopping exposures adversely affect knee joint health among persons with unilateral lower limb loss: A predictive model

Single-leg hopping is an atypical, yet convenient, method of ambulation for individuals who have sustained unilateral lower limb-loss. Hopping is generally discouraged by therapists but many patients report hopping, and the potential deleterious effects of frequent hopping on knee joint health remains unclear. Mechanical fatigue due to repeated exposures to increased or abnormal loading on the intact limb is thought to be a primary contributor to the high prevalence of knee osteoarthritis among individuals with unilateral lower limb amputation. We aimed to compare knee joint mechanics between single-leg hopping and walking at self-selected paces among individuals with unilateral lower limb-loss, and estimated the associated probability of knee cartilage failure. Thirty-two males with traumatic unilateral lower limb-loss (22 transtibial, 10 transfemoral) hopped and walked at a self-selected pace along a 15-m walkway. Peak knee moments were input to a phenomenological model of cartilage fatigue to estimate the damage and long-term failure probability of the medial knee cartilage when hopping vs. walking. We estimate that each hop accumulates as much damage as at least 8 strides of walking (p < 0.001), and each meter of hopping accumulates as much damage as at least 12 m of walking (p < 0.001). The 30-year failure probability of the medial knee cartilage exceeded a "coin-flip" chance (50%) when performing more than 197 hops per day. Although a convenient mode of ambulation for persons with unilateral lower limb-loss, to mitigate risk for knee osteoarthritis it is advisable to minimize exposure to single-leg forward hopping.

Renal oxygenation: From data to insight

Computational models have made a major contribution to the field of physiology. As the complexity of our understanding of biological systems expands, the need for computational methods only increases. But collaboration between experimental physiologists and computational modellers (ie theoretical physiologists) is not easy. One of the major challenges is to break down the barriers created by differences in vocabulary and approach between the two disciplines. In this review, we have two major aims. Firstly, we wish to contribute to the effort to break down these barriers and so encourage more interdisciplinary collaboration. So, we begin with a "primer" on the ways in which computational models can help us understand physiology and pathophysiology. Second, we aim to provide an update of recent efforts in one specific area of physiology, renal oxygenation. This work is shedding new light on the causes and consequences of renal hypoxia. But as importantly, computational modelling is providing direction for experimental physiologists working in the field of renal oxygenation by: (a) generating new hypotheses that can be tested in experimental studies, (b) allowing experiments that are technically unfeasible to be simulated in silico, or variables that cannot be measured experimentally to be estimated, and (c) providing a means by which the quality of experimental data can be assessed. Critically, based on our experience, we strongly believe that experimental and theoretical physiology should not be seen as separate exercises. Rather, they should be integrated to permit an iterative process between modelling and experimentation.

Establishing outcome measures in early knee osteoarthritis

The classification and monitoring of individuals with early knee osteoarthritis (OA) are important considerations for the design and evaluation of therapeutic interventions and require the identification of appropriate outcome measures. Potential outcome domains to assess for early OA include patient-reported outcomes (such as pain, function and quality of life), features of clinical examination (such as joint line tenderness and crepitus), objective measures of physical function, levels of physical activity, features of imaging modalities (such as of magnetic resonance imaging) and biochemical markers in body fluid. Patient characteristics such as adiposity and biomechanics of the knee could also have relevance to the assessment of early OA. Importantly, research is needed to enable the selection of outcome measures that are feasible, reliable and validated in individuals at risk of knee OA or with early knee OA. In this Perspectives article, potential outcome measures for early symptomatic knee OA are discussed, including those measures that could be of use in clinical practice and/or the research setting.

Clinical characteristics and disability in patients with knee osteoarthritis: real world experience from Bulgaria

Objectives

Although knee osteoarthritis (KOA) is a leading cause of impaired functioning among older adults globally, little is still known about the complex mechanisms of disability accumulation in these patients. The aim of the study was to analyze the clinical parameters of patients with KOA in a Bulgarian population and to determine which of these clinical characteristics define disability to the greatest extent.

Material and methods

Patients aged 40–80 years with symptomatic KOA were included. The assessment tools for pain, clinical disease severity, and disability were the pain visual analogue scale (VAS) and disease-specific questionnaires: Algofunctional Index of Lequesne, Western Ontario and McMaster Universities OA Index (WOMAC), and the Health Assessment Questionnaire-Disability Index (HAQ-DI), respectively. Radiographs of the knees were obtained and graded according to the Kellgren-Lawrence (KL) system.

Results

One hundred and thirty-two patients (81% women) participated in the study. The median values of VAS (mm), WOMAC, Lequesne, and HAQ-DI scores were 52, 37.5, 11, 0.88, respectively. Men had milder disease, resulting in lower VAS, WOMAC, Lequesne, and HAQ-DI scores and less structural damage compared to women (p < 0.05). WOMAC index correlated positively with age of the patients but not with duration of the complaints. Patients with severe and very severe pain did not differ in their HAQ-DI, disease severity and KL grading. WOMAC physical function score and Lequesne index were independent predictors for the HAQ-DI in patients with KOA.

Conclusions

Bulgarian patients with KOA had moderate disability which showed a strong relationship with physical function of WOMAC and disease severity. Multiple layers of causality coexist to determine the knee pain in Bulgarian patients with KOA.

Maximum shear strain-based algorithm can predict proteoglycan loss in damaged articular cartilage

Post-traumatic osteoarthritis (PTOA) is a common disease, where the mechanical integrity of articular cartilage is compromised. PTOA can be a result of chondral defects formed due to injurious loading. One of the first changes around defects is proteoglycan depletion. Since there are no methods to restore injured cartilage fully back to its healthy state, preventing the onset and progression of the disease is advisable. However, this is problematic if the disease progression cannot be predicted. Thus, we developed an algorithm to predict proteoglycan loss of injured cartilage by decreasing the fixed charge density (FCD) concentration. We tested several mechanisms based on the local strains or stresses in the tissue for the FCD loss. By choosing the degeneration threshold suggested for inducing chondrocyte apoptosis and cartilage matrix damage, the algorithm driven by the maximum shear strain showed the most substantial FCD losses around the lesion. This is consistent with experimental findings in the literature. We also observed that by using coordinate system-independent strain measures and selecting the degeneration threshold in an ad hoc manner, all the resulting FCD distributions would appear qualitatively similar, i.e., the greatest FCD losses are found at the tissue adjacent to the lesion. The proposed strain-based FCD degeneration algorithm shows a great potential for predicting the progression of PTOA via biomechanical stimuli. This could allow identification of high-risk defects with an increased risk of PTOA progression.

Comparison between kinetic and kinetic-kinematic driven knee joint finite element models

Use of knee joint finite element models for diagnostic purposes is challenging due to their complexity. Therefore, simpler models are needed for studies where a high number of patients need to be analyzed, without compromising the results of the model. In this study, more complex, kinetic (forces and moments) and simpler, kinetic-kinematic (forces and angles) driven finite element models were compared during the stance phase of gait. Patella and tendons were included in the most complex model, while they were absent in the simplest model. The greatest difference between the most complex and simplest models was observed in the internal-external rotation and axial joint reaction force, while all other rotations, translations and joint reaction forces were similar to one another. In terms of cartilage stresses and strains, the simpler models behaved similarly with the more complex models in the lateral joint compartment, while minor differences were observed in the medial compartment at the beginning of the stance phase. We suggest that it is feasible to use kinetic-kinematic driven knee joint models with a simpler geometry in studies with a large cohort size, particularly when analyzing cartilage responses and failures related to potential overloads.

A novel mechanobiological model can predict how physiologically relevant dynamic loading causes proteoglycan loss in mechanically injured articular cartilage

Cartilage provides low-friction properties and plays an essential role in diarthrodial joints. A hydrated ground substance composed mainly of proteoglycans (PGs) and a fibrillar collagen network are the main constituents of cartilage. Unfortunately, traumatic joint loading can destroy this complex structure and produce lesions in tissue, leading later to changes in tissue composition and, ultimately, to post-traumatic osteoarthritis (PTOA). Consequently, the fixed charge density (FCD) of PGs may decrease near the lesion. However, the underlying mechanisms leading to these tissue changes are unknown. Here, knee cartilage disks from bovine calves were injuriously compressed, followed by a physiologically relevant dynamic compression for twelve days. FCD content at different follow-up time points was assessed using digital densitometry. A novel cartilage degeneration model was developed by implementing deviatoric and maximum shear strain, as well as fluid velocity controlled algorithms to simulate the FCD loss as a function of time. Predicted loss of FCD was quite uniform around the cartilage lesions when the degeneration algorithm was driven by the fluid velocity, while the deviatoric and shear strain driven mechanisms exhibited slightly discontinuous FCD loss around cracks. Our degeneration algorithm predictions fitted well with the FCD content measured from the experiments. The developed model could subsequently be applied for prediction of FCD depletion around different cartilage lesions and for suggesting optimal rehabilitation protocols.

On the biomechanical relationship between applied hip, knee and ankle joint moments and the internal knee compressive forces

Mechanical devices are common treating methods for knee osteoarthritis. It has the purpose of reducing the internal joint forces and unloading the damaged structure. The reduction is often achieved by alterations in the frontal plan, shifting the contact force from one compartment to the other, leaving the total compressive force unchanged. The aim of this study was to investigate how internal knee joint forces depend on applied external moments during gait. Musculoskeletal models of the gait of 10 healthy subjects were developed in the AnyBody Modelling System and used to simulate applied joint moments about different axes (load cases), each with the magnitude to compensate the net moment about the respective axis by a specified percentage. For each load case, the total, medial and lateral knee compressive force were computed and compared with a baseline case with no external moments applied. Among the investigated moments, hip flexion-extension, knee flexion-extension and ankle plantarflexion-dorsiflexion moment compensations have the most positive impact on the total knee joint compressive force, and combining the 3, each with a 40% compensation of the muscle moments, reduced the first peak by 23.6%, the second by 30.6% and the impulse by 28.6% with respect to no applied moments.

New algorithm for simulation of proteoglycan loss and collagen degeneration in the knee joint: Data from the osteoarthritis initiative

Osteoarthritis is a harmful joint disease but prediction of disease progression is problematic. Currently, there is only one modeling framework which can be applied to predict the progression of knee osteoarthritis but it only considers degenerative changes in the collagen fibril network. Here, we have developed the framework further by considering all of the major tissue changes (proteoglycan content, fluid flow, and collagen fibril network) occurring in osteoarthritis. While excessive levels of tissue stresses controlled degeneration of the collagen fibril network, excessive levels of tissue strains controlled the decrease in proteoglycan content and the increase in permeability. We created four knee joint models with increasing degrees of complexity based on the depth-wise composition. Models were tested for normal and abnormal, physiologically relevant, loading conditions in the knee. Finally, the predicted depth-wise compositional changes from each model were compared against experimentally observed compositional changes in vitro. The model incorporating the typical depth-wise composition of cartilage produced the best match with experimental observations. Consistent with earlier in vitro experiments, this model simulated the greatest proteoglycan depletion in the superficial and middle zones, while the collagen fibril degeneration was located mostly in the superficial zone. The presented algorithm can be used for predicting simultaneous collagen degeneration and proteoglycan loss during the development of knee osteoarthritis. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:1673-1683, 2018.

Collagen Damage Location in Articular Cartilage Differs if Damage is Caused by Excessive Loading Magnitude or Rate

Collagen damage in articular cartilage is considered nearly irreversible and may be an early indication of cartilage degeneration. Surface fibrillation and internal collagen damage may both develop after overloading. This study hypothesizes that damage develops at these different locations, because the distribution of excessive strains varies with loading rate as a consequence of time-dependent cartilage properties. The objective is to explore whether collagen damage could preferentially occur superficially or internally, depending on the magnitude and rate of overloading. Bovine osteochondral plugs were compressed with a 2 mm diameter indenter to 15, 25, 35 and 45 N, and at 5, 60 and 120 mm/min. Surface fibrillation and internal collagen damage were graded by four observers, based on histology and staining of collagen damage. Results show that loading magnitude affects the degree of collagen damage, while loading rate dominates the location of network damage: low rates predominantly damage superficial collagen, while at high rates, internal collagen damage occurs. The proposed explanation for the rate-dependent location is that internal fluid flows govern the time-dependent internal tissue deformation and therewith the location of overstained and damaged areas. This supports the hypothesis that collagen damage development is influenced by the time-dependent material behaviour of cartilage.

Application of a semi-automatic cartilage segmentation method for biomechanical modeling of the knee joint

Manual segmentation of articular cartilage from knee joint 3D magnetic resonance images (MRI) is a time consuming and laborious task. Thus, automatic methods are needed for faster and reproducible segmentations. In the present study, we developed a semi-automatic segmentation method based on radial intensity profiles to generate 3D geometries of knee joint cartilage which were then used in computational biomechanical models of the knee joint. Six healthy volunteers were imaged with a 3T MRI device and their knee cartilages were segmented both manually and semi-automatically. The values of cartilage thicknesses and volumes produced by these two methods were compared. Furthermore, the influences of possible geometrical differences on cartilage stresses and strains in the knee were evaluated with finite element modeling. The semi-automatic segmentation and 3D geometry construction of one knee joint (menisci, femoral and tibial cartilages) was approximately two times faster than with manual segmentation. Differences in cartilage thicknesses, volumes, contact pressures, stresses, and strains between segmentation methods in femoral and tibial cartilage were mostly insignificant (p > 0.05) and random, i.e. there were no systematic differences between the methods. In conclusion, the devised semi-automatic segmentation method is a quick and accurate way to determine cartilage geometries; it may become a valuable tool for biomechanical modeling applications with large patient groups.

Relationships Between Tibiofemoral Contact Forces and Cartilage Morphology at 2 to 3 Years After Single-Bundle Hamstring Anterior Cruciate Ligament Reconstruction and in Healthy Knees

BACKGROUND

Prevention of knee osteoarthritis (OA) following anterior cruciate ligament (ACL) rupture and reconstruction is vital. Risk of postreconstruction knee OA is markedly increased by concurrent meniscal injury. It is unclear whether reconstruction results in normal relationships between tibiofemoral contact forces and cartilage morphology and whether meniscal injury modulates these relationships.

HYPOTHESES

Since patients with isolated reconstructions (ie, without meniscal injury) are at lower risk for knee OA, we predicted that relationships between tibiofemoral contact forces and cartilage morphology would be similar to those of normal, healthy knees 2 to 3 years postreconstruction. In knees with meniscal injuries, these relationships would be similar to those reported in patients with knee OA, reflecting early degenerative changes.

STUDY DESIGN

Cross-sectional study; Level of evidence, 3.

METHODS

Three groups were examined: (1) 62 patients who received single-bundle hamstring reconstruction with an intact, uninjured meniscus (mean age, 29.8 ± 6.4 years; mean weight, 74.9 ± 13.3 kg); (2) 38 patients with similar reconstruction with additional meniscal injury (ie, tear, repair) or partial resection (mean age, 30.6 ± 6.6 years; mean weight, 83.3 ± 14.3 kg); and (3) 30 ligament-normal, healthy individuals (mean age, 28.3 ± 5.2 years; mean weight, 74.9 ± 14.9 kg) serving as controls. All patients underwent magnetic resonance imaging to measure the medial and lateral tibial articular cartilage morphology (volumes and thicknesses). An electromyography-driven neuromusculoskeletal model determined medial and lateral tibiofemoral contact forces during walking. General linear models were used to assess relationships between tibiofemoral contact forces and cartilage morphology.

RESULTS

In control knees, cartilage was thicker compared with that of isolated and meniscal-injured ACL-reconstructed knees, while greater contact forces were related to both greater tibial cartilage volumes (medial: R² = 0.43, β = 0.62, P = .000; lateral: R² = 0.19, β = 0.46, P = .03) and medial thicknesses (R² = 0.24, β = 0.48, P = .01). In the overall group of ACL-reconstructed knees, greater contact forces were related to greater lateral cartilage volumes (R² = 0.08, β = 0.28, P = .01). In ACL-reconstructed knees with lateral meniscal injury, greater lateral contact forces were related to greater lateral cartilage volumes (R² = 0.41, β = 0.64, P = .001) and thicknesses (R² = 0.20, β = 0.46, P = .04).

CONCLUSION

At 2 to 3 years postsurgery, ACL-reconstructed knees had thinner cartilage compared with healthy knees, and there were no positive relationships between medial contact forces and cartilage morphology. In lateral meniscal-injured reconstructed knees, greater contact forces were related to greater lateral cartilage volumes and thicknesses, although it was unclear whether this was an adaptive response or associated with degeneration. Future clinical studies may seek to establish whether cartilage morphology can be modified through rehabilitation programs targeting contact forces directly in addition to the current rehabilitation foci of restoring passive and dynamic knee range of motion, knee strength, and functional performance.

Decreased synovial fluid ghrelin levels are linked with disease severity in primary knee osteoarthritis patients and are increased following laser therapy

BACKGROUND

Ghrelin has been proved to inhibit inflammation and promote cartilage growth. So far, its role in patients with primary knee osteoarthritis has not been investigated.

OBJECTIVE

The current study was performed to explore the serum and synovial ghrelin levels as well as the relationship between ghrelin levels and disease severity in primary knee OA patients.

METHODS

52 primary knee OA patients were recruited in the study. 52 sex and age-matched patients visiting our hospital for regular body check were selected as controls. The serum and synovial fluid ghrelin levels were examined by enzyme linked immunosorbent assay (ELISA) before treatment, one week and four weeks after laser therapy, respectively. The inflammation markers IL-6 and TNF-α were also investigated. The radiographic progression was assessed by Kellgren-Lawrence (K-L) grade scale and the symptomatic severity was evaluated by visual analog scale (VAS), Lequesne index and Lysholm scores. The Receiver Operating Characteristic (ROC) analysis curve was conducted to test the diagnostic value of ghrelin, IL-6 and TNF-α for radiographic progression.

RESULTS

No significant difference of serum ghrelin levels was found between knee OA patients and healthy controls. Synovial fluid ghrelin concentrations were significantly negatively correlated with K-L grading (r=-0.591, P<0.001).Attenuated synovial fluid ghrelin levels were also related to clinical severity determined by Lequesne index (r=-0.308, P=0.025),VAS scores (r=-0.591, P<0.001) and Lysholm scores (r=0.381, P=0.005).In addition, ghrelin levels were also negatively associated with TNF-α (r=-0.424, P=0.002) and IL-6 concentrations (r=-0.428, P=0.002). ROC curve analysis demonstrated that ghrelin exhibited more diagnostic value than IL-6 and TNF-α for assessing radiographic progression in medium-late stage.

CONCLUSIONS

Decreased synovial fluid ghrelin levels are related to disease severity in patients with primary osteoarthritis and are increased following laser therapy. Local application of ghrelin may serve as an adjunctive therapy for knee OA.

Hip joint mechanics during walking in individuals with mild-to-moderate hip osteoarthritis

The purpose of this case-control study was to characterise hip joint kinematics and moments during gait in people with mild-to-moderate hip osteoarthritis (OA). Eligible participants were allocated to the hip OA group (n=27) or the age-matched control group (n=26) based on radiographic and symptomatically defined inclusion criteria. Participants walked barefoot along a 10-m walkway at their self-selected gait speed. Trajectories of 43 markers attached to the trunk, pelvis, upper and lower limbs were recorded using a 12-camera motion capture system. Ground reaction force data were simultaneously collected. Individuals in the hip OA group had a 10% higher body mass, 13% slower self-selected walking speed, 10% shorter step length, 2% and 9% longer relative stance and double support duration (% stride) respectively, 41% lower sagittal plane hip range of motion, and 28% and 45% lower peak sagittal and transverse plane hip joint moments respectively during gait compared to controls (p<0.05). The finding that individuals with mild-to-moderate hip OA experienced less net hip joint loading over a reduced range of hip motion for a longer proportion of the gait cycle when walking at their preferred gait speed suggest that the mechanics of the hip joint are altered in hip OA, and could have implications for disease progression through altered mechano-biological processes within the joint.

Osteoarthritis year in review 2016: mechanics

Inappropriate biomechanics, namely wear-and-tear, has been long believed to be a main cause of osteoarthritis (OA). However, this view is now being re-evaluated, especially when examined alongside mechanobiology and new biomechanical studies. These are multiscale experimental and computational studies focussing on cell- and tissue-level mechanobiology through to organ- and whole-body-level biomechanics, which focuses on the biomechanical and biochemical environment of the joint tissues. This review examined papers from April 2015 to April 2016, with a focus on multiscale experimental and computational biomechanical studies of OA. Assessing the onset or progression of OA at organ- and whole-body-levels, gait analysis, medical imaging and neuromusculoskeletal modelling revealed the extent to which tissue damage changes the view of inappropriate biomechanics. Traditional gait analyses studies reported that conservative treatments can alter joint biomechanics, thereby improving pain and function experienced by those with OA. Results of animal models of OA were consistent with these human studies, showing interactions among bone, cartilage and meniscus biomechanics and the onset and/or progression OA. Going down size scales, experimental and computational studies probed the nanosize biomechanics of molecules, cells and extracellular matrix, and demonstrated how the interactions between biomechanics and morphology affect cartilage dynamic poroelastic behaviour and pathways to OA. Finally, integration of multiscale experimental data and computational models were proposed to predict cartilage extracellular matrix remodelling and the development of OA. Summarising, experimental and computational methods provided a nuanced biomechanical understanding of the sub-cellular, cellular, tissue, organ and whole-body mechanisms involved in OA.