Recent insights suggest that the osteochondral interface plays a central role in maintaining healthy articulating joints. Uncovering the underlying transport mechanisms is key to the understanding of the cross-talk between articular cartilage and subchondral bone. Here, we describe the mechanisms that facilitate transport at the osteochondral interface. Using scanning electron microscopy (SEM), we found a continuous transition of mineralization architecture from the non-calcified cartilage towards the calcified cartilage. This refurbishes the classical picture of the so-called tidemark; a well-defined discontinuity at the osteochondral interface. Using focused-ion-beam SEM (FIB-SEM) on one osteochondral plug derived from a human cadaveric knee, we elucidated that the pore structure gradually varies from the calcified cartilage towards the subchondral bone plate. We identified nano-pores with radius of 10.71 ± 6.45 nm in calcified cartilage to 39.1 ± 26.17 nm in the subchondral bone plate. The extracted pore sizes were used to construct 3D pore-scale numerical models to explore the effect of pore sizes and connectivity among different pores. Results indicated that connectivity of nano-pores in calcified cartilage is highly compromised compared to the subchondral bone plate. Flow simulations showed a permeability decrease by about 2000-fold and solute transport simulations using a tracer (iodixanol, 1.5 kDa with a free diffusivity of 2.5 × 10⁻¹⁰ m²/s) showed diffusivity decrease by a factor of 1.5. Taken together, architecture of the nano-pores and the complex mineralization pattern in the osteochondral interface considerably impacts the cross-talk between cartilage and bone.

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AIMS: The aetiologies of common degenerative spine, hip, and knee pathologies are still not completely understood. Mechanical theories have suggested that those diseases are related to sagittal pelvic morphology and spinopelvic-femoral dynamics. The link between the most widely used parameter for sagittal pelvic morphology, pelvic incidence (PI), and the onset of degenerative lumbar, hip, and knee pathologies has not been studied in a large-scale setting. METHODS: A total of 421 patients from the Cohort Hip and Cohort Knee (CHECK) database, a population-based observational cohort, with hip and knee complaints < 6 months, aged between 45 and 65 years old, and with lateral lumbar, hip, and knee radiographs available, were included. Sagittal spinopelvic parameters and pathologies (spondylolisthesis and degenerative disc disease (DDD)) were measured at eight-year follow-up and characteristics of hip and knee osteoarthritis (OA) at baseline and eight-year follow-up. Epidemiology of the degenerative disorders and clinical outcome scores (hip and knee pain and Western Ontario and McMaster Universities Osteoarthritis Index) were compared between low PI (< 50°), normal PI (50° to 60°), and high PI (> 60°) using generalized estimating equations. RESULTS: Demographic details were not different between the different PI groups. L4 to L5 and L5 to S1 spondylolisthesis were more frequently present in subjects with high PI compared to low PI (L4 to L5, OR 3.717; p = 0.024 vs L5 to S1 OR 7.751; p = 0.001). L5 to S1 DDD occurred more in patients with low PI compared to high PI (OR 1.889; p = 0.010), whereas there were no differences in L4 to L5 DDD among individuals with a different PI. The incidence of hip OA was higher in participants with low PI compared to normal (OR 1.262; p = 0.414) or high PI (OR 1.337; p = 0.274), but not statistically different. The incidence of knee OA was higher in individuals with a high PI compared to low PI (OR 1.620; p = 0.034). CONCLUSION: High PI is a risk factor for development of spondylolisthesis and knee OA. Low pelvic incidence is related to DDD, and may be linked to OA of the hip. Level of Evidence: 1b Cite this article: Bone Joint J 2020;102-B(9):1261-1267.

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Background and purpose — Being able to predict the hip–knee–ankle angle (HKAA) from standard knee radiographs allows studies on malalignment in cohorts lacking full-limb radiography. We aimed to develop an automated image analysis pipeline to measure the femoro-tibial angle (FTA) from standard knee radiographs and test various FTA definitions to predict the HKAA. Patients and methods — We included 110 pairs of standard knee and full-limb radiographs. Automatic search algorithms found anatomic landmarks on standard knee radiographs. Based on these landmarks, the FTA was automatically calculated according to 9 different definitions (6 described in the literature and 3 newly developed). Pearson and intra-class correlation coefficient [ICC]) were determined between the FTA and HKAA as measured on full-limb radiographs. Subsequently, the top 4 FTA definitions were used to predict the HKAA in a 5-fold cross-validation setting. Results — Across all pairs of images, the Pearson correlations between FTA and HKAA ranged between 0.83 and 0.90. The ICC values from 0.83 to 0.90. In the cross-validation experiments to predict the HKAA, these values decreased only minimally. The mean absolute error for the best method to predict the HKAA from standard knee radiographs was 1.8° (SD 1.3). Interpretation — We showed that the HKAA can be automatically predicted from standard knee radiographs with fair accuracy and high correlation compared with the true HKAA. Therefore, this method enables research of the relationship between malalignment and knee pathology in large (epidemiological) studies lacking full-limb radiography.

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The bones forming the talocrural joint (TCJ) and subtalar joint (STJ) are often assumed to be bilaterally symmetric. Therefore, the contralateral limb (i.e. the fibula, tibia, calcaneus and talus) is used as a template or an intra-subject control in clinical and research practice. However, the validity of the symmetry assumption is controversial, because insufficient information is available on the shape variations and bilateral (a)symmetry of the fibula, tibia, calcaneus and talus. Using three-dimensional spatially dense sampled representations of bone shapes extracted from bilateral computed tomography scans of 66 individuals (55 male, mean age: 61 ± 10 years; 11 female, mean age: 53 ± 15 years), we analyzed whether: (i) similar shape patterns exist in the left and right bones of the same type; (ii) gender has an effect on bone shape variations; (iii) intra-subject shape variation is smaller than that of inter-subject for a given shape variance direction. For the first set of analyses, all left and right instances of the same type of bone were considered as two separate groups, and statistically compared with each other on multiple aspects including group location (central tendency), variance-covariance scale (dispersion) and orientation (covariance structure) using distance-based permutational tests. For the second and third sets of analyses, all left and right bones of the same type were pooled into one group, and shape variations in the TCJ and STJ bones were extracted using principal component analysis. The effects of gender on age-adjusted bone shape differences were assessed using an analysis of covariance. Moreover, intra-class correlation was employed to evaluate intra- and inter-subject bone shape variations. For each bone type, both sides had similar shape patterns (P_{permutational}-values > 0.05). After Bonferroni adjustment, gender led to shape differences, which were mainly in the lateral and medial condyles of the tibia (P = 0.003), the length and height of the calcaneus (P < 0.001), the posterior and anterior talar articular surfaces of the calcaneus (P = 0.001), and in the posterior aspect of the talus (P = 0.001). Intra-subject shape variations in the tibial tuberosity together with the diameter of the tibia, and the curvature of the fibula shaft and the diameter of the fibula were as high as those of inter-subject. This result suggests that the shape symmetry assumption could be violated for some specific shape variations in the fibula and tibia.

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Objective: To assess the ability of radiography-based bone texture variables in proximal femur and acetabulum to predict incident radiographic hip osteoarthritis (rHOA) over a 10 years period. Design: Pelvic radiographs from CHECK at baseline (987 hips) were analyzed for bone texture using fractal signature analysis (FSA) in proximal femur and acetabulum. Elastic net (machine learning) was used to predict the incidence of rHOA (including Kellgren–Lawrence grade (KL) ≥ 2 or total hip replacement (THR)), joint space narrowing score (JSN, range 0–3), and osteophyte score (OST, range 0–3) after 10 years. Performance of prediction models was assessed using the area under the receiver operating characteristic curve (ROC AUC). Results: Of the 987 hips without rHOA at baseline, 435 (44%) had rHOA at 10-year follow-up. Of the 667 hips with JSN grade 0 at baseline, 471 (71%) had JSN grade ≥ 1 at 10-year follow-up. Of the 613 hips with OST grade 0 at baseline, 526 (86%) had OST grade ≥ 1 at 10-year follow-up. AUCs for the models including age, gender, and body mass index (BMI) to predict incident rHOA, JSN, and OST were 0.59, 0.54, and 0.51, respectively. The inclusion of bone texture variables in the models improved the prediction of incident rHOA (ROC AUC 0.68 and 0.71 when baseline KL was also included in the model) and JSN (ROC AUC 0.62), but not incident OST (ROC AUC 0.52). Conclusion: Bone texture analysis provides additional information for predicting incident rHOA or THR over 10 years.

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Objective: Aging can cause an increase in the stiffness of hyaline cartilage as a consequence of increased protein crosslinks. By induction of crosslinking, a reduction in the diffusion of solutions into the hyaline cartilage has been observed. However, there is a lack of knowledge about the effects of aging on the biophysical and biochemical properties of the temporomandibular joint (TMJ) cartilage. Hence, the aim of this study was to examine the biophysical properties (thickness, stiffness, and diffusion) of the TMJ condylar cartilage of horses of different ages and their correlation with biochemical parameters. Materials and methods: We measured the compressive stiffness of the condyles, after which the diffusion of two contrast agents into cartilage was measured using Contrast Enhanced Computed Tomography technique. Furthermore, the content of water, collagen, GAG, and pentosidine was analyzed. Results: Contrary to our expectations, the stiffness of the cartilage did not change with age (modulus remained around 0.7 MPa). The diffusion of the negatively charged contrast agent (Hexabrix) also did not alter. However, the diffusion of the uncharged contrast agent (Visipaque) decreased with aging. The flux was negatively correlated with the amount of collagen and crosslink level which increased with aging. Pentosidine, collagen, and GAG were positively correlated with age whereas thickness and water content showed negative correlations. Conclusion: Our data demonstrated that aging was not necessarily reflected in the biophysical properties of TMJ condylar cartilage. The combination of the changes happening due to aging resulted in different diffusive properties, depending on the nature of the solution.

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As articular cartilage is an avascular tissue, the transport of nutrients and cytokines through the tissue is essential for the health of cells, i.e. chondrocytes. Transport of specific contrast agents through cartilage has been investigated to elucidate cartilage quality. In laboratory, pre-clinical and clinical studies, imaging techniques such as magnetic imaging resonance (MRI), computed tomography (CT) and fluorescent microscopy have been widely employed to visualize and quantify solute transport in cartilage. Many parameters related to the physico-chemical properties of the solute, such as molecular weight, net charge and chemical structure, have a profound effect on the transport characteristics. Information on the interplay of the solute parameters with the imaging-dependent parameters (e.g. resolution, scan and acquisition time) could assist in selecting the most optimal imaging systems and data analysis tools in a specific experimental set up. Here, we provide a comprehensive review of various imaging systems to investigate solute transport properties in articular cartilage, by discussing their potentials and limitations. The presented information can serve as a guideline for applications in cartilage imaging and therapeutics delivery and to improve understanding of the set-up of solute transport experiments in articular cartilage.

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An important aspect in cartilage ageing is accumulation of advanced glycation end products (AGEs) after exposure to sugars. Advanced glycation results in cross-links formation between the collagen fibrils in articular cartilage, hampering their flexibility and making cartilage more brittle. In the current study, we investigate whether collagen cross-linking after exposure to sugars depends on the stretching condition of the collagen fibrils. Healthy equine cartilage specimens were exposed to l-threose sugar and placed in hypo-, iso-, or hyper-osmolal conditions that expanded or shrank the tissue and changed the 3D conformation of collagen fibrils. We applied micro-indentation tests, contrast enhanced micro-computed tomography, biochemical measurement of pentosidine cross-links, and cartilage surface color analysis to assess the effects of advanced glycation cross-linking under these different conditions. Swelling of extracellular matrix due to hypo-osmolality made cartilage less susceptible to advanced glycation, namely, the increase in effective Young's modulus was approximately 80% lower in hypo-osmolality compared to hyper-osmolality and pentosidine content per collagen was 47% lower. These results indicate that healthy levels of glycosaminoglycans not only keep cartilage stiffness at appropriate levels by swelling and pre-stressed collagen fibrils, but also protect collagen fibrils from adverse effects of advanced glycation. These findings highlight the fact that collagen fibrils and therefore cartilage can be protected from further advanced glycation ("ageing") by maintaining the joint environment at sufficiently low osmolality. Understanding of mechanochemistry of collagen fibrils provided here might evoke potential ageing prohibiting strategies against cartilage deterioration.

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We propose a protocol to investigate the transport of charged and uncharged molecules across articular cartilage with the aid of recently developed experimental and numerical methods. @en

Cross-talk of subchondral bone and articular cartilage could be an important aspect in the etiology of osteoarthritis. Previous research has provided some evidence of transport of small molecules (~370 Da) through the calcified cartilage and subchondral bone plate in murine osteoarthritis models. The current study, for the first time, uses a neutral diffusing computed tomography (CT) contrast agent (iodixanol, ~1550 Da) to study the permeability of the osteochondral interface in equine and human samples. Sequential CT monitoring of diffusion after injecting a finite amount of contrast agent solution onto the cartilage surface using a micro-CT showed penetration of the contrast molecules across the cartilage-bone interface. Moreover, diffusion through the cartilage-bone interface was affected by thickness and porosity of the subchondral bone as well as the cartilage thickness in both human and equine samples. Our results revealed that porosity of the subchondral plate contributed more strongly to the diffusion across osteochondral interface compared to other morphological parameters in healthy equine samples. However, thickness of the subchondral plate contributed more strongly to the diffusion in slightly osteoarthritic human samples.@en

Transport of solutes helps to regulate normal physiology and proper function of cartilage in diarthrodial joints. Multiple studies have shown the effects of characteristic parameters such as concentration of proteoglycans and collagens and the orientation of collagen fibrils on the diffusion process. However, not much quantitative information and accurate models are available to help understand how the characteristics of the fluid surrounding articular cartilage influence the diffusion process. In this study, we used a combination of micro-computed tomography experiments and biphasic-solute finite element models to study the effects of three parameters of the overlying bath on the diffusion of neutral solutes across cartilage zones. Those parameters include bath size, degree of stirring of the bath, and the size and concentration of the stagnant layer that forms at the interface of cartilage and bath. Parametric studies determined the minimum of the finite bath size for which the diffusion behavior reduces to that of an infinite bath. Stirring of the bath proved to remarkably influence neutral solute transport across cartilage zones. The well-stirred condition was achieved only when the ratio of the diffusivity of bath to that of cartilage was greater than ≈1000. While the thickness of the stagnant layer at the cartilage-bath interface did not significantly influence the diffusion behavior, increase in its concentration substantially elevated solute concentration in cartilage. Sufficient stirring attenuated the effects of the stagnant layer. Our findings could be used for efficient design of experimental protocols aimed at understanding the transport of molecules across articular cartilage.

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Recent advances in the realm of computational modeling of complex multiphysics phenomena in articular cartilage enabled efficient and precise determination of articular cartilage properties. However, still accurate quantification of complicated indentation and diffusion processes tying closely with the inhomogeneity of articular cartilage remains challenging. In the present thesis accurate approaches are proposed to capture the mechanical and physical behavior of articular cartilage as faithfully as possible. Finite element models (FE-models) capable of detecting contact between indenter and cartilage surface are developed and applied to spherical indentation process. To predict mechanical and physical properties of cartilage artificial neural networks (ANN) were used and to guarantee the efficacy of the generated ANN they were trained using simulated noisy force-time data. The combination of FE-model and ANN trained with noisy data allowed obtaining cartilage properties robustly. FE-models taking the inhomogeneity of articular cartilage into account were developed and validated and applied to capture neutral (biphasicsolute model) and charged (multiphasic model) solute transfer across articular cartilage in a finite bath experimental setup. Those models could capture the behavior of solute diffusion across cartilage and provide diffusivities and fixed charge densities (FCD) of different cartilage zones. An algorithm consisting of inverse and forward ANNs was developed to obtain the diffusivities of cartilage layers which eliminates the need for computational expertise. The final goal of this algorithm is to introduce a methodology by which properties of cartilage can be determined without any need for computational expertise, which provides a promising opportunity to meet the needs for clinics when it comes to assess the healthiness of articular cartilage during osteoarthritis progression. Effects of bath osmolarity, concentration and charge of solute were investigated using a combination of micro-CT experiments and FE-models. The results suggested that solute charge unlike the osmoalrity and solute concentration had a profound effect on solute diffusion. Porosity and thickness of subchondral plate were identified as two primary factors affecting the diffusion of neutral solutes across subchondral plate. Using a developed multi-zone biphasic-solute model allowed obtaining the diffusivities of cartilage layers as well as subchondral plate. Using a multi-zone biphasic-solute model, we found that overlying bath size, bath stirring and thickness of the formed stagnant layer can substantially influence the diffusion across cartilage. This provides an opportunity to optimally design diffusion experiments.@en

Analytical and numerical methods have been used to extract essential engineering parameters such as elastic modulus, Poisson's ratio, permeability and diffusion coefficient from experimental data in various types of biological tissues. The major limitation associated with analytical techniques is that they are often only applicable to problems with simplified assumptions. Numerical multi-physics methods, on the other hand, enable minimizing the simplified assumptions but require substantial computational expertise, which is not always available. In this paper, we propose a novel approach that combines
inverse and forward artificial neural networks (ANNs) which enables fast and accurate estimation of the diffusion coefficient of cartilage without any need for computational modeling. In this approach, an inverse ANN is trained using our multi-zone biphasic-solute finite-bath computational model of diffusion
in cartilage to estimate the diffusion coefficient of the various zones of cartilage given the concentrationtime curves. Robust estimation of the diffusion coefficients, however, requires introducing certain levels of stochastic variations during the training process. Determining the required level of stochastic variation is performed by coupling the inverse ANN with a forward ANN that receives the diffusion coefficient as input and returns the concentration-time curve as output. Combined together, forward-inverse ANNs enable computationally inexperienced users to obtain accurate and fast estimation of the diffusion coefficients of cartilage zones. The diffusion coefficients estimated using the proposed approach are compared with those determined using direct scanning of the parameter space as the optimization approach. It has been shown that both approaches yield comparable results.@en

Charged and uncharged solutes penetrate through cartilage to maintain the metabolic function of chondrocytes and to possibly restore or further breakdown the cartilage tissue in different stages of osteoarthritis. In this study the transport of charged solutes across the various zones of cartilage was quantified, taken into account the physicochemical interactions between the solute and the cartilage constituents. A multiphasic finite-bath finite element (FE) model was developed to simulate equine cartilage diffusion experiments that used a negatively charged contrast agent (ioxaglate) in combination with serial micro-computed tomography (micro-CT) to measure the diffusion. By comparing the FE model with the experimental data both the diffusion coefficient of ioxaglate and the fixed charge density (FCD) were obtained. In the multiphasic model, cartilage was divided into multiple (three) zones to help understand how diffusion coefficient and FCD vary across cartilage thickness. The direct effects of charged solute-FCD interaction on diffusion were investigated by comparing the diffusion coefficients derived from the multiphasic and biphasic-solute models. We found a relationship between the FCD obtained by the multiphasic model and ioxaglate partitioning obtained from micro-CT experiments. Using our multi-zone multiphasic model, diffusion coefficient of the superficial zone was up to ten-fold higher than that of the middle zone, while the FCD of the middle zone was up to almost two-fold higher than that of the superficial zone. In conclusion, the developed finite-bath multiphasic model provides us with a non-destructive method by which we could obtain both diffusion coefficient and FCD of different cartilage zones. The outcomes of the current work will also help understand how charge of the bath affects the diffusion of a charged molecule and also predict the diffusion behavior of a charged solute across articular cartilage.@en