Cohort profile: Worldwide Collaboration on OsteoArthritis prediCtion for the Hip (World COACH) - an international consortium of prospective cohort studies with individual participant data on hip osteoarthritis.

PURPOSE: Hip osteoarthritis (OA) is a major cause of pain and disability worldwide. Lack of effective therapies may reflect poor knowledge on its aetiology and risk factors, and result in the management of end-stage hip OA with costly joint replacement. The Worldwide Collaboration on OsteoArthritis prediCtion for the Hip (World COACH) consortium was established to pool and harmonise individual participant data from prospective cohort studies. The consortium aims to better understand determinants and risk factors for the development and progression of hip OA, to optimise and automate methods for (imaging) analysis, and to develop a personalised prediction model for hip OA. PARTICIPANTS: World COACH aimed to include participants of prospective cohort studies with ≥200 participants, that have hip imaging data available from at least 2 time points at least 4 years apart. All individual participant data, including clinical data, imaging (data), biochemical markers, questionnaires and genetic data, were collected and pooled into a single, individual-level database. FINDINGS TO DATE: World COACH currently consists of 9 cohorts, with 38 021 participants aged 18-80 years at baseline. Overall, 71% of the participants were women and mean baseline age was 65.3±8.6 years. Over 34 000 participants had baseline pelvic radiographs available, and over 22 000 had an additional pelvic radiograph after 8-12 years of follow-up. Even longer radiographic follow-up (15-25 years) is available for over 6000 of these participants. FUTURE PLANS: The World COACH consortium offers unique opportunities for studies on the relationship between determinants/risk factors and the development or progression of hip OA, by using harmonised data on clinical findings, imaging, biomarkers, genetics and lifestyle. This provides a unique opportunity to develop a personalised hip OA risk prediction model and to optimise methods for imaging analysis of the hip.

MRI-based synthetic CT in the detection of knee osteoarthritis: Comparison with CT.

Magnetic resonance Imaging is the gold standard for assessment of soft tissues; however, X-ray-based techniques are required for evaluating bone-related pathologies. This study evaluated the performance of synthetic computed tomography (sCT), a novel MRI-based bone visualization technique, compared with CT, for the scoring of knee osteoarthritis. sCT images were generated from the 3T T1-weighted gradient-echo MR images using a trained machine learning algorithm. Two readers scored the severity of osteoarthritis in tibiofemoral and patellofemoral joints according to OACT, which enables the evaluation of osteoarthritis, from its characteristics of joint space narrowing, osteophytes, cysts and sclerosis in CT (and sCT) images. Cohen's κ was used to assess the interreader agreement for each modality, and intermodality agreement of CT- and sCT-based scores for each reader. We also compared the confidence level of readers for grading CT and sCT images using confidence scores collected during grading. Inter-reader agreement for tibiofemoral and patellofemoral joints were almost-perfect for both modalities (κ = 0.83-0.88). The intermodality agreement of osteoarthritis scores between CT and sCT was substantial to almost-perfect for tibiofemoral (κ = 0.63 and 0.84 for the two readers) and patellofemoral joints (κ = 0.78 and 0.81 for the two readers). The analysis of diagnosis confidence scores showed comparable visual quality of the two modalities, where both are showing acceptable confidence levels for scoring OA. In conclusion, in this single-center study, sCT and CT were comparable for the scoring of knee OA.

Statistical shape model of the talus bone morphology: A comparison between impinged and nonimpinged ankles.

Diagnosis of ankle impingement is performed primarily by clinical examination, whereas medical imaging is used for severity staging and treatment guidance. The association of impingement symptoms with regional three-dimensional (3D) bone shape variaties visible in medical images has not been systematically explored, nor do we know the type and magnitude of this relation. In this cross-sectional case-control study, we hypothesized that 3D talus bone shape could be used to quantitatively formulate the discriminating shape variations between ankles with impingement from ankles without impingement, and we aimed to characterize and quantify these variations. We used statistical shape modeling (SSM) methods to determine the most prevalent modes of shape variations that discriminate between the impinged and nonimpinged ankles. Results of the compactness and parallel analysis test on the statistical shape model identify 8 prominent shape modes of variations (MoVs) representing approximately 78% of the total 3D variations in the population of shapes, among which two modes captured discriminating features between impinged and nonimpinged ankles (p value of 0.023 and 0.042). Visual inspection confirms that these two shape modes, capturing abnormalities in the anterior and posterior parts of talus, represent the two main bony risk factors in anterior and posterior ankle impingement. In conclusion, in this research using SSM we have identified shape MoVs that were found to correlate significantly with bony ankle impingement. We also illustrated potential guidance from SSMs for surgical planning.

Unravelling the hip-spine dilemma from the CHECK-cohort: is sagittal pelvic morphology linked to radiographic signs of femoroacetabular impingement?

INTRODUCTION: To date the aetiology of femoroacetabular impingement (FAI) is still not completely understood. There are mechanical theories that suggest symptomatic FAI is linked to sagittal pelvic morphology and spinopelvic-femoral dynamics. The aim of this study is to evaluate the relation of sagittal pelvic morphology and orientation to radiographic signs of FAI. Additionally, we test whether the relation between FAI and spinopelvic parameters differs in osteoarthritic hips. METHODS: From a prospective, observational cohort study, 1002 patients between 45 and 65 years old with a first episode of knee or hip pain were followed for 8 years. All patients who had lateral lumbar radiographs and clinical and radiographic follow-up of the hips were included in the present study. Range of internal rotation of the hip as well as radiographic signs of FAI (alpha and Wiberg angle) and presence of hip osteoarthritis (Kellgren and Lawrence) were systematically measured at baseline. Pelvic incidence (PI), pelvic tilt (PT), sacral slope (SS)) were measured at 8-year follow-up. Associations between PI, PT, SS and FAI parameters were tested using generalised estimating equations. RESULTS: 421 subjects, 842 hips, were included. No significant relations between PI, PT or SS and alpha or Wiberg angle were found. Comparison of hips with and without radiological sign(s) of FAI showed no differences in PI, PT or SS. There was no relation between range of internal rotation of the hip and spinopelvic parameters. CONCLUSION: Sagittal pelvic morphology and orientation are not related to the presence of radiological signs of FAI in this study population.

Effect of resilient architecture in an ancient windmill in the Sistan region on natural ventilation enhancement.

Over centuries different elements have been developed in architectures for ensuring adequate natural ventilation in residential units. This study assesses the different components of an ancient windmill in Sistan, Iran, on the structure's indoor air quality (IAQ) enhancement. Several climatic scenarios have been defined by the wind analysis of Sistan meteorological data and analyzed by CFD. The site measurements confirm the accuracy of the simulation results. In the windmill, two deflectors facing the prevailing wind are the significant elements which, in addition to directing wind toward the entrance, could form vortices near the east and west openings leading to suction ventilation. Alteration of the wind speed and angle from 10 to 15 m/s and 30° to 17° would increase the air change per hour (ACH) by 150% and 110%, respectively. Meanwhile, the ACHs were higher than the ASHRAE desired level (ACH > 0.35).

Efficient cascaded V-net optimization for lower extremity CT segmentation validated using bone morphology assessment.

Semantic segmentation of bone from lower extremity computerized tomography (CT) scans can improve and accelerate the visualization, diagnosis, and surgical planning in orthopaedics. However, the large field of view of these scans makes automatic segmentation using deep learning based methods challenging, slow and graphical processing unit (GPU) memory intensive. We investigated methods to more efficiently represent anatomical context for accurate and fast segmentation and compared these with state-of-the-art methodology. Six lower extremity bones from patients of two different datasets were manually segmented from CT scans, and used to train and optimize a cascaded deep learning approach. We varied the number of resolution levels, receptive fields, patch sizes, and number of V-net blocks. The best performing network used a multi-stage, cascaded V-net approach with 1283 -643 -323 voxel patches as input. The average Dice coefficient over all bones was 0.98 ± 0.01, the mean surface distance was 0.26 ± 0.12 mm and the 95th percentile Hausdorff distance 0.65 ± 0.28 mm. This was a significant improvement over the results of the state-of-the-art nnU-net, with only approximately 1/12th of training time, 1/3th of inference time and 1/4th of GPU memory required. Comparison of the morphometric measurements performed on automatic and manual segmentations showed good correlation (Intraclass Correlation Coefficient [ICC] >0.8) for the alpha angle and excellent correlation (ICC >0.95) for the hip-knee-ankle angle, femoral inclination, femoral version, acetabular version, Lateral Centre-Edge angle, acetabular coverage. The segmentations were generally of sufficient quality for the tested clinical applications and were performed accurately and quickly compared to state-of-the-art methodology from the literature.

Topographic features of nano-pores within the osteochondral interface and their effects on transport properties -a 3D imaging and modeling study.

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.

Unravelling the knee-hip-spine trilemma from the CHECK study.

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.

Predicting the mechanical hip-knee-ankle angle accurately from standard knee radiographs: a cross-validation experiment in 100 patients.

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.

Three-dimensional analysis of shape variations and symmetry of the fibula, tibia, calcaneus and talus.

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 ±â€…10 years; 11 female, mean age: 53 ±â€…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 (Ppermutational -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.

Multi-scale imaging techniques to investigate solute transport across articular cartilage.

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.

Non-enzymatic cross-linking of collagen type II fibrils is tuned via osmolality switch.

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. © 2018 The Authors. Journal of Orthopaedic Research Published by Wiley Periodicals, Inc. on behalf of Orthopaedic Research Society. J Orthop Res 36:1929-1936, 2018.

An Experimental and Finite Element Protocol to Investigate the Transport of Neutral and Charged Solutes across Articular Cartilage.

Osteoarthritis (OA) is a debilitating disease that is associated with degeneration of articular cartilage and subchondral bone. Degeneration of articular cartilage impairs its load-bearing function substantially as it experiences tremendous chemical degradation, i.e. proteoglycan loss and collagen fibril disruption. One promising way to investigate chemical damage mechanisms during OA is to expose the cartilage specimens to an external solute and monitor the diffusion of the molecules. The degree of cartilage damage (i.e. concentration and configuration of essential macromolecules) is associated with collisional energy loss of external solutes while moving across articular cartilage creates different diffusion characteristics compared to healthy cartilage. In this study, we introduce a protocol, which consists of several steps and is based on previously developed experimental micro-Computed Tomography (micro-CT) and finite element modeling. The transport of charged and uncharged iodinated molecules is first recorded using micro-CT, which is followed by applying biphasic-solute and multiphasic finite element models to obtain diffusion coefficients and fixed charge densities across cartilage zones.

Solute transport at the interface of cartilage and subchondral bone plate: Effect of micro-architecture.

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 (~370Da) 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, ~1550Da) 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.

Isolated effects of external bath osmolality, solute concentration, and electrical charge on solute transport across articular cartilage.

The metabolic function of cartilage primarily depends on transport of solutes through diffusion mechanism. In the current study, we use contrast enhanced micro-computed tomography to determine equilibrium concentration of solutes through different cartilage zones and solute flux in the cartilage, using osteochondral plugs from equine femoral condyles. Diffusion experiments were performed with two solutes of different charge and approximately equal molecular weight, namely iodixanol (neutral) and ioxaglate (charge=-1) in order to isolate the effects of solute's charge on diffusion. Furthermore, solute concentrations as well as bath osmolality were changed to isolate the effects of steric hindrance on diffusion. Bath concentration and bath osmolality only had minor effects on the diffusion of the neutral solute through cartilage at the surface, middle and deep zones, indicating that the diffusion of the neutral solute was mainly Fickian. The negatively charged solute diffused considerably slower through cartilage than the neutral solute, indicating a large non-Fickian contribution in the diffusion of charged molecules. The numerical models determined maximum solute flux in the superficial zone up to a factor of 2.5 lower for the negatively charged solutes (charge=-1) as compared to the neutral solutes confirming the importance of charge-matrix interaction in diffusion of molecules across cartilage.

Neutral solute transport across osteochondral interface: A finite element approach.

Investigation of the solute transfer across articular cartilage and subchondral bone plate could nurture the understanding of the mechanisms of osteoarthritis (OA) progression. In the current study, we approached the transport of neutral solutes in human (slight OA) and equine (healthy) samples using both computed tomography and biphasic-solute finite element modeling. We developed a multi-zone biphasic-solute finite element model (FEM) accounting for the inhomogeneity of articular cartilage (superficial, middle and deep zones) and subchondral bone plate. Fitting the FEM model to the concentration-time curves of the cartilage and the equilibrium concentration of the subchondral plate/calcified cartilage enabled determination of the diffusion coefficients in the superficial, middle and deep zones of cartilage and subchondral plate. We found slightly higher diffusion coefficients for all zones in the human samples as compared to the equine samples. Generally the diffusion coefficient in the superficial zone of human samples was about 3-fold higher than the middle zone, the diffusion coefficient of the middle zone was 1.5-fold higher than that of the deep zone, and the diffusion coefficient of the deep zone was 1.5-fold higher than that of the subchondral plate/calcified cartilage. Those ratios for equine samples were 9, 2 and 1.5, respectively. Regardless of the species considered, there is a gradual decrease of the diffusion coefficient as one approaches the subchondral plate, whereas the rate of decrease is dependent on the type of species.

Application of multiphysics models to efficient design of experiments of solute transport across articular cartilage.

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.

Combined inverse-forward artificial neural networks for fast and accurate estimation of the diffusion coefficients of cartilage based on multi-physics models.

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 concentration-time 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.

Multiphasic modeling of charged solute transport across articular cartilage: Application of multi-zone finite-bath model.

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.

Determination of the mechanical and physical properties of cartilage by coupling poroelastic-based finite element models of indentation with artificial neural networks.

One of the most widely used techniques to determine the mechanical properties of cartilage is based on indentation tests and interpretation of the obtained force-time or displacement-time data. In the current computational approaches, one needs to simulate the indentation test with finite element models and use an optimization algorithm to estimate the mechanical properties of cartilage. The modeling procedure is cumbersome, and the simulations need to be repeated for every new experiment. For the first time, we propose a method for fast and accurate estimation of the mechanical and physical properties of cartilage as a poroelastic material with the aid of artificial neural networks. In our study, we used finite element models to simulate the indentation for poroelastic materials with wide combinations of mechanical and physical properties. The obtained force-time curves are then divided into three parts: the first two parts of the data is used for training and validation of an artificial neural network, while the third part is used for testing the trained network. The trained neural network receives the force-time curves as the input and provides the properties of cartilage as the output. We observed that the trained network could accurately predict the properties of cartilage within the range of properties for which it was trained. The mechanical and physical properties of cartilage could therefore be estimated very fast, since no additional finite element modeling is required once the neural network is trained. The robustness of the trained artificial neural network in determining the properties of cartilage based on noisy force-time data was assessed by introducing noise to the simulated force-time data. We found that the training procedure could be optimized so as to maximize the robustness of the neural network against noisy force-time data.