Quantitative Evaluation of the Mechanical Risks Caused by Focal Cartilage Defects in the Knee

Hybrid discrete and finite element analysis enables fast evaluation of hip joint cartilage mechanical response

Finite element analysis (FEA) is the leading numerical technique for studying joint biomechanics related to the onset and progression of osteoarthritis. However, subject-specific FEA of joint mechanics is a time- and compute-intensive process limiting its clinical applicability. We introduce and evaluate a novel hybrid modelling framework combining discrete element analysis (DEA) and FEA for computationally efficient evaluation of cartilage mechanics in the hip joint. In our approach, the hip joint contact mechanics are first estimated using DEA and subsequently used as input for matching FEA models, substantially reducing model complexity. The cartilage mechanical responses obtained using the hybrid DEA-FEA method were evaluated for subject-specific hip joint geometries from five asymptomatic individuals under loading conditions typical to normal walking gait and compared to conventional FEA in terms of peak intra-tissue mechanical stresses and model run-times. The hybrid DEA-FEA method had a median run-time of 3.6 min per subject (64-core processor, 512 GB RAM) and produced minimum principal (compressive) stress estimates comparable to stresses obtained using conventional FEA models with a median run-time of 96.2 min. On average, the peak compressive stresses obtained using the hybrid DEA-FEA approach were 0.06 MPa (95 % confidence interval: -0.86-0.99) lower than the stresses estimated with conventional FEA. Despite up to 1.4 MPa differences at individual gait time-points, the results indicate that the proposed hybrid DEA-FEA method enables estimation of hip cartilage mechanics in a fraction of time compared to conventional FEA, facilitating implementation in large cohort studies and clinical applications.

Computational modelling of articular joints with biphasic cartilage: recent advances, challenges and opportunities

Biphasic models have been widely used to simulate the time-dependent biomechanical response of soft tissues. Modelling techniques of joints with biphasic weight-bearing soft tissues have been markedly improved over the last decade, enhancing our understanding of the function, degenerative mechanism and outcomes of interventions of joints. This paper reviews the recent advances, challenges and opportunities in computational models of joints with biphasic weight-bearing soft tissues. The review begins with an introduction of the function and degeneration of joints from a biomechanical aspect. Different constitutive models of articular cartilage, in particular biphasic materials, are illustrated in the context of the study of contact mechanics in joints. Approaches, advances and major findings of biphasic models of the hip and knee are presented, followed by a discussion of the challenges awaiting to be addressed, including the convergence issue, high computational cost and inadequate validation. Finally, opportunities and clinical insights in the areas of subject-specific modeling and tissue engineering are provided and discussed.

An advanced biphasic porous and injectable scaffold displays a fine balance between mechanical strength and remodeling capabilities essential for cartilage regeneration

An important challenge in tissue engineering is the regeneration of functional articular cartilage (AC). In the field, biomimetic hydrogels are being extensively studied as scaffolds that recapitulate microenvironmental features or as mechanical supports for transplanted cells. New advanced hydrogel formulations based on salmon methacrylate gelatin (sGelMA), a cold-adapted biomaterial, are presented in this work. The psychrophilic nature of this biomaterial provides rheological advantages allowing the fabrication of scaffolds with high concentrations of the biopolymer and high mechanical strength, suitable for formulating injectable hydrogels with high mechanical strength for cartilage regeneration. However, highly intricate cell-laden scaffolds derived from highly concentrated sGelMA solutions could be deleterious for cells and scaffold remodeling. On this account, the current study proposes the use of sGelMA supplemented with a mesophilic sacrificial porogenic component. The cytocompatibility of different sGelMA-based formulations is tested through the encapsulation of osteoarthritic chondrocytes (OACs) and stimulated to synthesize extracellular matrix (ECM) components in vitro and in vivo. The sGelMA-derived scaffolds reach high levels of stiffness, and the inclusion of porogens impacts positively the scaffold degradability and molecular diffusion, improved fitness of OACs, increased the expression of cartilage-related genes, increased glycosaminoglycan (GAG) synthesis, and improved remodeling toward cartilage-like tissues. Altogether, these data support the use of sGelMA solutions in combination with mammalian solid gelatin beads for highly injectable formulations for cartilage regeneration, strengthening the importance of the balance between mechanical properties and remodeling capabilities.

A novel knee joint model in FEBio with inhomogeneous fibril-reinforced biphasic cartilage simulating tissue mechanical responses during gait: data from the osteoarthritis initiative

We developed a novel knee joint model in FEBio to simulate walking. Knee cartilage was modeled using a fibril-reinforced biphasic (FRB) formulation with depth-wise collagen architecture and split-lines to account for cartilage structure. Under axial compression, the knee model with FRB cartilage yielded contact pressures, similar to reported experimental data. Furthermore, gait analysis with FRB cartilage simulated spatial and temporal trends in cartilage fluid pressures, stresses, and strains, comparable to those of a fibril-reinforced poroviscoelastic (FRPVE) material in Abaqus. This knee joint model in FEBio could be used for further studies of knee disorders using physiologically relevant loading.

Computational assessment on the impact of collagen fiber orientation in cartilages on healthy and arthritic knee kinetics/kinematics

BACKGROUND

The inhomogeneous distribution of collagen fiber in cartilage can substantially influence the knee kinematics. This becomes vital for understanding the mechanical response of soft tissues, and cartilage deterioration including osteoarthritis (OA). Though the conventional computational models consider geometrical heterogeneity along with fiber reinforcements in the cartilage model as material heterogeneity, the influence of fiber orientation on knee kinetics and kinematics is not fully explored. This work examines how the collagen fiber orientation in the cartilage affects the healthy (intact knee) and arthritic knee response over multiple gait activities like running and walking.

METHODS

A 3D finite element knee joint model is used to compute the articular cartilage response during the gait cycle. A fiber-reinforced porous hyper elastic (FRPHE) material is used to model the soft tissue. A split-line pattern is used to implement the fiber orientation in femoral and tibial cartilage. Four distinct intact cartilage models and three OA models are simulated to assess the impact of the orientation of collagen fibers in a depth wise direction. The cartilage models with fibers oriented in parallel, perpendicular, and inclined to the articular surface are investigated for multiple knee kinematics and kinetics.

FINDINGS

The comparison of models with fiber orientation parallel to articulating surface for walking and running gait has the highest elastic stress and fluid pressure compared with inclined and perpendicular fiber-oriented models. Also, the maximum contact pressure is observed to be higher in the case of intact models during the walking cycle than for OA models. In contrast, the maximum contact pressure is higher during running in OA models than in intact models. Additionally, parallel-oriented models produce higher maximum stresses and fluid pressure for walking and running gait than proximal-distal-oriented models. Interestingly, during the walking cycle, the maximum contact pressure with intact models is approximately three times higher than on OA models. In contrast, the OA models exhibit higher contact pressure during the running cycle.

INTERPRETATION

Overall, the study indicates that collagen orientation is crucial for tissue responsiveness. This investigation provides insights into the development of tailored implants.

Finite Element Analysis of Different Osseocartilaginous Reconstruction Techniques in Animal Model Knees

Lesions of the articular cartilage are frequent in all age populations and lead to functional impairment. Multiple surgical techniques have failed to provide an effective method for cartilage repair. The aim of our research was to evaluate the effect of two different compression forces on three types of cartilage repair using finite element analysis (FEA). Initially, an in vivo study was performed on sheep. The in vivo study was prepared as following: Case 0-control group, without cartilage lesion; Case 1-cartilage lesion treated with macro-porous collagen implants; Case 2-cartilage lesion treated with collagen implants impregnated with bone marrow concentrate (BMC); Case 3-cartilage lesion treated with collagen implants impregnated with adipose-derived stem cells (ASC). Using the computed tomography (CT) data, virtual femur-cartilage-tibia joints were created for each Case. The study showed better results in bone changes when using porous collagen implants impregnated with BMC or ASC stem cells for the treatment of osseocartilaginous defects compared with untreated macro-porous implant. After 7 months postoperative, the presence of un-resorbed collagen influences the von Mises stress distribution, total deformation, and displacement on the Z axis. The BMC treatment was superior to ASC cells in bone tissue morphology, resembling the biomechanics of the control group in all FEA simulations.

Simulating Knee-Stress Distribution Using a Computed Tomography-Based Finite Element Model: A Case Study

This study aimed to evaluate the mechanism of progression involved in knee osteoarthritis (OA). We used the computed tomography-based finite element method (CT-FEM) of quantitative X-ray CT imaging to calculate and create a model of the load response phase, wherein the greatest burden is placed on the knee joint while walking. Weight gain was simulated by asking a male individual with a normal gait to carry sandbags on both shoulders. We developed a CT-FEM model that incorporated walking characteristics of individuals. Upon simulating changes owing to a weight gain of approximately 20%, the equivalent stress increased extensively in both medial and lower leg aspects of the femur and increased medio-posteriorly by approximately 230%. As the varus angle increased, stress on the surface of the femoral cartilage did not change significantly. However, the equivalent stress on the surface of the subchondral femur was distributed over a wider area, increasing by approximately 170% in the medio-posterior direction. The range of equivalent stress affecting the lower-leg end of the knee joint widened, and stress on the posterior medial side also increased significantly. It was reconfirmed that weight gain and varus enhancement increase knee-joint stress and cause the progression of OA.

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

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

Computed Tomography: State-of-the-Art Advancements in Musculoskeletal Imaging

ABSTRACT

Although musculoskeletal magnetic resonance imaging (MRI) plays a dominant role in characterizing abnormalities, novel computed tomography (CT) techniques have found an emerging niche in several scenarios such as trauma, gout, and the characterization of pathologic biomechanical states during motion and weight-bearing. Recent developments and advancements in the field of musculoskeletal CT include 4-dimensional, cone-beam (CB), and dual-energy (DE) CT. Four-dimensional CT has the potential to quantify biomechanical derangements of peripheral joints in different joint positions to diagnose and characterize patellofemoral instability, scapholunate ligamentous injuries, and syndesmotic injuries. Cone-beam CT provides an opportunity to image peripheral joints during weight-bearing, augmenting the diagnosis and characterization of disease processes. Emerging CBCT technologies improved spatial resolution for osseous microstructures in the quantitative analysis of osteoarthritis-related subchondral bone changes, trauma, and fracture healing. Dual-energy CT-based material decomposition visualizes and quantifies monosodium urate crystals in gout, bone marrow edema in traumatic and nontraumatic fractures, and neoplastic disease. Recently, DE techniques have been applied to CBCT, contributing to increased image quality in contrast-enhanced arthrography, bone densitometry, and bone marrow imaging. This review describes 4-dimensional CT, CBCT, and DECT advances, current logistical limitations, and prospects for each technique.

Multiscale In Silico Modeling of Cartilage Injuries

Injurious loading of the joint can be accompanied by articular cartilage damage and trigger inflammation. However, it is not well-known which mechanism controls further cartilage degradation, ultimately leading to post-traumatic osteoarthritis. For personalized prognostics, there should also be a method that can predict tissue alterations following joint and cartilage injury. This chapter gives an overview of experimental and computational methods to characterize and predict cartilage degradation following joint injury. Two mechanisms for cartilage degradation are proposed. In (1) biomechanically driven cartilage degradation, it is assumed that excessive levels of strain or stress of the fibrillar or non-fibrillar matrix lead to proteoglycan loss or collagen damage and degradation. In (2) biochemically driven cartilage degradation, it is assumed that diffusion of inflammatory cytokines leads to degradation of the extracellular matrix. When implementing these two mechanisms in a computational in silico modeling workflow, supplemented by in vitro and in vivo experiments, it is shown that biomechanically driven cartilage degradation is concentrated on the damage environment, while inflammation via synovial fluid affects all free cartilage surfaces. It is also proposed how the presented in silico modeling methodology may be used in the future for personalized prognostics and treatment planning of patients with a joint injury.

Proteomic, mechanical, and biochemical development of tissue-engineered neocartilage

Background

The self-assembling process of cartilage tissue engineering is a promising technique to heal cartilage defects, preventing osteoarthritic changes. Given that chondrocytes dedifferentiate when expanded, it is not known if cellular expansion affects the development of self-assembled neocartilage. The objective of this study was to use proteomic, mechanical, and biochemical analyses to quantitatively investigate the development of self-assembled neocartilage derived from passaged, rejuvenated costal chondrocytes.

Methods

Yucatan minipig costal chondrocytes were used to create self-assembled neocartilage constructs. After 1, 4, 7, 14, 28, 56, or 84 days of self-assembly, constructs were analyzed through a variety of histological, biomechanical, biochemical, and proteomic techniques.

Results

It was found that temporal trends in neocartilage formation are similar to those seen in native hyaline articular cartilage development. For example, between days 7 and 84 of culture, tensile Young’s modulus increased 4.4-times, total collagen increased 2.7-times, DNA content decreased 69.3%, collagen type II increased 1.5-times, and aggrecan dropped 55.3%, mirroring trends shown in native knee cartilage. Importantly, collagen type X, which is associated with cartilage calcification, remained at low levels (≤ 0.05%) at all neocartilage developmental time points, similar to knee cartilage (< 0.01%) and unlike donor rib cartilage (0.98%).

Conclusions

In this work, bottom-up proteomics, a powerful tool to interrogate tissue composition, was used for the first time to quantify and compare the proteome of a developing engineered tissue to a recipient tissue. Furthermore, it was shown that self-assembled, costal chondrocyte-derived neocartilage is suitable for a non-homologous approach in the knee.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40824-022-00284-4.

Dynamic pressure analysis of novel interpositional knee spacer implants in 3D-printed human knee models

Alternative treatment methods for knee osteoarthritis (OA) are in demand, to delay the young (< 50 Years) patient's need for osteotomy or knee replacement. Novel interpositional knee spacers shape based on statistical shape model (SSM) approach and made of polyurethane (PU) were developed to present a minimally invasive method to treat medial OA in the knee. The implant should be supposed to reduce peak strains and pain, restore the stability of the knee, correct the malalignment of a varus knee and improve joint function and gait. Firstly, the spacers were tested in artificial knee models. It is assumed that by application of a spacer, a significant reduction in stress values and a significant increase in the contact area in the medial compartment of the knee will be registered. Biomechanical analysis of the effect of novel interpositional knee spacer implants on pressure distribution in 3D-printed knee model replicas: the primary purpose was the medial joint contact stress-related biomechanics. A secondary purpose was a better understanding of medial/lateral redistribution of joint loading. Six 3D printed knee models were reproduced from cadaveric leg computed tomography. Each of four spacer implants was tested in each knee geometry under realistic arthrokinematic dynamic loading conditions, to examine the pressure distribution in the knee joint. All spacers showed reduced mean stress values by 84-88% and peak stress values by 524-704% in the medial knee joint compartment compared to the non-spacer test condition. The contact area was enlarged by 462-627% as a result of the inserted spacers. Concerning the appreciable contact stress reduction and enlargement of the contact area in the medial knee joint compartment, the premises are in place for testing the implants directly on human knee cadavers to gain further insights into a possible tool for treating medial knee osteoarthritis.

Research progress of cartilage lubrication and biomimetic cartilage lubrication materials

Human joints move thousands of times a day. The articular cartilage plays a vital role in joints’ protection. If there is dysfunction in cartilage lubrication, cartilage cannot maintain its normal function. Eventually, the dysfunction may bring about osteoarthritis (OA). Extensive researches have shown that fluid film lubrication, boundary lubrication, and hydration lubrication are three discovered lubrication models at cartilage surface, and analyzing and simulating the mechanism of cartilage lubrication are fundamental to the treatment of OA. This essay concludes recent researches on the progress of cartilage lubrication and biomimetic cartilage, revealing the pathophysiology of cartilage lubrication and updating bio-inspired cartilage lubrication applications.

Influence of material heterogeneity on the mechanical response of articulated cartilages in a knee joint

Structurally, the articular cartilages are heterogeneous owing to nonuniform distribution and orientation of its constituents. The oversimplification of this soft tissue as a homogeneous material is generally considered in the simulation domain to estimate contact pressure along with other physical responses. Hence, there is a need for investigating knee cartilages for their actual response to external stimuli. In this article, impact of material and geometrical heterogeneity of the cartilage is resolved using well known material models. The findings are compared with conventional homogeneous models. The results indicate vital differences in contact pressure distribution and tissue deformation. Further, this study paves way for standardizing material models to extract maximum information possible for investigating knee mechanics with variable geometry and case specific parameters.

Shear strain and inflammation-induced fixed charge density loss in the knee joint cartilage following ACL injury and reconstruction: A computational study

Excessive tissue deformation near cartilage lesions and acute inflammation within the knee joint after anterior cruciate ligament (ACL) rupture and reconstruction surgery accelerate the loss of fixed charge density (FCD) and subsequent cartilage tissue degeneration. Here, we show how biomechanical and biochemical degradation pathways can predict FCD loss using a patient-specific finite element model of an ACL reconstructed knee joint exhibiting a chondral lesion. Biomechanical degradation was based on the excessive maximum shear strains that may result in cell apoptosis, while biochemical degradation was driven by the diffusion of pro-inflammatory cytokines. We found that the biomechanical model was able to predict substantial localized FCD loss near the lesion and on the medial areas of the lateral tibial cartilage. In turn, the biochemical model predicted FCD loss all around the lesion and at intact areas; the highest FCD loss was at the cartilage-synovial fluid-interface and decreased toward the deeper zones. Interestingly, simulating a downturn of an acute inflammatory response by reducing the cytokine concentration exponentially over time in synovial fluid led to a partial recovery of FCD content in the cartilage. Our novel numerical approach suggests that in vivo FCD loss can be estimated in injured cartilage following ACL injury and reconstruction. Our novel modeling platform can benefit the prediction of PTOA progression and the development of treatment interventions such as disease-modifying drug testing and rehabilitation strategies.

A musculoskeletal finite element model of rat knee joint for evaluating cartilage biomechanics during gait

Abnormal loading of the knee due to injuries or obesity is thought to contribute to the development of osteoarthritis (OA). Small animal models have been used for studying OA progression mechanisms. However, numerical models to study cartilage responses under dynamic loading in preclinical animal models have not been developed. Here we present a musculoskeletal finite element model of a rat knee joint to evaluate cartilage biomechanical responses during a gait cycle. The rat knee joint geometries were obtained from a 3-D MRI dataset and the boundary conditions regarding loading in the joint were extracted from a musculoskeletal model of the rat hindlimb. The fibril-reinforced poroelastic (FRPE) properties of the rat cartilage were derived from data of mechanical indentation tests. Our numerical results showed the relevance of simulating anatomical and locomotion characteristics in the rat knee joint for estimating tissue responses such as contact pressures, stresses, strains, and fluid pressures. We found that the contact pressure and maximum principal strain were virtually constant in the medial compartment whereas they showed the highest values at the beginning of the gait cycle in the lateral compartment. Furthermore, we found that the maximum principal stress increased during the stance phase of gait, with the greatest values at midstance. We anticipate that our approach serves as a first step towards investigating the effects of gait abnormalities on the adaptation and degeneration of rat knee joint tissues and could be used to evaluate biomechanically-driven mechanisms of the progression of OA as a consequence of joint injury or obesity.

Osteoarthritis is a disease of the musculoskeletal system which is characterized by the degradation of articular cartilage. Changes in the knee loading after injuries or obesity contribute to the development of cartilage degeneration. Since injured cartilage cannot be reversed back to intact conditions, small animal models have been widely used for investigating osteoarthritis progression mechanisms. Moreover, experimental studies have been complemented with numerical models to overcome inherent limitations such as cost, difficulties to obtain accurate measures and replicate degenerative situations in the knee joint. However, computational models to study articular cartilage responses under dynamic loading in small animal models have not been developed. Thus, here we present a musculoskeletal finite element model (MSFE) of a rat knee joint to evaluate cartilage biomechanical responses during gait. Our computational model considers both the anatomical and locomotion characteristics of the rat knee joint for estimating mechanical responses in the articular cartilage. We suggest that our approach can be used to investigate tissue adaptations based on the mechanobiological responses of the cartilage to prevent the progression of osteoarthritis.

Towards Tailored Rehabilitation by Implementation of a Novel Musculoskeletal Finite Element Analysis Pipeline

Tissue-level mechanics (e.g., stress and strain) are important factors governing tissue remodeling and development of knee osteoarthritis (KOA), and hence, the success of physical rehabilitation. To date, no clinically feasible analysis toolbox has been introduced and used to inform clinical decision making with subject-specific in-depth joint mechanics of different activities. Herein, we utilized a rapid state-of-the-art electromyography-assisted musculoskeletal finite element analysis toolbox with fibril-reinforced poro(visco)elastic cartilages and menisci to investigate knee mechanics in different activities. Tissue mechanical responses, believed to govern collagen damage, cell death, and fixed charge density loss of proteoglycans, were characterized within 15 patients with KOA while various daily activities and rehabilitation exercises were performed. Results showed more inter-participant variation in joint mechanics during rehabilitation exercises compared to daily activities. Accordingly, the devised workflow may be used for designing subject-specific rehabilitation protocols. Further, results showed the potential to tailor rehabilitation exercises, or assess capacity for daily activity modifications, to optimally load knee tissue, especially when mechanically-induced cartilage degeneration and adaptation are of interest.

Finite Element Modelling of Planus and Rectus Foot Types for the Study of First Metatarsophalangeal and First Metatarsocuneiform Joint Contact Mechanics

Evaluating the contact mechanics of human joints is an important element in understanding the pathomechanics of orthopaedic diseases. Although physical testing is essential in the evaluation process, reliable computational models can augment these experiments by non-invasive predictions of biomechanical or surgical variables. The objective of this study was to perform verification of a framework for developing a medial forefoot finite element. Verification was conducted by comparing computational predictions to experimental measurements of first metatarsophalangeal and first metatarsocuneiform joint contact mechanics. A custom-built force-controlled cadaveric test-rig was used to derive measurements of contact pressure, force, and area. A quasi-static finite element was developed and driven under the same boundary and loading conditions. Calibration of cartilage moduli and mesh sensitivity analyses were performed. Mean errors in contact pressures, forces, and areas were 24%, 4%, and 40% at the first metatarsophalangeal joint and 23%, 12%, and 19% at the first Metatarsocuneiform joint, respectively. Verification of a medial forefoot finite element model development framework was presented and found to be within 30% for contact pressure and contact force of both joints. This study presents a method to verify and simulate realistic physiological loading to investigate orthopaedic diseases of the medial forefoot.

Finite element analysis of bone remodelling with piezoelectric effects using an open-source framework

Bone tissue exhibits piezoelectric properties and thus is capable of transforming mechanical stress into electrical potential. Piezoelectricity has been shown to play a vital role in bone adaptation and remodelling processes. Therefore, to better understand the interplay between mechanical and electrical stimulation during these processes, strain-adaptive bone remodelling models without and with considering the piezoelectric effect were simulated using the Python-based open-source software framework. To discretise numerical attributes, the finite element method (FEM) was used for the spatial variables and an explicit Euler scheme for the temporal derivatives. The predicted bone apparent density distributions were qualitatively and quantitatively evaluated against the radiographic scan of a human proximal femur and the bone apparent density calculated using a bone mineral density (BMD) calibration phantom, respectively. Additionally, the effect of the initial bone density on the resulting predicted density distribution was investigated globally and locally. The simulation results showed that the electrically stimulated bone surface enhanced bone deposition and these are in good agreement with previous findings from the literature. Moreover, mechanical stimuli due to daily physical activities could be supported by therapeutic electrical stimulation to reduce bone loss in case of physical impairment or osteoporosis. The bone remodelling algorithm implemented using an open-source software framework facilitates easy accessibility and reproducibility of finite element analysis made.

Prediction of local fixed charge density loss in cartilage following ACL injury and reconstruction: A computational proof-of-concept study with MRI follow-up

The purpose of this proof-of-concept study was to develop three-dimensional patient-specific mechanobiological knee joint models to simulate alterations in the fixed charged density (FCD) around cartilage lesions during the stance phase of the walking gait. Two patients with anterior cruciate ligament (ACL) reconstructed knees were imaged at 1 and 3 years after surgery. The magnetic resonance imaging (MRI) data were used for segmenting the knee geometries, including the cartilage lesions. Based on these geometries, finite element (FE) models were developed. The gait of the patients was obtained using a motion capture system. Musculoskeletal modeling was utilized to calculate knee joint contact and lower extremity muscle forces for the FE models. Finally, a cartilage adaptation algorithm was implemented in both FE models. In the algorithm, it was assumed that excessive maximum shear and deviatoric strains (calculated as the combination of principal strains), and fluid velocity, are responsible for the FCD loss. Changes in the longitudinal T_1ρ and T₂ relaxation times were postulated to be related to changes in the cartilage composition and were compared with the numerical predictions. In patient 1 model, both the excessive fluid velocity and strain caused the FCD loss primarily near the cartilage lesion. T_1ρ and T₂ relaxation times increased during the follow-up in the same location. In contrast, in patient 2 model, only the excessive fluid velocity led to a slight FCD loss near the lesion, where MRI parameters did not show evidence of alterations. Significance: This novel proof-of-concept study suggests mechanisms through which a local FCD loss might occur near cartilage lesions. In order to obtain statistical evidence for these findings, the method should be investigated with a larger cohort of subjects.

Stabilization of Damaged Articular Cartilage with Hydrogel-Mediated Reinforcement and Sealing

Cartilage injuries and subsequent tissue deterioration impact millions of patients. Since the regeneration of functional hyaline cartilage remains elusive, methods to stabilize the remaining tissue, and prevent further deterioration, would be of significant clinical utility and prolong joint function. Finite element modeling shows that fortification of the degenerate cartilage (Reinforcement) and reestablishment of a superficial zone (Sealing) are both required to restore fluid pressurization within the tissue and restrict fluid flow and matrix loss from the defect surface. Here, a hyaluronic acid (HA) hydrogel system is designed to both interdigitate with and promote the sealing of the degenerated cartilage. Interdigitating fortification restores both bulk and local pericellular tissue mechanics, reestablishing the homeostatic mechanotransduction of endogenous chondrocytes within the tissue. This HA therapy is further functionalized to present chemo mechanical cues that improve the attachment and direct the response of mesenchymal stem/stromal cells at the defect site, guiding localized extracellular matrix deposition to "seal" the defect. Together, these results support the therapeutic potential, across cell and tissue length scales, of an innovative hydrogel therapy for the treatment of damaged cartilage.

Machine learning augmented near-infrared spectroscopy: In vivo follow-up of cartilage defects

OBJECTIVE

To assess the potential of near-infrared spectroscopy (NIRS) for in vivo arthroscopic monitoring of cartilage defects.

METHOD

Sharp and blunt cartilage grooves were induced in the radiocarpal and intercarpal joints of Shetland ponies and monitored at baseline (0 weeks) and at three follow-up timepoints (11, 23, and 39 weeks) by measuring near-infrared spectra in vivo at and around the grooves. The animals were sacrificed after 39 weeks and the joints were harvested. Spectra were reacquired ex vivo to ensure reliability of in vivo measurements and for reference analyses. Additionally, cartilage thickness and instantaneous modulus were determined via computed tomography and mechanical testing, respectively. The relationship between the ex vivo spectra and cartilage reference properties was determined using convolutional neural network.

RESULTS

In an independent test set, the trained networks yielded significant correlations for cartilage thickness (ρ = 0.473) and instantaneous modulus (ρ = 0.498). These networks were used to predict the reference properties at baseline and at follow-up time points. In the radiocarpal joint, cartilage thickness increased significantly with both groove types after baseline and remained swollen. Additionally, at 39 weeks, a significant difference was observed in cartilage thickness between controls and sharp grooves. For the instantaneous modulus, a significant decrease was observed with both groove types in the radiocarpal joint from baseline to 23 and 39 weeks.

CONCLUSION

NIRS combined with machine learning enabled determination of cartilage properties in vivo, thereby providing longitudinal evaluation of post-intervention injury development. Additionally, radiocarpal joints were found more vulnerable to cartilage degeneration after damage than intercarpal joints.

Rapid CT-based Estimation of Articular Cartilage Biomechanics in the Knee Joint Without Cartilage Segmentation

Knee osteoarthritis (OA) is a painful joint disease, causing disabilities in daily activities. However, there is no known cure for OA, and the best treatment strategy might be prevention. Finite element (FE) modeling has demonstrated potential for evaluating personalized risks for the progression of OA. Current FE modeling approaches use primarily magnetic resonance imaging (MRI) to construct personalized knee joint models. However, MRI is expensive and has lower resolution than computed tomography (CT). In this study, we extend a previously presented atlas-based FE modeling framework for automatic model generation and simulation of knee joint tissue responses using contrast agent-free CT. In this method, based on certain anatomical dimensions measured from bone surfaces, an optimal template is selected and scaled to generate a personalized FE model. We compared the simulated tissue responses of the CT-based models with those of the MRI-based models. We show that the CT-based models are capable of producing similar tensile stresses, fibril strains, and fluid pressures of knee joint cartilage compared to those of the MRI-based models. This study provides a new methodology for the analysis of knee joint and cartilage mechanics based on measurement of bone dimensions from native CT scans.

Computational technology for nasal cartilage-related clinical research and application

Surgeons need to understand the effects of the nasal cartilage on facial morphology, the function of both soft tissues and hard tissues and nasal function when performing nasal surgery. In nasal cartilage-related surgery, the main goals for clinical research should include clarification of surgical goals, rationalization of surgical methods, precision and personalization of surgical design and preparation and improved convenience of doctor-patient communication. Computational technology has become an effective way to achieve these goals. Advances in three-dimensional (3D) imaging technology will promote nasal cartilage-related applications, including research on computational modelling technology, computational simulation technology, virtual surgery planning and 3D printing technology. These technologies are destined to revolutionize nasal surgery further. In this review, we summarize the advantages, latest findings and application progress of various computational technologies used in clinical nasal cartilage-related work and research. The application prospects of each technique are also discussed.

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

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

EMG-Assisted Muscle Force Driven Finite Element Model of the Knee Joint with Fibril-Reinforced Poroelastic Cartilages and Menisci

Abnormal mechanical loading is essential in the onset and progression of knee osteoarthritis. Combined musculoskeletal (MS) and finite element (FE) modeling is a typical method to estimate load distribution and tissue responses in the knee joint. However, earlier combined models mostly utilize static-optimization based MS models and muscle force driven FE models typically use elastic materials for soft tissues or analyze specific time points of gait. Therefore, here we develop an electromyography-assisted muscle force driven FE model with fibril-reinforced poro(visco)elastic cartilages and menisci to analyze knee joint loading during the stance phase of gait. Moreover, since ligament pre-strains are one of the important uncertainties in joint modeling, we conducted a sensitivity analysis on the pre-strains of anterior and posterior cruciate ligaments (ACL and PCL) as well as medial and lateral collateral ligaments (MCL and LCL). The model produced kinematics and kinetics consistent with previous experimental data. Joint contact forces and contact areas were highly sensitive to ACL and PCL pre-strains, while those changed less cartilage stresses, fibril strains, and fluid pressures. The presented workflow could be used in a wide range of applications related to the aetiology of cartilage degeneration, optimization of rehabilitation exercises, and simulation of knee surgeries.

EMG-Assisted Muscle Force Driven Finite Element Model of the Knee Joint with Fibril-Reinforced Poroelastic Cartilages and Menisci

Abnormal mechanical loading is essential in the onset and progression of knee osteoarthritis. Combined musculoskeletal (MS) and finite element (FE) modeling is a typical method to estimate load distribution and tissue responses in the knee joint. However, earlier combined models mostly utilize static-optimization based MS models and muscle force driven FE models typically use elastic materials for soft tissues or analyze specific time points of gait. Therefore, here we develop an electromyography-assisted muscle force driven FE model with fibril-reinforced poro(visco)elastic cartilages and menisci to analyze knee joint loading during the stance phase of gait. Moreover, since ligament pre-strains are one of the important uncertainties in joint modeling, we conducted a sensitivity analysis on the pre-strains of anterior and posterior cruciate ligaments (ACL and PCL) as well as medial and lateral collateral ligaments (MCL and LCL). The model produced kinematics and kinetics consistent with previous experimental data. Joint contact forces and contact areas were highly sensitive to ACL and PCL pre-strains, while those changed less cartilage stresses, fibril strains, and fluid pressures. The presented workflow could be used in a wide range of applications related to the aetiology of cartilage degeneration, optimization of rehabilitation exercises, and simulation of knee surgeries.

The Effect of Articular Cartilage Focal Defect Size and Location in Whole Knee Biomechanics Models

Articular cartilage focal defects are common soft tissue injuries potentially linked to osteoarthritis (OA) development. Although several defect characteristics likely contribute to osteoarthritis, their relationship to local tissue deformation remains unclear. Using finite element models with various femoral cartilage geometries, we explore how defects change cartilage deformation and joint kinematics assuming loading representative of the maximum joint compression during the stance phase of gait. We show how defects, in combination with location-dependent cartilage mechanics, alter deformation in affected and opposing cartilages, as well as joint kinematics. Small and average sized defects increased maximum compressive strains by approximately 50% and 100%, respectively, compared to healthy cartilage. Shifts in the spatial locations of maximum compressive strains of defect containing models were also observed, resulting in loading of cartilage regions with reduced initial stiffnesses supporting the new, elevated loading environments. Simulated osteoarthritis (modeled as a global reduction in mean cartilage stiffness) did not significantly alter joint kinematics, but exacerbated tissue deformation. Femoral defects were also found to affect healthy tibial cartilage deformations. Lateral femoral defects increased tibial cartilage maximum compressive strains by 25%, while small and average sized medial defects exhibited decreases of 6% and 15%, respectively, compared to healthy cartilage. Femoral defects also affected the spatial distributions of deformation across the articular surfaces. These deviations are especially meaningful in the context of cartilage with location-dependent mechanics, leading to increases in peak contact stresses supported by the cartilage of between 11% and 34% over healthy cartilage.

Monitoring the health of transitioning professional footballers: protocol of an observational prospective cohort study

INTRODUCTION

Transitioning out of professional football is a challenging time in most players' lives. During these preretirement and postretirement years, professional footballers may struggle with their mental, musculoskeletal, neurocognitive and cardiovascular health. Currently, longitudinal data about these health conditions are lacking. This article presents the design of a prospective cohort study with the primary aim of gathering epidemiological evidence about the onset and course of mental, musculoskeletal, neurocognitive and cardiovascular health conditions in professional footballers during their preretirement and postretirement years and evaluating the associations between risk indicators and the health conditions under study in these players.

METHODS AND ANALYSIS

An observational prospective cohort study with repeated measurements over a follow-up period of 10 years will be conducted among at least 200 professional footballers (male; 27 (±1) years old). Mental health will be explored by assessing symptoms of distress, anxiety, depression, sleep disturbance, alcohol misuse, drug misuse and disordered eating. Musculoskeletal health will be explored by assessing severe joint injury and related surgery, clinical and radiological osteoarthritis, and joint function (hips, knees and ankles). Neurocognitive health will be explored by assessing the concussion, brain structure and functioning, and neurocognitive functioning. Cardiovascular health will be explored by assessing blood pressure, lipid profile and ECG abnormalities.

ETHICS AND DISSEMINATION

Ethical approval for the study was provided by the Medical Ethics Review Committee of the Amsterdam University Medical Centers. The results of the study will be submitted to peer-reviewed journals, will be presented at scientific conferences and will be released in the media (postpublication).

TRIAL REGISTRATION NUMBER

The Dutch Trial Registry (Drake Football Study NL7999).

Effects of a Medial Knee Unloading Implant on Tibiofemoral Joint Mechanics During Walking

The Atlas™ unicompartmental knee system is a second-generation extra-articular unloading implant for patients with mild to moderate medial knee osteoarthritis. The technology acts to reduce a portion of the weight-bearing load exerted on the medial knee during physical activity thereby, reducing the mechanical stress imposed on a degenerative joint. The purpose of the present study was to evaluate the effects of the Atlas™ on tibiofemoral joint mechanics during walking. A computer-aided design assembly of the Atlas™ was virtually implanted on the medial aspect of a previously validated finite element tibiofemoral joint model. Data for knee joint forces and moments from an anthropometrically matched male were applied to the model to quasi-statically simulate the stance phase of gait. Predictions of tibiofemoral joint mechanics were computed pre- and post-virtual implantation of the Atlas™. Compressive force in the medial tibiofemoral compartment was reduced by a mean of 53%, resulting in the decrement of mean cartilage-cartilage and cartilage-meniscus von Mises stress by 31% and 32%, respectively. The Atlas™ was not predicted to transfer net loading to the lateral compartment. The tibiofemoral joint model exhibited less internal-external rotation and anterior-posterior translation post-Atlas™, indicating a change in the kinematic environment of the knee. From a biomechanical perspective, extra-articular joint unloading may serve as a treatment option for patients recalcitrant to conservative care. Evaluation of mechanical changes in the tibiofemoral joint demonstrate the potential treatment mechanism of the Atlas™, in accordance with the available clinical data. © 2019 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 37:2149-2156, 2019.

Effects of mechanical injury on the tribological rehydration and lubrication of articular cartilage

Healthy articular cartilage is crucial to joint function, as it provides the low friction and load bearing surface necessary for joint articulation. Nonetheless, joint injury places patients at increased risk of experiencing both accelerated cartilage degeneration and wear, and joint dysfunction due to post-traumatic osteoarthritis (PTOA). In this study, we used our ex vivo convergent stationary contact area (cSCA) explant testing configuration to demonstrate that high-speed sliding of healthy tissues against glass could drive consistent and reproducible recovery of compression-induced cartilage deformation, through the mechanism of 'tribological rehydration'. In contrast, the presence of physical cartilage damage, mimicking those injuries known to precipitate PTOA, could compromise tribological rehydration and the sliding-driven recovery of cartilage function. Full-thickness cartilage injuries (i.e. fissures and chondral defects) markedly suppressed sliding-driven tribological rehydration. In contrast, impaction to cartilage, which caused surface associated damage, had little effect on the immediate tribomechanical response of explants to sliding (deformation/strain, tribological rehydration, and friction/lubricity). By leveraging the unique ability of the cSCA configuration to support tribological rehydration, this study permitted the first direct ex vivo investigation of injury-dependent strain and friction outcomes in cartilage under testing conditions that replicate and maintain physiologically-relevant levels of fluid load support and frictional outcomes under high sliding speeds (80 mm/s) and moderate compressive stresses (~0.3 MPa). Understanding how injury alters cartilage tribomechanics during sliding sheds light on mechanisms by which cartilage's long-term resilience and low frictional properties are maintained, and can guide studies investigating the functional consequences of physical injury and joint articulation on cartilage health, disease, and rehabilitation.

Polymer Fiber Scaffolds for Bone and Cartilage Tissue Engineering

Successful regeneration of weight‐bearing bone defects and critical‐sized cartilage defects remains a major challenge in clinical orthopedics. In the past decades, biodegradable polymer materials with biomimetic chemical and physical properties have been rapidly developed as ideal candidates for bone and cartilage tissue engineering scaffolds. Due to their unique advantages over other materials of high specific‐surface areas, suitable mechanical strength, and tailorable characteristics, scaffolds made of polymer fibers have been increasingly used for the repair of bone and cartilage defects. This Review summarizes the preparation and compositions of polymer fibers, as well as their characteristics. More importantly, the applications of polymer fiber scaffolds with well‐designed structures or unique properties in bone, cartilage, and osteochondral tissue engineering have been comprehensively highlighted. On the whole, such a comprehensive summary affords constructive suggestions for the development of polymer fiber scaffolds in bone and cartilage tissue engineering.

Bioactive factors for cartilage repair and regeneration: Improving delivery, retention, and activity

Articular cartilage is a remarkable tissue whose sophisticated composition and architecture allow it to withstand complex stresses within the joint. Once injured, cartilage lacks the capacity to self-repair, and injuries often progress to joint wide osteoarthritis (OA) resulting in debilitating pain and loss of mobility. Current palliative and surgical management provides short-term symptom relief, but almost always progresses to further deterioration in the long term. A number of bioactive factors, including drugs, corticosteroids, and growth factors, have been utilized in the clinic, in clinical trials, or in emerging research studies to alleviate the inflamed joint environment or to promote new cartilage tissue formation. However, these therapies remain limited in their duration and effectiveness. For this reason, current efforts are focused on improving the localization, retention, and activity of these bioactive factors. The purpose of this review is to highlight recent advances in drug delivery for the treatment of damaged or degenerated cartilage. First, we summarize material and modification techniques to improve the delivery of these factors to damaged tissue and enhance their retention and action within the joint environment. Second, we discuss recent studies using novel methods to promote new cartilage formation via biofactor delivery, that have potential for improving future long-term clinical outcomes. Lastly, we review the emerging field of orthobiologics, using delivered and endogenous cells as drug-delivering "factories" to preserve and restore joint health. Enhancing drug delivery systems can improve both restorative and regenerative treatments for damaged cartilage. STATEMENT OF SIGNIFICANCE: Articular cartilage is a remarkable and sophisticated tissue that tolerates complex stresses within the joint. When injured, cartilage cannot self-repair, and these injuries often progress to joint-wide osteoarthritis, causing patients debilitating pain and loss of mobility. Current palliative and surgical treatments only provide short-term symptomatic relief and are limited with regards to efficiency and efficacy. Bioactive factors, such as drugs and growth factors, can improve outcomes to either stabilize the degenerated environment or regenerate replacement tissue. This review highlights recent advances and novel techniques to enhance the delivery, localization, retention, and activity of these factors, providing an overview of the cartilage drug delivery field that can guide future research in restorative and regenerative treatments for damaged cartilage.

Assessment and prevention of cartilage degeneration surrounding a focal chondral defect in the porcine model

Focal defects in articular cartilage are unable to self-repair and, if left untreated, are a leading risk factor for osteoarthritis. This study examined cartilage degeneration surrounding a defect and then assessed whether infilling the defect prevents degeneration. We created a focal chondral defect in porcine osteochondral explants and cultured them ex vivo with and without dynamic compressive loading to decouple the role of loading. When compared to a defect in a porcine knee four weeks post-injury, this model captured loss in sulfated glycosaminoglycans (sGAGs) along the defect's edge that was observed in vivo, but this loss was not load dependent. Loading, however, reduced the indentation modulus of the surrounding cartilage. After infilling with in situ polymerized hydrogels that were soft (100 kPa) or stiff (1 MPa) and which produced swelling pressures of 13 and 310 kPa, respectively, sGAG loss was reduced. This reduction correlated with increased hydrogel stiffness and swelling pressure, but was not affected by loading. This ex vivo model recapitulates sGAG loss surrounding a defect and, when infilled with a mechanically supportive hydrogel, degeneration is minimized.

Neuro-musculoskeletal flexible multibody simulation yields a framework for efficient bone failure risk assessment

Fragility fractures are a major socioeconomic problem. A non-invasive, computationally-efficient method for the identification of fracture risk scenarios under the representation of neuro-musculoskeletal dynamics does not exist. We introduce a computational workflow that integrates modally-reduced, quantitative CT-based finite-element models into neuro-musculoskeletal flexible multibody simulation (NfMBS) for early bone fracture risk assessment. Our workflow quantifies the bone strength via the osteogenic stresses and strains that arise due to the physiological-like loading of the bone under the representation of patient-specific neuro-musculoskeletal dynamics. This allows for non-invasive, computationally-efficient dynamic analysis over the enormous parameter space of fracture risk scenarios, while requiring only sparse clinical data. Experimental validation on a fresh human femur specimen together with femur strength computations that were consistent with literature findings provide confidence in the workflow: The simulation of an entire squat took only 38 s CPU-time. Owing to the loss (16% cortical, 33% trabecular) of bone mineral density (BMD), the strain measure that is associated with bone fracture increased by 31.4%; and yielded an elevated risk of a femoral hip fracture. Our novel workflow could offer clinicians with decision-making guidance by enabling the first combined in-silico analysis tool using NfMBS and BMD measurements for optimized bone fracture risk assessment.

Arthroscopic Determination of Cartilage Proteoglycan Content and Collagen Network Structure with Near-Infrared Spectroscopy

Conventional arthroscopic evaluation of articular cartilage is subjective and insufficient for assessing early compositional and structural changes during the progression of post-traumatic osteoarthritis. Therefore, in this study, arthroscopic near-infrared (NIR) spectroscopy is introduced, for the first time, for in vivo evaluation of articular cartilage thickness, proteoglycan (PG) content, and collagen orientation angle. NIR spectra were acquired in vivo and in vitro from equine cartilage adjacent to experimental cartilage repair sites. As reference, digital densitometry and polarized light microscopy were used to evaluate superficial and full-thickness PG content and collagen orientation angle. To relate NIR spectra and cartilage properties, ensemble neural networks, each with two different architectures, were trained and evaluated by using Spearman’s correlation analysis (ρ). The ensemble networks enabled accurate predictions for full-thickness reference properties (PG content: ρ_{in vitro, Val}= 0.691, ρ_{in vivo}= 0.676; collagen orientation angle: ρ_{in vitro, Val}= 0.626, ρ_{in vivo}= 0.574) from NIR spectral data. In addition, the networks enabled reliable prediction of PG content in superficial (25%) cartilage (ρ_{in vitro, Val}= 0.650, ρ_{in vivo}= 0.613) and cartilage thickness (ρ_{in vitro, Val}= 0.797, ρ_{in vivo}= 0.596). To conclude, NIR spectroscopy could enhance the detection of initial cartilage degeneration and thus enable demarcation of the boundary between healthy and compromised cartilage tissue during arthroscopic surgery.

Computational evaluation of altered biomechanics related to articular cartilage lesions observed in vivo

Chondral lesions provide a potential risk factor for development of osteoarthritis. Despite the variety of in vitro studies on lesion degeneration, in vivo studies that evaluate relation between lesion characteristics and the risk for the possible progression of OA are lacking. Here, we aimed to characterize different lesions and quantify biomechanical responses experienced by surrounding cartilage tissue. We generated computational knee joint models with nine chondral injuries based on clinical in vivo arthrographic computed tomography images. Finite element models with fibril-reinforced poro(visco)elastic cartilage and menisci were constructed to simulate physiological loading. Systematically, the lesions experienced increased peak values of maximum principal strain, maximum shear strain, and minimum principal strain in the surrounding chondral tissue (p < 0.01) compared with intact tissue. Depth, volume, and area of the lesion correlated with the maximum shear strain (p < 0.05, Spearman rank correlation coefficient ρ = 0.733-0.917). Depth and volume of the lesion correlated also with the maximum principal strain (p < 0.05, ρ = 0.767, and ρ = 0.717, respectively). However, the lesion area had non-significant correlation with this strain parameter (p = 0.06, ρ = 0.65). Potentially, the introduced approach could be developed for clinical evaluation of biomechanical risks of a chondral lesion and planning an intervention. Statement of Clinical Relevance: In this study, we computationally characterized different in vivo chondral lesions and evaluated their risk of cartilage degeneration. This information is vital in decision-making for intervention in order to prevent post-traumatic osteoarthritis. © 2019 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res.

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.

Functional assessment of strains around a full-thickness and critical sized articular cartilage defect under compressive loading using MRI

OBJECTIVE

The objective of this study was to evaluate the effect of full-thickness chondral defects on intratissue deformation patterns and matrix constituents in an experimental model mimicking in vivo cartilage-on-cartilage contact conditions.

DESIGN

Pairs of bovine osteochondral explants, in a unique cartilage-on-cartilage model system, were compressed uniaxially by 350 N during 2 s loading and 1.4 s unloading cycles (≈1700 repetitions). Tissue deformations under quasi-steady state load deformation response were measured with displacement encoded imaging with stimulated echoes (DENSE) in a 9.4 T magnetic resonance imaging (MRI) scanner. Pre- and post-loading, T₁, T₂ and T_1ρ relaxation time maps were measured. We analyzed differences in strain patterns and relaxation times between intact cartilage (n = 8) and cartilage in which a full-thickness and critical sized defect was created (n = 8).

RESULTS

Under compressive loading, strain magnitudes were elevated at the defect rim, with elevated tensile and compressive principal strains (Δϵ_max = 4.2%, P = 0.02; Δϵ_min = -4.3%, P = 0.02) and maximum shear strain at the defect rim (Δγ_max = 4.4%, P = 0.007). The opposing cartilage showed minimal increase in strain patterns at contact with the defect rim but decreased strains opposing the defect. After defect creation, T₁, T₂ and T_1ρ relaxation times were elevated at the defect rim only. Following loading, the overall relaxations times of the defect tissue and especially at the rim, increased compared to intact cartilage.

CONCLUSIONS

This study demonstrates that the local biomechanical changes occurring after defect creation may induce tissue damage by increasing shear strains and depletion of cartilage constituents at the defect rim under compressive loading.

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.

Osteochondral resurfacing implantation angle is more important than implant material stiffness

Osteochondral resurfacing implants are a promising treatment for focal cartilage defects. Several implant-factors may affect the clinical outcome of this treatment, such as the implant material stiffness and the accuracy of implant placement, known to be challenging. In general, softer implants are expected to be more accommodating for implant misalignment than stiffer implants, and motion is expected to increase effects from implant misalignment and stiffness. 3D finite element models of cartilage/cartilage contact were employed in which implantation angle (0°, 5°, 10°) and implant material stiffness (E = 5 MPa, 100 MPa, 2 GPa) were varied. A creep loading (0.6 MPa) was simulated, followed by a sliding motion. Creep loading resulted in low maximum collagen strains of 2.5% in the intact case compared to 11.7% with an empty defect. Implants mostly positively affected collagen strains, deviatoric strains, and hydrostatic pressures in the adjacent cartilage, but these effects were superior for correct alignment (0°). The main effect of implant misalignment was bulging of opposing cartilage tissue into the gap caused by the misalignment. This increased collagen strains and hydrostatic pressures. Deviatoric strains were increased adjacent to the gap. Subsequent sliding initially increased strains for a stiff, misaligned implant, but generally sliding decreased strains. In conclusion, implants can decrease the detrimental effect of defects, but correct implant alignment is crucial, more than implant material stiffness. Implant misalignment causes a gap, causing potentially damaging cartilage deformation during prolonged loading, for example, standing, even for soft implants. Mild motion may positively affect the cartilage. © 2018 The Authors. Journal of Orthopaedic Research® published by Wiley Periodicals, Inc. on behalf of Orthopaedic Research Society. J Orthop Res 36:2911-2922, 2018.

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.

Cartilage defect location and stiffness predispose the tibiofemoral joint to aberrant loading conditions during stance phase of gait

OBJECTIVES

The current study quantified the influence of cartilage defect location on the tibiofemoral load distribution during gait. Furthermore, changes in local mechanical stiffness representative for matrix damage or bone ingrowth were investigated. This may provide insights in the mechanical factors contributing to cartilage degeneration in the presence of an articular cartilage defect.

METHODS

The load distribution following cartilage defects was calculated using a musculoskeletal model that included tibiofemoral and patellofemoral joints with 6 degrees-of-freedom. Circular cartilage defects of 100 mm2 were created at different locations in the tibiofemoral contact geometry. By assigning different mechanical properties to these defect locations, softening and hardening of the tissue were evaluated.

RESULTS

Results indicate that cartilage defects located at the load-bearing area only affect the load distribution of the involved compartment. Cartilage defects in the central part of the tibia plateau and anterior-central part of the medial femoral condyle present the largest influence on load distribution. Softening at the defect location results in overloading, i.e., increased contact pressure and compressive strains, of the surrounding tissue. In contrast, inside the defect, the contact pressure decreases and the compressive strain increases. Hardening at the defect location presents the opposite results in load distribution compared to softening. Sensitivity analysis reveals that the surrounding contact pressure, contact force and compressive strain alter significantly when the elastic modulus is below 7 MPa or above 18 MPa.

CONCLUSION

Alterations in local mechanical behavior within the high load bearing area resulted in aberrant loading conditions, thereby potentially affecting the homeostatic balance not only at the defect but also at the tissue surrounding and opposing the defect. Especially, cartilage softening predisposes the tissue to loads that may contribute to accelerated risk of cartilage degeneration and the initiation or progression towards osteoarthritis of the whole compartment.

Arthroscopic near infrared spectroscopy enables simultaneous quantitative evaluation of articular cartilage and subchondral bone in vivo

Arthroscopic assessment of articular tissues is highly subjective and poorly reproducible. To ensure optimal patient care, quantitative techniques (e.g., near infrared spectroscopy (NIRS)) could substantially enhance arthroscopic diagnosis of initial signs of post-traumatic osteoarthritis (PTOA). Here, we demonstrate, for the first time, the potential of arthroscopic NIRS to simultaneously monitor progressive degeneration of cartilage and subchondral bone in vivo in Shetland ponies undergoing different experimental cartilage repair procedures. Osteochondral tissues adjacent to the repair sites were evaluated using an arthroscopic NIRS probe and significant (p < 0.05) degenerative changes were observed in the tissue properties when compared with tissues from healthy joints. Artificial neural networks (ANN) enabled reliable (ρ = 0.63–0.87, NMRSE = 8.5–17.2%, RPIQ = 1.93–3.03) estimation of articular cartilage biomechanical properties, subchondral bone plate thickness and bone mineral density (BMD), and subchondral trabecular bone thickness, bone volume fraction (BV), BMD, and structure model index (SMI) from in vitro spectral data. The trained ANNs also reliably predicted the properties of an independent in vitro test group (ρ = 0.54–0.91, NMRSE = 5.9–17.6%, RPIQ = 1.68–3.36). However, predictions based on arthroscopic NIR spectra were less reliable (ρ = 0.27–0.74, NMRSE = 14.5–24.0%, RPIQ = 1.35–1.70), possibly due to errors introduced during arthroscopic spectral acquisition. Adaptation of NIRS could address the limitations of conventional arthroscopy through quantitative assessment of lesion severity and extent, thereby enhancing detection of initial signs of PTOA. This would be of high clinical significance, for example, when conducting orthopaedic repair surgeries.

Method for Segmentation of Knee Articular Cartilages Based on Contrast-Enhanced CT Images

Segmentation of contrast-enhanced computed tomography (CECT) images enables quantitative evaluation of morphology of articular cartilage as well as the significance of the lesions. Unfortunately, automatic segmentation methods for CECT images are currently lacking. Here, we introduce a semiautomated technique to segment articular cartilage from in vivo CECT images of human knee. The segmented cartilage geometries of nine knee joints, imaged using a clinical CT-scanner with an intra-articular contrast agent, were compared with manual segmentations from CT and magnetic resonance (MR) images. The Dice similarity coefficients (DSCs) between semiautomatic and manual CT segmentations were 0.79-0.83 and sensitivity and specificity values were also high (0.76-0.86). When comparing semiautomatic and manual CT segmentations, mean cartilage thicknesses agreed well (intraclass correlation coefficient = 0.85-0.93); the difference in thickness (mean ± SD) was 0.27 ± 0.03 mm. Differences in DSC, when MR segmentations were compared with manual and semiautomated CT segmentations, were statistically insignificant. Similarly, differences in volume were not statistically significant between manual and semiautomatic CT segmentations. Semiautomation decreased the segmentation time from 450 ± 190 to 42 ± 10 min per joint. The results reveal that the proposed technique is fast and reliable for segmentation of cartilage. Importantly, this is the first study presenting semiautomated segmentation of cartilage from CECT images of human knee joint with minimal user interaction.

Strain distribution of repaired articular cartilage defects by tissue engineering under compression loading

Background

It is difficult to repair cartilage damage when cartilage undergoes trauma or degeneration. Cartilage tissue engineering is an ideal treatment method to repair cartilage defects, but at present, there are still some uncertainties to be researched in cartilage tissue engineering including the mechanical properties of the repaired region.

Methods

In this study, using an agarose gel as artificial cartilage implanted into the cartilage defect and gluing the agarose gel to cartilage by using the medical bio-adhesive, the full-thickness and half-thickness defects models of articular cartilage in vitro repaired by tissue engineering were constructed. Strain behaviors of the repaired region were analyzed by the digital correlation technology under 5, 10, 15, and 20% compressive load.

Results

The axial normal strain (Ex) perpendicular to the surface of the cartilage and lateral normal strain (Ey) as well as shear strain (Exy) appeared obviously heterogeneous in the repaired region. In the full-defect model, Ex showed depth-dependent strain profiles where maximum Ex occurs at the low middle zone while in the half-defect mode, Ex showed heterogeneous strain profiles where maximum Ex occurs at the near deep zone. Ey and Exy at the interface site of both models present significantly differed from the host cartilage site. Ey and Exy exhibited region-specific change at the host, interface, and artificial cartilage sites in the superficial, middle, and deep zones due to the artificial cartilage implantation.

Conclusion

Both defect models of cartilage exhibited a heterogeneous strain field due to the engineered cartilage tissue implant. The abnormal strain field can cause the cells within the repaired area to enter complex mechanical states which will affect the restoration of cartilage defects.

Tissue material properties and computational modelling of the human tibiofemoral joint: a critical review

Understanding how structural and functional alterations of individual tissues impact on whole-joint function is challenging, particularly in humans where direct invasive experimentation is difficult. Finite element (FE) computational models produce quantitative predictions of the mechanical and physiological behaviour of multiple tissues simultaneously, thereby providing a means to study changes that occur through healthy ageing and disease such as osteoarthritis (OA). As a result, significant research investment has been placed in developing such models of the human knee. Previous work has highlighted that model predictions are highly sensitive to the various inputs used to build them, particularly the mathematical definition of material properties of biological tissues. The goal of this systematic review is two-fold. First, we provide a comprehensive summation and evaluation of existing linear elastic material property data for human tibiofemoral joint tissues, tabulating numerical values as a reference resource for future studies. Second, we review efforts to model tibiofemoral joint mechanical behaviour through FE modelling with particular focus on how studies have sourced tissue material properties. The last decade has seen a renaissance in material testing fuelled by development of a variety of new engineering techniques that allow the mechanical behaviour of both soft and hard tissues to be characterised at a spectrum of scales from nano- to bulk tissue level. As a result, there now exists an extremely broad range of published values for human tibiofemoral joint tissues. However, our systematic review highlights gaps and ambiguities that mean quantitative understanding of how tissue material properties alter with age and OA is limited. It is therefore currently challenging to construct FE models of the knee that are truly representative of a specific age or disease-state. Consequently, recent tibiofemoral joint FE models have been highly generic in terms of material properties even relying on non-human data from multiple species. We highlight this by critically evaluating current ability to quantitatively compare and model (1) young and old and (2) healthy and OA human tibiofemoral joints. We suggest that future research into both healthy and diseased knee function will benefit greatly from a subject- or cohort-specific approach in which FE models are constructed using material properties, medical imagery and loading data from cohorts with consistent demographics and/or disease states.