Petri Tanska

Characterization of site-specific biomechanical properties of human meniscus—Importance of collagen and fluid on mechanical nonlinearities

Meniscus adapts to joint loads by depth- and site-specific variations in its composition and structure. However, site-specific mechanical characteristics of intact meniscus under compression are poorly known. In particular, mechanical nonlinearities caused by different meniscal constituents (collagen and fluid) are not known. In the current study, in situ indentation testing was conducted to determine site-specific elastic, viscoelastic and poroelastic properties of intact human menisci. Lateral and medial menisci (n=26) were harvested from the left knee joint of 13 human cadavers. Indentation tests, using stress-relaxation and dynamic (sinusoidal) loading protocols, were conducted for menisci at different sites (anterior, middle, posterior, n=78). Sample- and site-specific axisymmetric finite element models with fibril-reinforced poroelastic properties were fitted to the corresponding stress-relaxation curves to determine the mechanical parameters. Elastic moduli, especially the instantaneous and dynamic moduli, showed site-specific variation only in the medial meniscus (p<0.05 between the sites). The instantaneous and dynamic elastic moduli of the anterior horn were significantly (p<0.05) greater in the medial than lateral meniscus. The phase angle showed no statistically significant variation between the sites (p>0.05). The values for the strain-dependent fibril network modulus (nonlinear behaviour of collagen) were significantly different (p<0.05) between all sites in the medial menisci. Additionally, there was a significant difference (p<0.01) in the strain-dependent fibril network modulus between the lateral and medial anterior horns. The initial permeability was significantly different (p<0.05) in the medial meniscus only between the middle and posterior sites. For the strain-dependent permeability coefficient, only anterior and middle sites showed a significant difference (p<0.05) in the medial meniscus. This parameter demonstrated a significant difference (p<0.05) between lateral and medial menisci at the anterior horns. Our results reveal that under in situ indentation loading, medial meniscus shows more site-dependent variation in the mechanical properties as compared to lateral meniscus. In particular, anterior horn of medial meniscus was the stiffest and showed the most nonlinear mechanical behaviour. The nonlinearity was related to both collagen fibrils and fluid.

A multi-scale finite element model for investigation of chondrocyte mechanics in normal and medial meniscectomy human knee joint during walking

Mechanical signals experienced by chondrocytes (articular cartilage cells) modulate cell synthesis and cartilage health. Multi-scale modeling can be used to study how forces are transferred from joint surfaces through tissues to chondrocytes. Therefore, estimation of chondrocyte behavior during certain physical activities, such as walking, could provide information about how cells respond to normal and abnormal loading in joints. In this study, a 3D multi-scale model was developed for evaluating chondrocyte and surrounding peri- and extracellular matrix responses during gait loading within healthy and medial meniscectomy knee joints. The knee joint geometry was based on MRI, whereas the input used for gait loading was obtained from the literature. Femoral and tibial cartilages were modeled as fibril-reinforced poroviscoelastic materials, whereas menisci were considered as transversely isotropic. Fluid pressures in the chondrocyte and cartilage tissue increased up to 2MPa (an increase of 30%) in the meniscectomy joint compared to the normal, healthy joint. The elevated level of fluid pressure was observed during the entire stance phase of gait. A medial meniscectomy caused substantially larger (up to 60%) changes in maximum principal strains in the chondrocyte compared to those in the peri- or extracellular matrices. Chondrocyte volume or morphology did not change substantially due to a medial meniscectomy. Current findings suggest that during walking chondrocyte deformations are not substantially altered due to a medial meniscectomy, while abnormal joint loading exposes chondrocytes to elevated levels of fluid pressure and maximum principal strains (compared to strains in the peri- or extracellular matrices). These might contribute to cell viability and the onset of osteoarthritis.

Superficial collagen fibril modulus and pericellular fixed charge density modulate chondrocyte volumetric behaviour in early osteoarthritis.

The aim of this study was to investigate if the experimentally detected altered chondrocyte volumetric behavior in early osteoarthritis can be explained by changes in the extracellular and pericellular matrix properties of cartilage. Based on our own experimental tests and the literature, the structural and mechanical parameters for normal and osteoarthritic cartilage were implemented into a multiscale fibril-reinforced poroelastic swelling model. Model simulations were compared with experimentally observed cell volume changes in mechanically loaded cartilage, obtained from anterior cruciate ligament transected rabbit knees. We found that the cell volume increased by 7% in the osteoarthritic cartilage model following mechanical loading of the tissue. In contrast, the cell volume decreased by 4% in normal cartilage model. These findings were consistent with the experimental results. Increased local transversal tissue strain due to the reduced collagen fibril stiffness accompanied with the reduced fixed charge density of the pericellular matrix could increase the cell volume up to 12%. These findings suggest that the increase in the cell volume in mechanically loaded osteoarthritic cartilage is primarily explained by the reduction in the pericellular fixed charge density, while the superficial collagen fibril stiffness is suggested to contribute secondarily to the cell volume behavior.

New Concept to Restore Normal Cell Responses in Osteoarthritic Knee Joint Cartilage.

Prediction of osteoarthritis progression does not exist. Cartilage “health” and degeneration during osteoarthritis depend on the signals perceived by chondrocytes. We hypothesize that biomechanical responses of chondrocytes in osteoarthritic cartilage can be restored close to their normal state. We propose an approach to evaluate quantitatively these responses in human joints and demonstrate how they can return close to normal levels.

Spatial variation of fixed charge density in knee joint cartilage from sodium MRI – Implication on knee joint mechanics under static loading

The effects of fixed charge density (FCD) and cartilage swelling have not been demonstrated on cartilage mechanics on knee joint level before. In this study, we present how the spatial and local variations of FCD affects the mechanical response of the knee joint cartilage during standing (half of the body weight, 13 minutes) using finite element (FE) modeling. The FCD distribution of tibial cartilage of an asymptomatic subject was determined using sodium (23Na) MRI at 7T and implemented into a 3-D FE-model of the knee joint (Subject-specific model, FCD: 0.18±0.08 mEq/ml). Tissue deformation in the Subject-specific model was validated against experimental, in vivo loading of the joint conducted with a MR-compatible compression device. For comparison, models with homogeneous FCD distribution (homogeneous model) and FCD distribution obtained from literature (literature model) were created. Immediately after application of the load (dynamic response), the variations in FCD had minor effects on cartilage stresses and strains. After 13 minutes of standing, the spatial and local variations in FCD had most influence on axial strains. In the superficial tibial cartilage in the Subject-specific model, axial strains were increased up to +13% due to smaller FCD (mean -11%), as compared to the homogeneous model. Compared to the literature model, those were decreased up to -18% due to greater FCD (mean +7%). The findings demonstrate that the spatial and local FCD variations in cartilage modulates strains in knee joint cartilage. Thereby, the results highlight the mechanical importance of site-specific content of proteoglycans in cartilage.

Comparison of different material models of articular cartilage in 3D computational modeling of the knee: Data from the Osteoarthritis Initiative (OAI)

The intricate properties of articular cartilage and the complexity of the loading environment are some of the key challenges in developing models for biomechanical analysis of the knee joint. Fibril-reinforced poroelastic (FRPE) material models have been reported to accurately capture characteristic responses of cartilage during dynamic and static loadings. However, high computational and time costs associated with such advanced models limit applicability of FRPE models when multiple subjects need to be analyzed. If choosing simpler material models, it is important to show that they can still produce truthful predictions. Therefore, the aim of this study was to compare depth-dependent maximum principal stresses and strains within articular cartilage in the 3D knee joint between FRPE material models and simpler isotropic elastic (IE), isotropic poroelastic (IPE) and transversely isotropic poroelastic (TIPE) material models during simulated gait cycle. When cartilage-cartilage contact pressures were matched between the models (15% allowed difference), maximum principal stresses in the IE, IPE and TIPE models were substantially lower than those in the FRPE model (by more than 50%, TIPE model being closest to the FRPE model), and stresses occurred only in compression in the IE model. Additional simulations were performed to find material parameters for the TIPE model (due to its anisotropic nature) that would yield maximum principal stresses similar to the FRPE model. The modified homogeneous TIPE model was in a better agreement with the homogeneous FRPE model, and the average and maximum differences in maximum principal stresses throughout the depth of cartilage were 7% and 9%, respectively, in the lateral compartment and 9% and 11% in the medial compartment. This study revealed that it is possible to match simultaneously maximum principal stresses and strains of cartilage between non-fibril-reinforced and fibril-reinforced knee joint models during gait. Depending on the research question (such as analysis of fibril strain necessitates the use of fibril-reinforced material models) or clinical demand (fast simulations with simpler material models), the choice of the material model should be done carefully.

Optical coherence tomography enables accurate measurement of equine cartilage thickness for determination of speed of sound

Background and purpose — Arthroscopic estimation of articular cartilage thickness is important for scoring of lesion severity, and measurement of cartilage speed of sound (SOS)—a sensitive index of changes in cartilage composition. We investigated the accuracy of optical coherence tomography (OCT) in measurements of cartilage thickness and determined SOS by combining OCT thickness and ultrasound (US) time-of-flight (TOF) measurements. Material and methods — Cartilage thickness measurements from OCT and microscopy images of 94 equine osteochondral samples were compared. Then, SOS in cartilage was determined using simultaneous OCT thickness and US TOF measurements. SOS was then compared with the compositional, structural, and mechanical properties of cartilage. Results — Measurements of non-calcified cartilage thickness using OCT and microscopy were significantly correlated (ρ = 0.92; p < 0.001). With calcified cartilage included, the correlation was ρ = 0.85 (p < 0.001). The mean cartilage SOS (1,636 m/s) was in agreement with the literature. However, SOS and the other properties of cartilage lacked any statistically significant correlation. Interpretation — OCT can give an accurate measurement of articular cartilage thickness. Although SOS measurements lacked accuracy in thin equine cartilage, the concept of SOS measurement using OCT appears promising.

New algorithm for simulation of proteoglycan loss and collagen degeneration in the knee joint: Data from the osteoarthritis initiative: NEW ALGORITHM FOR SIMULATION OF PROTEOGLYCAN LOSS AND COLLAGEN DEGENERATION

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

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

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

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

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