3D analysis and grading of calcifications from ex vivo human meniscus.

OBJECTIVE: Meniscal calcifications are associated with the pathogenesis of knee osteoarthritis (OA). We propose a micro-computed tomography (µCT) based 3D analysis of meniscal calcifications ex vivo, including a new grading system. METHOD: Human medial and lateral menisci were obtained from 10 patients having total knee replacement for medial compartment OA and 10 deceased donors without knee OA (healthy references). The samples were fixed; one subsection was imaged with µCT, and the adjacent tissue was processed for histological evaluation. Calcifications were examined from the reconstructed 3D µCT images, and a new grading system was developed. To validate the grading system, meniscal calcification volumes (CVM) were quantitatively analyzed and compared between the calcification grades. Furthermore, we estimated the relationship between histopathological degeneration and the calcification severity. RESULTS: 3D µCT images depict calcifications in every sample, including diminutive calcifications that are not visible in histology. In the new grading system, starting from grade 2, each grade results in a CVM that is 20.3 times higher (95% CI 13.3-30.5) than in the previous grade. However, there was no apparent difference in CVM between grades 1 and 2. The calcification grades appear to increase with the increasing histopathological degeneration, although histopathological degeneration is also observed with small calcification grades. CONCLUSIONS: 3D µCT grading of meniscal calcifications is feasible. Interestingly, it seems that there are two patterns of degeneration in the menisci of our sample set: 1) with diminutive calcifications (calcification grades 1-2), and 2) with large to widespread calcifications (calcification grades 3-5).

Comparison of material models for anterior cruciate ligament in tension: from poroelastic to a novel fibril-reinforced nonlinear composite model.

Computational models of the knee joint are useful for evaluating stresses and strains within the joint tissues. However, the outcome of those models is sensitive to the material model and material properties chosen for ligaments, the collagen reinforced tissues connecting bone to bone. The purpose of this study was to investigate different compositionally motivated material models and further to develop a model that can accurately reproduce experimentally measured stress-relaxation data of bovine anterior cruciate ligament (ACL). Tensile testing samples were extracted from ACLs of bovine knee joints (N = 10) and subjected to a three-step stress-relaxation test at the toe region. Data from the experiments was averaged and one average finite element model was generated to replicate the experiment. Poroelastic and different fibril-reinforced poro(visco)elastic material models were applied, and their material parameters were optimized to reproduce the experimental force-time response. Material models with only fluid flow mediated relaxation were not able to capture the stress-relaxation behavior (R2 = 0.806, 0.803 and 0.938). The inclusion of the viscoelasticity of the fibrillar network improved the model prediction (R2 = 0.978 and 0.976), but the complex stress-relaxation behavior was best captured by a poroelastic model with a nonlinear two-relaxation-time strain-recruited viscoelastic fibrillar network (R2 = 0.997). The results suggest that in order to replicate the multi-step stress-relaxation behavior of ACL in tension, the fibrillar network formulation should include the complex nonlinear viscoelastic phenomena.

Automating three-dimensional osteoarthritis histopathological grading of human osteochondral tissue using machine learning on contrast-enhanced micro-computed tomography.

OBJECTIVE: To develop and validate a machine learning (ML) approach for automatic three-dimensional (3D) histopathological grading of osteochondral samples imaged with contrast-enhanced micro-computed tomography (CEµCT). DESIGN: A total of 79 osteochondral cores from 24 total knee arthroplasty patients and two asymptomatic donors were imaged using CEµCT with phosphotungstic acid -staining. Volumes-of-interest (VOI) in surface (SZ), deep (DZ) and calcified (CZ) zones were extracted depth-wise and subjected to dimensionally reduced Local Binary Pattern -textural feature analysis. Regularized linear and logistic regression (LR) models were trained zone-wise against the manually assessed semi-quantitative histopathological CEµCT grades (diameter = 2 mm samples). Models were validated using nested leave-one-out cross-validation and an independent test set (4 mm samples). The performance was primarily assessed using Mean Squared Error (MSE) and Average Precision (AP, confidence intervals are given in square brackets). RESULTS: Highest performance on cross-validation was observed for SZ, both on linear regression (MSE = 0.49, 0.69 and 0.71 for SZ, DZ and CZ, respectively) and LR (AP = 0.9 [0.77-0.99], 0.46 [0.28-0.67] and 0.65 [0.41-0.85] for SZ, DZ and CZ, respectively). The test set evaluations yielded increased MSE on all zones. For LR, the performance was also best for the SZ (AP = 0.85 [0.73-0.93], 0.82 [0.70-0.92] and 0.8 [0.67-0.9], for SZ, DZ and CZ, respectively). CONCLUSION: We present the first ML-based automatic 3D histopathological osteoarthritis (OA) grading method which also adequately perform on grading unseen data, especially in SZ. After further development, the method could potentially be applied by OA researchers since the grading software and all source codes are publicly available.

Comparison of water, hydroxyproline, uronic acid and elastin contents of bovine knee ligaments and patellar tendon and their relationships with biomechanical properties.

Mechanical material properties of ligaments originate from their biochemical composition and structural organization. However, it is not yet fully elucidated how biochemical contents vary between knee ligaments and patellar tendon (PT) and how they relate with mechanical properties. The purpose of this study was to compare water, collagen, proteoglycan and elastin contents between bovine knee ligaments and PT and correlate them with tensile material properties. Hydroxyproline (collagen), uronic acid (proteoglycan) and elastin contents per wet and dry weights were measured using colorimetric biochemical methods for bovine knee ligament and PT samples (n = 10 knees). Direct comparison and correlation with multiple linear regression were performed against biomechanical properties measured in our earlier study. Anterior cruciate ligament (ACL) and PT exhibited lower hydroxyproline content per wet weight compared with other ligaments (p < 0.05). Cruciate ligaments had higher uronic acid content per dry weight compared with collateral ligaments (p < 0.05). Posterior cruciate ligament had higher elastin content than ACL (p < 0.05). Higher hydroxyproline content per wet weight implied higher Young's modulus, strength and toughness. Quantitatively, higher elastin content per wet weight predicted higher toe region nonlinearity and Young's modulus whereas higher uronic acid content per dry weight predicted lower Young's modulus, yield stress and toughness. Differences between ligaments in biochemical composition highlight differences in their physiological function and loading regimes. As expected, collagen content showed similar trend with stiffness and strength. The predictive role of proteoglycan and elastin contents on the mechanical properties might indicate their important functional role in ligaments.

Quantifying Subresolution 3D Morphology of Bone with Clinical Computed Tomography.

The aim of this study was to quantify sub-resolution trabecular bone morphometrics, which are also related to osteoarthritis (OA), from clinical resolution cone beam computed tomography (CBCT). Samples (n = 53) were harvested from human tibiae (N = 4) and femora (N = 7). Grey-level co-occurrence matrix (GLCM) texture and histogram-based parameters were calculated from CBCT imaged trabecular bone data, and compared with the morphometric parameters quantified from micro-computed tomography. As a reference for OA severity, histological sections were subjected to OARSI histopathological grading. GLCM and histogram parameters were correlated to bone morphometrics and OARSI individually. Furthermore, a statistical model of combined GLCM/histogram parameters was generated to estimate the bone morphometrics. Several individual histogram and GLCM parameters had strong associations with various bone morphometrics (|r| > 0.7). The most prominent correlation was observed between the histogram mean and bone volume fraction (r = 0.907). The statistical model combining GLCM and histogram-parameters resulted in even better association with bone volume fraction determined from CBCT data (adjusted R2 change = 0.047). Histopathology showed mainly moderate associations with bone morphometrics (|r| > 0.4). In conclusion, we demonstrated that GLCM- and histogram-based parameters from CBCT imaged trabecular bone (ex vivo) are associated with sub-resolution morphometrics. Our results suggest that sub-resolution morphometrics can be estimated from clinical CBCT images, associations becoming even stronger when combining histogram and GLCM-based parameters.

Composition, structure and tensile biomechanical properties of equine articular cartilage during growth and maturation.

Articular cartilage undergoes structural and biochemical changes during maturation, but the knowledge on how these changes relate to articular cartilage function at different stages of maturation is lacking. Equine articular cartilage samples of four different maturation levels (newborn, 5-month-old, 11-month-old and adult) were collected (N = 25). Biomechanical tensile testing, Fourier transform infrared microspectroscopy (FTIR-MS) and polarized light microscopy were used to study the tensile, biochemical and structural properties of articular cartilage, respectively. The tensile modulus was highest and the breaking energy lowest in the newborn group. The collagen and the proteoglycan contents increased with age. The collagen orientation developed with age into an arcade-like orientation. The collagen content, proteoglycan content, and collagen orientation were important predictors of the tensile modulus (p < 0.05 in multivariable regression) and correlated significantly also with the breaking energy (p < 0.05 in multivariable regression). Partial least squares regression analysis of FTIR-MS data provided accurate predictions for the tensile modulus (r = 0.79) and the breaking energy (r = 0.65). To conclude, the composition and structure of equine articular cartilage undergoes changes with depth that alter functional properties during maturation, with the typical properties of mature tissue reached at the age of 5-11 months.

Imaging of Osteoarthritic Human Articular Cartilage using Fourier Transform Infrared Microspectroscopy Combined with Multivariate and Univariate Analysis.

The changes in chemical composition of human articular cartilage (AC) caused by osteoarthritis (OA) were investigated using Fourier transform infrared microspectroscopy (FTIR-MS). We demonstrate the sensitivity of FTIR-MS for monitoring compositional changes that occur with OA progression. Twenty-eight AC samples from tibial plateaus were imaged with FTIR-MS. Hyperspectral images of all samples were combined for K-means clustering. Partial least squares regression (PLSR) analysis was used to compare the spectra with the OARSI grade (histopathological grading of OA). Furthermore, the amide I and the carbohydrate regions were used to estimate collagen and proteoglycan contents, respectively. Spectral peak at 1338 cm(-1) was used to estimate the integrity of the collagen network. The layered structure of AC was revealed using the carbohydrate region for clustering. Statistically significant correlation was observed between the OARSI grade and the collagen integrity in the superficial (r = -0.55) and the deep (r = -0.41) zones. Furthermore, PLSR models predicted the OARSI grade from the superficial (r = 0.94) and the deep (r = 0.77) regions of the AC with high accuracy. Obtained results suggest that quantitative and qualitative changes occur in the AC composition during OA progression, and these can be monitored by the use of FTIR-MS.