Collagen distribution within articular cartilage (AC) is typically evaluated from histological sections, e.g., using collagen staining and light microscopy (LM). Unfortunately, all techniques based on histological sections are time-consuming, destructive, and without extraordinary effort, limited to two dimensions. This study investigates whether phosphotungstic acid (PTA) and phosphomolybdic acid (PMA), two collagen-specific markers and X-ray absorbers, could (1) produce contrast for AC X-ray imaging or (2) be used to detect collagen distribution within AC. We labeled equine AC samples with PTA or PMA and imaged them with micro-computed tomography (micro-CT) at pre-defined time points 0, 18, 36, 54, 72, 90, 180, 270 h during staining. The micro-CT image intensity was compared with collagen distributions obtained with a reference technique, i.e., Fourier-transform infrared imaging (FTIRI). The labeling time and contrast agent producing highest association (Pearson correlation, Bland-Altman analysis) between FTIRI collagen distribution and micro-CT -determined PTA distribution was selected for human AC. Both, PTA and PMA labeling permitted visualization of AC features using micro-CT in non-calcified cartilage. After labeling the samples for 36 h in PTA, the spatial distribution of X-ray attenuation correlated highly with the collagen distribution determined by FTIRI in both equine (mean ± S.D. of the Pearson correlation coefficients, r = 0.96 ± 0.03, n = 12) and human AC (r = 0.82 ± 0.15, n = 4). PTA-induced X-ray attenuation is a potential marker for non-destructive detection of AC collagen distributions in 3D. This approach opens new possibilities in development of non-destructive 3D histopathological techniques for characterization of OA.

Contrast-enhanced micro-computed tomography (CEμCT) with phosphotungstic acid (PTA) has shown potential for detecting collagen distribution of articular cartilage. However, the selectivity of the PTA staining to articular cartilage constituents remains to be elucidated. The aim of this study was to investigate the dependence of PTA for the collagen content in bovine articular cartilage. Adjacent bovine articular cartilage samples were treated with chondroitinase ABC and collagenase to degrade the proteoglycan and the collagen constituents in articular cartilage, respectively. Enzymatically degraded samples were compared to the untreated samples using CEμCT and reference methods, such as Fourier-transform infrared imaging. Decrease in the X-ray attenuation of PTA in articular cartilage and collagen content was observed in cartilage depth of 0–13% and deeper in tissue after collagen degradation. Increase in the X-ray attenuation of PTA was observed in the cartilage depth of 13–39% after proteoglycan degradation. The X-ray attenuation of PTA-labelled articular cartilage in CEμCT is associated mainly with collagen content but the proteoglycans have a minor effect on the X-ray attenuation of the PTA-labelled articular cartilage. In conclusion, the PTA labeling provides a feasible CEμCT method for 3D characterization of articular cartilage.

Histopathological grading of osteochondral (OC) tissue is widely used in osteoarthritis (OA) research, and it is relatively common in post-surgery in vitro diagnostics. However, relying on thin tissue section, this approach includes a number of limitations, such as: (1) destructiveness, (2) sample processing artefacts, (3) 2D section does not represent spatial 3D structure and composition of the tissue, and (4) the final outcome is subjective. To overcome these limitations, we recently developed a contrast-enhanced μCT (CEμCT) imaging technique to visualize the collagenous extracellular matrix (ECM) of articular cartilage (AC). In the present study, we demonstrate that histopathological scoring of OC tissue from CEμCT is feasible. Moreover, we establish a new, semi-quantitative OA μCT grading system for OC tissue. Pathological features were clearly visualized in AC and subchondral bone (SB) with μCT and verified with histology, as demonstrated with image atlases. Comparison of histopathological grades (OARSI or severity (0-3)) across the characterization approaches, CEμCT and histology, excellent (0.92, 95% CI = [0.84, 0.96], n = 30) or fair (0.50, 95% CI = [0.16, 0.74], n = 27) intra-class correlations (ICC), respectively. A new μCT grading system was successfully established which achieved an excellent cross-method (μCT vs histology) reader-to-reader intra-class correlation (0.78, 95% CI = [0.58, 0.89], n = 27). We demonstrated that histopathological information relevant to OA can reliably be obtained from CEμCT images. This new grading system could be used as a reference for 3D imaging and analysis techniques intended for volumetric evaluation of OA pathology in research and clinical applications.

Our aim is to establish methods for quantifying morphometric properties of calcified cartilage (CC) from micro-computed tomography (μCT). Furthermore, we evaluated the feasibility of these methods in investigating relationships between osteoarthritis (OA), tidemark surface morphology and open subchondral channels (OSCCs). Samples (n = 15) used in this study were harvested from human lateral tibial plateau (n = 8). Conventional roughness and parameters assessing local 3-dimensional (3D) surface variations were used to quantify the surface morphology of the CC. Subchondral channel properties (percentage, density, size) were also calculated. As a reference, histological sections were evaluated using Histopathological osteoarthritis grading (OARSI) and thickness of CC and subchondral bone (SCB) was quantified. OARSI grade correlated with a decrease in local 3D variations of the tidemark surface (amount of different surface patterns (rs = -0.600, P = 0.018), entropy of patterns (EP) (rs = -0.648, P = 0.018), homogeneity index (HI) (rs = 0.555, P = 0.032)) and tidemark roughness (TMR) (rs = -0.579, P = 0.024). Amount of different patterns (ADP) and EP associated with channel area fraction (CAF) (rp = 0.876, P < 0.0001; rp = 0.665, P = 0.007, respectively) and channel density (CD) (rp = 0.680, P = 0.011; rp = 0.582, P = 0.023, respectively). TMR was associated with CAF (rp = 0.926, P < 0.0001) and average channel size (rp = 0.574, P = 0.025). CC topography differed statistically significantly in early OA vs healthy samples. We introduced a μ-CT image method to quantify 3D CC topography and perforations through CC. CC topography was associated with OARSI grade and OSCC properties; this suggests that the established methods can detect topographical changes in tidemark and CC perforations associated with OA.

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). 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). 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). 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.

Contrast-enhanced micro-computed tomography (CEµCT) with cationic and anionic contrast agents reveals glycosaminoglycan (GAG) content and distribution in articular cartilage (AC). The advantage of using cationic stains (e.g. CA4+) compared to anionic stains (e.g. Hexabrix®), is that it distributes proportionally with GAGs, while anionic stain distribution in AC is inversely proportional to the GAG content. To date, studies using cationic stains have been conducted with sufficient resolution to study its distributions on the macro-scale, but with insufficient resolution to study its distributions on the micro-scale. Therefore, it is not known whether the cationic contrast agents accumulate in extra/pericellular matrix and if they interact with chondrocytes. The insufficient resolution has also prevented to answer the question whether CA4+ accumulation in chondrons could lead to an erroneous quantification of GAG distribution with low-resolution µCT setups. In this study, we use high-resolution µCT to investigate whether CA4+ accumulates in chondrocytes, and further, to determine whether it affects the low-resolution ex vivo µCT studies of CA4+ stained human AC with varying degree of osteoarthritis. Human osteochondral samples were immersed in three different concentrations of CA4+ (3 mgI/ml, 6mgI/ml, and 24 mgI/ml) and imaged with high-resolution µCT at several timepoints. Different uptake diffusion profiles of CA4+ were observed between the segmented chondrons and the rest of the tissue. While the X-ray -detected CA4+ concentration in chondrons was greater than in the rest of the AC, its contribution to the uptake into the whole tissue was negligible and in line with macro-scale GAG content detected from histology. The efficient uptake of CA4+ into chondrons and surrounding territorial matrix can be explained by the micro-scale distribution of GAG content. CA4+ uptake in chondrons occurred regardless of the progression stage of osteoarthritis in the samples and the relative difference between the interterritorial matrix and segmented chondron area was less than 4%. To conclude, our results suggest that GAG quantification with CEµCT is not affected by the chondron uptake of CA4+. This further confirms the use of CA4+ for macro-scale assessment of GAG throughout the AC, and highlight the capability of studying chondron properties in 3D at the micro scale.