Effects of Articular Cartilage Constituents on Phosphotungstic Acid Enhanced Micro-Computed Tomography

Contrast-enhanced micro-computed tomography (CE mu CT) 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 CE mu CT 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 CE mu CT 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 CE mu CT method for 3D characterization of articular cartilage.Peer reviewe

Fourier Transform Infrared Spectroscopic Imaging and Multivariate Regression for Prediction of Proteoglycan Content of Articular Cartilage

Fourier Transform Infrared (FT-IR) spectroscopic imaging has been earlier applied for the spatial estimation of the collagen and the proteoglycan (PG) contents of articular cartilage (AC). However, earlier studies have been limited to the use of univariate analysis techniques. Current analysis methods lack the needed specificity for collagen and PGs. The aim of the present study was to evaluate the suitability of partial least squares regression (PLSR) and principal component regression (PCR) methods for the analysis of the PG content of AC. Multivariate regression models were compared with earlier used univariate methods and tested with a sample material consisting of healthy and enzymatically degraded steer AC. Chondroitinase ABC enzyme was used to increase the variation in PG content levels as compared to intact AC. Digital densitometric measurements of Safranin O –stained sections provided the reference for PG content. The results showed that multivariate regression models predict PG content of AC significantly better than earlier used absorbance spectrum (i.e. the area of carbohydrate region with or without amide I normalization) or second derivative spectrum univariate parameters. Increased molecular specificity favours the use of multivariate regression models, but they require more knowledge of chemometric analysis and extended laboratory resources for gathering reference data for establishing the models. When true molecular specificity is required, the multivariate models should be used

3D morphometric analysis of calcified cartilage properties using micro-computed tomography

OBJECTIVE: Our aim is to establish methods for quantifying morphometric properties of calcified cartilage (CC) from micro-computed tomography (muCT). Furthermore, we evaluated the feasibility of these methods in investigating relationships between osteoarthritis (OA), tidemark surface morphology and open subchondral channels (OSCCs). METHOD: 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. RESULTS: 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. CONCLUSION: We introduced a mu-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

Vibrational spectroscopy of articular cartilage

Abstract Articular cartilage is a connective tissue that is located at the ends of long bones. Type II collagen, proteoglycans, water, and chondrocytes are the main constituents of articular cartilage. Osteoarthritis, the most common joint disease in the world, causes degenerative changes in articular cartilage tissue. Fourier transform infrared (FTIR), Raman, and near infrared (NIR) spectroscopic techniques offer versatile tools to assess biochemical composition and quality of articular cartilage. These vibrational spectroscopic techniques can be used to broaden our understanding about the compositional changes during osteoarthritis, and they also hold promise in disease diagnostics. In this article, the current literature of articular cartilage spectroscopic studies is reviewed

Bone density and texture from minimally post-processed knee radiographs in subjects with knee osteoarthritis

Abstract Plain radiography is the most common modality to assess the stage of osteoarthritis. Our aims were to assess the relationship of radiography-based bone density and texture between radiographs with minimal and clinical post-processing, and to compare the differences in bone characteristics between controls and subjects with knee osteoarthritis or medial tibial bone marrow lesions (BMLs). Tibial bone density and texture was evaluated from radiographs with both minimal and clinical post-processing in 109 subjects with and without osteoarthritis. Bone texture was evaluated using fractal signature analysis. Significant correlations (p &lt; 0.001) were found in all regions (between 0.94 and 0.97) for calibrated bone density between radiographs with minimal and clinical post-processing. Correlations varied between 0.51 and 0.97 (p &lt;0.001) for FDVer texture parameter and between −0.10 and 0.97 for FDHor. Bone density and texture were different (p &lt; 0.05) between controls and subjects with osteoarthritis or BMLs mainly in medial tibial regions. When classifying healthy and osteoarthritic subjects using a machine learning-based elastic net model with bone characteristics, area under the receiver operating characteristics (ROCAUC) curve was 0.77. For classifying controls and subjects with BMLs, ROCAUC was 0.85. In conclusion, differences in bone density and texture can be assessed from knee radiographs when using minimal post-processing

A novel method for automatic localization of joint area on knee plain radiographs

Abstract Osteoarthritis (OA) is a common musculoskeletal condition typically diagnosed from radiographic assessment after clinical examination. However, a visual evaluation made by a practitioner suffers from subjectivity and is highly dependent on the experience. Computer-aided diagnostics (CAD) could improve the objectivity of knee radiographic examination. The first essential step of knee OA CAD is to automatically localize the joint area. However, according to the literature this task itself remains challenging. The aim of this study was to develop novel and computationally efficient method to tackle the issue. Here, three different datasets of knee radiographs were used (n = 473/93/77) to validate the overall performance of the method. Our pipeline consists of two parts: anatomically-based joint area proposal and their evaluation using Histogram of Oriented Gradients and the pre-trained Support Vector Machine classifier scores. The obtained results for the used datasets show the mean intersection over the union equals to: 0.84, 0.79 and 0.78. Using a high-end computer, the method allows to automatically annotate conventional knee radiographs within 14–16 ms and high resolution ones within 170 ms. Our results demonstrate that the developed method is suitable for large-scale analyses

Quantitative Information From Ultrasound Evaluation of Articular Cartilage Should Be Interpreted With Care

Department of Health Technology and Informatic

Volumetric assessment of bone microstructures by a 3D local binary patterns -based method:bone changes with osteoarthritis

Abstract Osteoarthritis (OA) causes progressive degeneration of articular cartilage and pathological changes in subchondral bone, conventionally assessed volumetrically using micro-computed tomography (μCT) imaging in vitro. The local binary patterns (LBP) method has recently been suggested as a new alternative solution to perform analysis of local bone structures from μCT scans. In this study, a novel 3D LBP-based method to provide a new lead in bone microstructural analysis is proposed. In addition to the detailed description of the method, this solution is tested using µCT data of OA human trabecular bone samples, harvested from patients treated with total knee arthroplasty. The method was applied to correlate the distribution of orientations of local patterns with the severity of the disease. The local orientations of the bone fibers changed along the severity of OA, suggesting an adaptation of the bone to the disease. The structural parameters derived from the process were able to provide a new approach for the assessment of the disease, supporting the potential of this volumetric LBP-based method to assess trabecular bone changes

Ultrasound attenuation in normal and spontaneously degenerated articular cartilage

High-frequency ultrasound (US) measurements may provide means for the quantification of articular cartilage quality. Bovine patellar cartilage samples (n = 32) at various degenerative stages were studied using US attenuation measurements in the 5- to 9-MHz frequency range. The results were compared with the histologic, biochemical and mechanical parameters obtained for the same samples, to identify which structural or functional factors could be related to the attenuation and its variations. Attenuation, as calculated in the frequency or time domain, correlated significantly with the histologic tissue integrity (i.e., Mankin score, Spearman r = -0.576 or -0.571, p < 0.01), but the slope of attenuation vs. frequency was not related to Mankin score. Ultrasound speed was, however, the most sensitive indicator of Mankin score (r = -0.755, p < 0.01). Cartilage quality index (CQI), a combination of structural and functional parameters, correlated significantly with the attenuation or speed (r = -0.655 or -0.872, p < 0.01). Our results suggest that US attenuation and speed may be suited for the diagnostics of cartilage degeneration

Orientation anisotropy of quantitative MRI relaxation parameters in ordered tissue

Abstract In highly organized tissues, such as cartilage, tendons and white matter, several quantitative MRI parameters exhibit dependence on the orientation of the tissue constituents with respect to the main imaging magnetic field (B₀). In this study, we investigated the dependence of multiple relaxation parameters on the orientation of articular cartilage specimens in the B₀. Bovine patellar cartilage-bone samples (n = 4) were investigated ex vivo at 9.4 Tesla at seven different orientations, and the MRI results were compared with polarized light microscopy findings on specimen structure. Dependences of T₂ and continuous wave (CW)-T₁ᵨ relaxation times on cartilage orientation were confirmed. T₂ (and T₂*) had the highest sensitivity to orientation, followed by TRAFF2 and adiabatic T₂ᵨ. The highest dependence was seen in the highly organized deep cartilage and the smallest in the least organized transitional layer. Increasing spin-lock amplitude decreased the orientation dependence of CW-T1ρ. T₁ was found practically orientation-independent and was closely followed by adiabatic T₁ᵨ. The results suggest that T₁ and adiabatic T₁ᵨ should be preferred for orientation-independent quantitative assessment of organized tissues such as articular cartilage. On the other hand, based on the literature, parameters with higher orientation anisotropy appear to be more sensitive to degenerative changes in cartilage