Optical spectral reflectance of human articular cartilage - relationships with tissue structure, composition and mechanical properties

Fourier Transform Infrared Microspectroscopy Combined with Principal Component Analysis and Artificial Neural Networks for the Study of the Effect of β-Hydroxy-β-Methylbutyrate (HMB) Supplementation on Articular Cartilage

The potential of Fourier Transform infrared microspectroscopy (FTIR microspectroscopy) and multivariate analyses were applied for the classification of the frequency ranges responsible for the distribution changes of the main components of articular cartilage (AC) that occur during dietary β-hydroxy-β-methyl butyrate (HMB) supplementation. The FTIR imaging analysis of histological AC sections originating from 35-day old male piglets showed the change in the collagen and proteoglycan contents of the HMB-supplemented group compared to the control. The relative amount of collagen content in the superficial zone increased by more than 23% and in the middle zone by about 17%, while no changes in the deep zone were observed compared to the control group. Considering proteoglycans content, a significant increase was registered in the middle and deep zones, respectively; 62% and 52% compared to the control. AFM nanoindentation measurements collected from animals administered with HMB displayed an increase in AC tissue stiffness by detecting a higher value of Young’s modulus in all investigated AC zones. We demonstrated that principal component analysis and artificial neural networks could be trained with spectral information to distinguish AC histological sections and the group under study accurately. This work may support the use and effectiveness of FTIR imaging combined with multivariate analyses as a quantitative alternative to traditional collagenous tissue-related histology.

Spectroscopic photoacoustic imaging of cartilage damage

OBJECTIVE

Osteoarthritis (OA) is a chronic joint disease characterized by progressive degradation of cartilage. It affects more than 10% of the people aged over 60 years-old worldwide with a rising prevalence due to the increasingly aging population. OA is a major source of pain, disability, and socioeconomic cost. Currently, the lack of effective diagnosis and affordable imaging options for early detection and monitoring of OA presents the clinic with many challenges. Spectroscopic Photoacoustic (sPA) imaging has the potential to reveal changes in cartilage composition with different degrees of damage, based on optical absorption contrast.

DESIGN

In this study, the capabilities of sPA imaging and its potential to characterize cartilage damage were explored. To this end, 15 pieces of cartilage samples from patients undergoing a total joint replacement were collected and were imaged ex vivo with sPA imaging at a wide optical spectral range (between 500 nm and 1,300 nm) to investigate the photoacoustic properties of cartilage tissue. All the PA spectra of the cartilage samples were analyzed and compared to the corresponding histological results.

RESULTS

The collagen related PA spectral changes were clearly visible in our imaging data and were related to different degrees of cartilage damage. The results are in good agreement with histology and the current gold standard, i.e., the Mankin score.

CONCLUSIONS

This study demonstrates the potential and possible clinical application of sPA imaging in OA.

Ultraviolet light (365 nm) transmission properties of articular cartilage as a function of depth, extracellular matrix, and swelling

Current tissue engineering approaches for treatment of injured or diseased articular cartilage use ultraviolet light (UV) for in situ photopolymerization of biomaterials to fill chondral and osteochondral defects as well as resurfacing, stiffening and bonding the extracellular matrix and tissue interfaces. The most commonly used UV light wavelength is UVA 365 nm, the least cytotoxic and deepest penetrating. However, little information is available on the transmission of UVA 365 nm light through the cartilage matrix. In the present study, 365 nm UV light transmission was measured as a function of depth through 100 μm thick slices of healthy articular cartilage removed from mature bovine knees. Transmission properties were measured in normal (Native) cartilage and after swelling equilibration in phosphate-buffered saline (Swollen). Single-factor and multiple linear regression analyses were performed to determine depth-dependencies between the effective attenuation coefficients and proteoglycan, collagen and water contents. For both cartilages, a significant depth-dependency was found for the effective attenuation coefficients, being highest at the articular surface (superficial zone) and decreasing with depth. The effective attenuation coefficients for full-thickness cartilages were approximately a third lower than the total attenuation coefficients calculated from the individual slices. Analysis of absorption and scattering effects due to the ECM and chondrocytes found that UV light scatter coefficients were ∼10 times greater than absorption coefficients. The greater transmittance of UV light through the thicker cartilage was attributed to the collagen within the ECM causing significant backscatter forward reflectance.

Discrimination of healthy and osteoarthritic articular cartilage by Fourier transform infrared imaging and Fisher's discriminant analysis

Fourier transform infrared spectroscopic imaging (FTIRI) technique can be used to obtain the quantitative information of content and spatial distribution of principal components in cartilage by combining with chemometrics methods. In this study, FTIRI combining with principal component analysis (PCA) and Fisher's discriminant analysis (FDA) was applied to identify the healthy and osteoarthritic (OA) articular cartilage samples. Ten 10-μm thick sections of canine cartilages were imaged at 6.25μm/pixel in FTIRI. The infrared spectra extracted from the FTIR images were imported into SPSS software for PCA and FDA. Based on the PCA result of 2 principal components, the healthy and OA cartilage samples were effectively discriminated by the FDA with high accuracy of 94% for the initial samples (training set) and cross validation, as well as 86.67% for the prediction group. The study showed that cartilage degeneration became gradually weak with the increase of the depth. FTIRI combined with chemometrics may become an effective method for distinguishing healthy and OA cartilages in future.

Discrimination of healthy and osteoarthritic articular cartilages by Fourier transform infrared imaging and partial least squares-discriminant analysis

Fourier transform infrared imaging (FTIRI) combined with chemometrics algorithm has strong potential to obtain complex chemical information from biology tissues. FTIRI and partial least squares-discriminant analysis (PLS-DA) were used to differentiate healthy and osteoarthritic (OA) cartilages for the first time. A PLS model was built on the calibration matrix of spectra that was randomly selected from the FTIRI spectral datasets of healthy and lesioned cartilage. Leave-one-out cross-validation was performed in the PLS model, and the fitting coefficient between actual and predicted categorical values of the calibration matrix reached 0.95. In the calibration and prediction matrices, the successful identifying percentages of healthy and lesioned cartilage spectra were 100% and 90.24%, respectively. These results demonstrated that FTIRI combined with PLS-DA could provide a promising approach for the categorical identification of healthy and OA cartilage specimens.

The contribution of bone and cartilage to the near-infrared spectrum of osteochondral tissue

Near-infrared (NIR) spectroscopy has been used to assess hyaline cartilage quality in human and animal osteochondral tissues. However, due to the lack of NIR signal from bone phosphate and the relatively deep penetration depth of the radiation, the separate contributions of cartilage and bone to the spectral signatures have not been well defined. The objectives of the current study were (1) to improve the understanding of the contributions of bone and cartilage to NIR spectra acquired from osteochondral tissue and (2) to assess the ability of this nondestructive method to predict cartilage thickness and modified Mankin grade of human tibial plateau articular cartilage. Near-infrared spectra were acquired from samples of bovine bone and cartilage with varying thicknesses and from 22 tibial plateaus harvested from patients undergoing knee replacement surgery. The spectra were recorded from regions of the tibial plateaus with varying degrees of degradation, and the cartilage thickness and modified Mankin grade of these regions were assessed histologically. The spectra from bone and cartilage samples of known thicknesses were investigated to identify spectral regions that were distinct for these two tissues. Univariate and multivariate linear regression methods were used to correlate modified Mankin grade and cartilage thickness with NIR spectral changes. The ratio of the NIR absorbances associated with water at 5270 and 7085 cm(-1) was the best differentiator of cartilage and bone spectra. The NIR prediction models for thickness and Mankin grade calculated using partial least squares regression were more accurate than were univariate-based prediction models, with a root mean square errors of cross-validation of 0.42 mm (for thickness) and 1.3 (for modified Mankin grade). We conclude that NIR spectroscopy may be used to simultaneously assess articular cartilage thickness and modified Mankin grade, based in part on differences in spectral contributions from bone and cartilage.

Composite three-dimensional woven scaffolds with interpenetrating network hydrogels to create functional synthetic articular cartilage

The development of synthetic biomaterials that possess mechanical properties that mimic those of native tissues remains an important challenge to the field of materials. In particular, articular cartilage is a complex nonlinear, viscoelastic, and anisotropic material that exhibits a very low coefficient of friction, allowing it to withstand millions of cycles of joint loading over decades of wear. Here we show that a three-dimensionally woven fiber scaffold that is infiltrated with an interpenetrating network hydrogel can provide a functional biomaterial that provides the load-bearing and tribological properties of native cartilage. An interpenetrating dual-network "tough-gel" consisting of alginate and polyacrylamide was infused into a porous three-dimensionally woven poly(ε-caprolactone) fiber scaffold, providing a versatile fiber-reinforced composite structure as a potential acellular or cell-based replacement for cartilage repair.

Spectroscopic measurement of cartilage thickness in arthroscopy: ex vivo validation in human knee condyles

PURPOSE

To evaluate the accuracy of articular cartilage thickness measurement when implementing a new technology based on spectroscopic measurement into an arthroscopic camera.

METHODS

Cartilage thickness was studied by ex vivo arthroscopy at a number of sites (N = 113) in human knee joint osteoarthritic femoral condyles and tibial plateaus, removed from 7 patients undergoing total knee replacement. The arthroscopic image spectral data at each site were used to estimate cartilage thickness. Arthroscopically derived thickness values were compared with reference cartilage thickness as measured by 3 different methods: needle penetration, spiral computed tomography scanning, and geometric measurement after sample slicing.

RESULTS

The lowest mean error (0.28 to 0.30 mm) in the regression between arthroscopic and reference cartilage thickness was seen for reference cartilage thickness less than 1.5 mm. Corresponding values for cartilage thickness less than 2.0 and 2.5 mm were 0.32 to 0.40 mm and 0.37 to 0.47 mm, respectively. Cartilage thickness images--created by pixel-by-pixel regression model calculations applied to the arthroscopic images--were derived to demonstrate the clinical use of a camera implementation.

CONCLUSIONS

On the basis of this investigation on osteoarthritic material, when one is implementing the spectroscopic method for estimating cartilage thickness into an arthroscopic camera, errors in the range of 0.28 to 0.30 mm are expected. This implementation does not, however, influence the fact that the spectral method performs less well in the cartilage thickness region from 1.5 to 2.5 mm and cannot assess cartilage thicker than 2.5 mm.

CLINICAL RELEVANCE

Imaging cartilage thickness directly in the arthroscopic camera video stream could serve as an interesting image tool for in vivo cartilage quality assessment, in connection with cartilage diagnosis, repair, and follow-up.