Effects of optical beam angle on quantitative optical coherence tomography (OCT) in normal and surface degenerated bovine articular cartilage

2010-2011 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

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

Intravascular Ultrasound (IVUS): A Potential Arthroscopic Tool for Quantitative Assessment of Articular Cartilage

Conventional ultrasound examination of the articular cartilage performed externally on the body surface around the joint has limited accuracy due to the inadequacy in frequency used. In contrast to this, minimally invasive arthroscopy-based ultrasound with adequately high frequency may be a better alternative to assess the cartilage. Up to date, no special ultrasound transducer for imaging the cartilage in arthroscopic use has been designed. In this study, we introduced the intravascular ultrasound (IVUS) for this purpose. An IVUS system with a catheter-based probe (Ø ≈ 1mm) was used to measure the thickness and surface acoustical reflection of the bovine patellar articular cartilage in vitro before and after degeneration induced by enzyme treatments. Similar measurement was performed using another high frequency ultrasound system (Vevo) with a probe of much larger size and the results were compared between the two systems. The thickness measured using IVUS was highly correlated (r = 0.985, p < 0.001) with that obtained by Vevo. Thickness and surface reflection amplitude measured using IVUS on the enzymatically digested articular cartilage showed changes similar to those obtained by Vevo, which were expectedly consistent with previous investigations. IVUS can be potentially used for the quantitative assessment of articular cartilage, with its ready-to-use arthroscopic feature

Stress-relaxation of human patellar articular cartilage in unconfined compression: Prediction of mechanical response by tissue composition and structure.

Mechanical properties of articular cartilage are controlled by tissue composition and structure. Cartilage function is sensitively altered during tissue degeneration, in osteoarthritis (OA). However, mechanical properties of the tissue cannot be determined non-invasively. In the present study, we evaluate the feasibility to predict, without mechanical testing, the stress–relaxation response of human articular cartilage under unconfined compression. This is carried out by combining microscopic and biochemical analyses with composition-based mathematical modeling.Cartilage samples from five cadaver patellae were mechanically tested under unconfined compression. Depth-dependent collagen content and fibril orientation, as well as proteoglycan and water content were derived by combining Fourier transform infrared imaging, biochemical analyses and polarized light microscopy. Finite element models were constructed for each sample in unconfined compression geometry. First, composition-based fibril-reinforced poroviscoelastic swelling models, including composition and structure obtained from microscopical and biochemical analyses were fitted to experimental stress–relaxation responses of three samples. Subsequently, optimized values of model constants, as well as compositional and structural parameters were implemented in the models of two additional samples to validate the optimization.Theoretical stress–relaxation curves agreed with the experimental tests (R=0.95–0.99). Using the optimized values of mechanical parameters, as well as composition and structure of additional samples, we were able to predict their mechanical behavior in unconfined compression, without mechanical testing (R=0.98). Our results suggest that specific information on tissue composition and structure might enable assessment of cartilage mechanics without mechanical testing