Clinical outcome of autologous chondrocyte implantation is correlated with infrared spectroscopic imaging-derived parameters

Characterisation of Cartilage Damage via Fusing Mid-Infrared, Near-Infrared, and Raman Spectroscopic Data

Mid-infrared spectroscopy (MIR), near-infrared spectroscopy (NIR), and Raman spectroscopy are all well-established analytical techniques in biomedical applications. Since they provide complementary chemical information, we aimed to determine whether combining them amplifies their strengths and mitigates their weaknesses. This study investigates the feasibility of the fusion of MIR, NIR, and Raman spectroscopic data for characterising articular cartilage integrity. Osteochondral specimens from bovine patellae were subjected to mechanical and enzymatic damage, and then MIR, NIR, and Raman data were acquired from the damaged and control specimens. We assessed the capacity of individual spectroscopic methods to classify the samples into damage or control groups using Partial Least Squares Discriminant Analysis (PLS-DA). Multi-block PLS-DA was carried out to assess the potential of data fusion by combining the dataset by applying two-block (MIR and NIR, MIR and Raman, NIR and Raman) and three-block approaches (MIR, NIR, and Raman). The results of the one-block models show a higher classification accuracy for NIR (93%) and MIR (92%) than for Raman (76%) spectroscopy. In contrast, we observed the highest classification efficiency of 94% and 93% for the two-block (MIR and NIR) and three-block models, respectively. The detailed correlative analysis of the spectral features contributing to the discrimination in the three-block models adds considerably more insight into the molecular origin of cartilage damage.

Near infrared spectroscopic assessment of developing engineered tissues: correlations with compositional and mechanical properties

Articular cartilage degeneration causes pain and reduces the mobility of millions of people annually. Regeneration of cartilage is challenging, due in part to its avascular nature, and thus tissue engineering approaches for cartilage repair have been studied extensively. Current techniques to assess the composition and integrity of engineered tissues, including histology, biochemical evaluation, and mechanical testing, are destructive, which limits real-time monitoring of engineered cartilage tissue development in vitro and in vivo. Near infrared spectroscopy (NIRS) has been proposed as a non-destructive technique to characterize cartilage. In the current study, we describe a non-destructive NIRS approach for assessment of engineered cartilage during development, and demonstrate correlation of these data to gold standard mid infrared spectroscopic measurements, and to mechanical properties of constructs. Cartilage constructs were generated using bovine chondrocyte culture on polyglycolic acid (PGA) scaffolds for six weeks. BMP-4 growth factor and ultrasound mechanical stimulation were used to provide a greater dynamic range of tissue properties and outcome variables. NIR spectra were collected daily using an infrared fiber optic probe in diffuse reflectance mode. Constructs were harvested after three and six weeks of culture and evaluated by the correlative modalities of mid infrared (MIR) spectroscopy, histology, and mechanical testing (equilibrium and dynamic stiffness). We found that specific NIR spectral absorbances correlated with MIR measurements of chemical composition, including relative amount of PGA (R = 0.86, p = 0.02), collagen (R = 0.88, p = 0.03), and proteoglycan (R = 0.83, p = 0.01). In addition, NIR-derived water content correlated with MIR-derived proteoglycan content (R = 0.76, p = 0.04). Both equilibrium and dynamic mechanical properties generally improved with cartilage growth from three to six weeks. In addition, significant correlations between NIRS-derived parameters and mechanical properties were found for constructs that were not treated with ultrasound (PGA (R = 0.71, p = 0.01), water (R = 0.74, p = 0.02), collagen (R = 0.69, p = 0.04), and proteoglycan (R = 0.62, p = 0.05)). These results lay the groundwork for extension to arthroscopic engineered cartilage assessment in clinical studies.

Spatial correlation of native and engineered cartilage components at micron resolution

Tissue engineering (TE) approaches are being widely investigated for repair of focal defects in articular cartilage. However, the amount and/or type of extracellular matrix (ECM) produced in engineered constructs does not always correlate with the resultant mechanical properties. This could be related to the specifics of ECM distribution throughout the construct. Here, we present data on the amount and distribution of the primary components of native and engineered cartilage (i.e., collagen, proteoglycan (PG), and water) using Fourier transform infrared imaging spectroscopy (FT-IRIS). These data permit visualization of matrix and water at 25 μm resolution throughout the tissues, and subsequent colocalization of these components using image processing methods. Native and engineered cartilage were cryosectioned at 80 μm for evaluation by FT-IRIS in the mid-infrared (MIR) and near-infrared (NIR) regions. PG distribution correlated strongly with water in native and engineered cartilage, supporting the binding of water to PG in both tissues. In addition, NIR-derived matrix peaks correlated significantly with MIR-derived collagen peaks, confirming the interpretation that these absorbances arise primarily from collagen and not PG. The combined use of MIR and NIR permits assessment of ECM and water spatial distribution at the micron level, which may aid in improved development of TE techniques.

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.

A case study: Glycosaminoglycan profiles of autologous chondrocyte implantation (ACI) tissue improve as the tissue matures

BACKGROUND

Autologous chondrocyte implantation (ACI) has been used to treat cartilage defects in thousands of patients worldwide with good clinical effectiveness 10-20years after implantation. Information concerning the quality of the repair cartilage is still limited because biopsies are small and rare. Glycosaminoglycan structure influences physiological function and is likely to be important in the long term stability of the repair tissue. The aim of this study was to assess glycosaminoglycans in ACI tissue over a two year period.

METHODS

Biopsies were taken from one patient (25years old) at 12months and 20months post-ACI-treatment and from three normal cadavers (21, 22 and 25years old). Fluorophore-assisted carbohydrate electrophoresis (FACE) was used to quantitatively assess the individual glycosaminoglycans.

RESULTS

At 12months the ACI biopsy had 40% less hyaluronan than the age-matched cadaveric biopsies but by 20months the ACI biopsy had the same amount of hyaluronan as the controls. Both the 12 and 20month ACI biopsies had less chondroitin sulphate disaccharides and shorter chondroitin sulphate chains than the age-matched cadaveric biopsies. However, chondroitin sulphate chain length doubled as the ACI repair tissue matured at 12months (3913Da±464) and 20months (6923Da±711) and there was less keratan sulphate as compared to the controls.

CONCLUSIONS

Although the glycosaminoglycan composition of the repair tissue is not identical to mature articular cartilage its quality continues to improve with time.

Early Alterations in Bone Characteristics of Type I Diabetic Rat Femur: A Fourier Transform Infrared (FT-IR) Imaging Study

Alterations in microstructure and mineral features can affect the mechanical and chemical properties of bones and their capacity to resist mechanical forces. Controversial results on diabetic bone mineral content have been reported and little is known about the structural alterations in collagen, maturation of apatite crystals, and carbonate content in diabetic bone. This current study is the first to report the mineral and organic properties of cortical, trabecular, and growth plate regions of diabetic rat femurs using Fourier transform infrared (FT-IR) microspectroscopy and the Vickers microhardness test. Femurs of type I diabetic rats were embedded into polymethylmethacrylate blocks, which were used for FT-IR imaging and microhardness studies. A lower mineral content and microhardness, a higher carbonate content especially labile type carbonate content, and an increase in size and maturation of hydroxyapatite crystals were observed in diabetic femurs, which indicate that diabetes has detrimental effects on bone just like osteoporosis. There was a decrease in the level of collagen maturity in diabetic femurs, implying a decrease in bone collagen quality that may contribute to the decrease in tensile strength and bone fragility. Taken together, the findings revealed alterations in structure and composition of mineral and matrix components, and an altered quality and mechanical strength of rat femurs in an early stage of type I diabetes. The results contribute to the knowledge of structure-function relationship of mineral and matrix components in diabetic bone disorder and can further be used for diagnostic or therapeutic purposes.

Investigation of intervertebral disc degeneration using multivariate FTIR spectroscopic imaging

Traditionally tissue samples are analysed using protein or enzyme specific stains on serial sections to build up a picture of the distribution of components contained within them. In this study we investigated the potential of multivariate curve resolution-alternating least squares (MCR-ALS) to deconvolute 2nd derivative spectra of Fourier transform infrared (FTIR) microscopic images measured in transflectance mode of goat and human paraffin embedded intervertebral disc (IVD) tissue sections, to see if this methodology can provide analogous information to that provided by immunohistochemical stains and bioassays but from a single section. MCR-ALS analysis of non-degenerate and enzymatically in vivo degenerated goat IVDs reveals five matrix components displaying distribution maps matching histological stains for collagen, elastin and proteoglycan (PG), as well as immunohistochemical stains for collagen type I and II. Interestingly, two components exhibiting characteristic spectral and distribution profiles of proteoglycans were found, and relative component/tissue maps of these components (labelled PG1 and PG2) showed distinct distributions in non-degenerate versus mildly degenerate goat samples. MCR-ALS analysis of human IVD sections resulted in comparable spectral profiles to those observed in the goat samples, highlighting the inter species transferability of the presented methodology. Multivariate FTIR image analysis of a set of 43 goat IVD sections allowed the extraction of semi-quantitative information from component/tissue gradients taken across the IVD width of collagen type I, collagen type II, PG1 and PG2. Regional component/tissue parameters were calculated and significant correlations were found between histological grades of degeneration and PG parameters (PG1: p = 0.0003, PG2: p < 0.0001); glycosaminoglycan (GAG) content and PGs (PG1: p = 0.0055, PG2: p = 0.0001); and MRI T2* measurements and PGs (PG1: p = 0.0021, PG2: p < 0.0001). Additionally, component/tissue parameters for collagen type I and II showed significant correlations with total collagen content (p = 0.0204, p = 0.0127). In conclusion, the presented findings illustrate, that the described multivariate FTIR imaging approach affords the necessary chemical specificity to be considered an important tool in the study of IVD degeneration in goat and human IVDs.

Nondestructive Assessment of Engineered Cartilage Composition by Near Infrared Spectroscopy

Tissue engineering presents a strategy to overcome the limitations of current tissue healing methods. Scaffolds, cells, external growth factors and mechanical input are combined in an effort to obtain constructs with properties that mimic native tissues. However, engineered constructs developed using similar culture environments can have very different matrix composition and biomechanical properties. Accordingly, a nondestructive technique to assess constructs during development such that appropriate compositional endpoints can be defined is desirable. Near infrared spectroscopy (NIRS) analysis is a modality being investigated to address the challenges associated with current evaluation techniques, which includes nondestructive compositional assessment. In the present study, cartilage tissue constructs were grown using chondrocytes seeded onto polyglycolic acid (PGA) scaffolds in similar environments in three separate tissue culture experiments and monitored using NIRS. Multivariate partial least squares (PLS) analysis models of NIR spectra were calculated and used to predict tissue composition, with biochemical assay information used as the reference data. Results showed that for combined data from all tissue culture experiments, PLS models were able to assess composition with significant correlations to reference values, including engineered cartilage water (at 5200 cm(-1), R = 0.68, p = 0.03), proteoglycan (at 4310 cm(-1), R = 0.82, p = 0.007), and collagen (at 4610 cm(-1), R = 0.84, p = 0.005). In addition, degradation of PGA was monitored using specific NIRS frequencies. These results demonstrate that NIR spectroscopy combined with multivariate analysis provides a nondestructive modality to assess engineered cartilage, which could provide information to determine the optimal time for tissue harvest for clinical applications.

Monitoring the Progression of Spontaneous Articular Cartilage Healing with Infrared Spectroscopy

OBJECTIVE

Evaluation of early compositional changes in healing articular cartilage is critical for understanding tissue repair and for therapeutic decision-making. Fourier transform infrared imaging spectroscopy (FT-IRIS) can be used to assess the molecular composition of harvested repair tissue. Furthermore, use of an infrared fiber-optic probe (IFOP) has the potential for translation to a clinical setting to provide molecular information in situ. In the current study, we determined the feasibility of IFOP assessment of cartilage repair tissue in a rabbit model, and assessed correlations with gold-standard histology.

DESIGN

Bilateral osteochondral defects were generated in mature white New Zealand rabbits, and IFOP data obtained from defect and adjacent regions at 2, 4, 6, 8, 12, and 16 weeks postsurgery. Tissues were assessed histologically using the modified O'Driscoll score, by FT-IRIS, and by partial least squares (PLS) modeling of IFOP spectra.

RESULTS

The FT-IRIS parameters of collagen content, proteoglycan content, and collagen index correlated significantly with modified O'Driscoll score (P = 0.05, 0.002, and 0.02, respectively), indicative of their sensitivity to tissue healing. Repair tissue IFOP spectra were distinguished from normal tissue IFOP spectra in all samples by PLS analysis. However, the PLS model for prediction of histological score had a high prediction error, which was attributed to the spectral information being acquired from the tissue surface only.

CONCLUSION

The strong correlations between FT-IRIS data and histological score support further development of the IFOP technique for clinical applications, although further studies to optimize data collection from the full sample depths are required.

Primary murine growth plate and articular chondrocyte isolation and cell culture

The ability to isolate primary chondrocytes from wild-type and genetically altered mice has provided tremendous advances in the understanding of signaling networks that regulate chondrocytes in health and disease. Isolation of chondrocytes from both growth plate tissues and articular cartilage has been challenging due to the cells being embedded within a highly organized tissue matrix. Here we describe highly reproducible methods for the isolation of pure populations of growth plate chondrocytes from the murine sternum and ribs and articular chondrocytes from the knee joint.

FTIR-I compositional mapping of the cartilage-to-bone interface as a function of tissue region and age

Soft tissue-to-bone transitions, such as the osteochondral interface, are complex junctions that connect multiple tissue types and are critical for musculoskeletal function. The osteochondral interface enables pressurization of articular cartilage, facilitates load transfer between cartilage and bone, and serves as a barrier between these two distinct tissues. Presently, there is a lack of quantitative understanding of the matrix and mineral distribution across this multitissue transition. Moreover, age-related changes at the interface with the onset of skeletal maturity are also not well understood. Therefore, the objective of this study is to characterize the cartilage-to-bone transition as a function of age, using Fourier transform infrared spectroscopic imaging (FTIR-I) analysis to map region-dependent changes in collagen, proteoglycan, and mineral distribution, as well as collagen organization. Both tissue-dependent and age-related changes were observed, underscoring the role of postnatal physiological loading in matrix remodeling. It was observed that the relative collagen content increased continuously from cartilage to bone, whereas proteoglycan peaked within the deep zone of cartilage. With age, collagen content across the interface increased, accompanied by a higher degree of collagen alignment in both the surface and deep zone cartilage. Interestingly, regardless of age, mineral content increased exponentially across the calcified cartilage interface. These observations reveal new insights into both region- and age-dependent changes across the cartilage-to-bone junction and will serve as critical benchmark parameters for current efforts in integrative cartilage repair.

Characterization of the cells in repair tissue following autologous chondrocyte implantation in mankind: a novel report of two cases

AIM

Autologous chondrocyte implantation (ACI) is used worldwide for the treatment of cartilage defects. This study has aimed to assess for the first time the cells that are contained within human ACI repair tissues several years post-treatment. We have compared the phenotypic properties of cells from within the ACI repair with adjacent chondrocytes and subchondral bone-derived mesenchymal stromal/stem cells (MSCs).

MATERIALS & METHODS

Two patients undergoing arthroplasty of their ACI-treated joint were investigated. Tissue and cells were isolated from the repair site, adjacent macroscopically normal cartilage and MSCs from the subchondral bone were characterized for their growth kinetics, morphology, immunoprofile and differentiation capacity.

RESULTS

ACI repair tissue appeared fibrocartilaginous, and ACI repair cells were heterogeneous in morphology and size when freshly isolated, becoming more homogeneous, resembling chondrocytes from adjacent cartilage, after culture expansion. The same weight of ACI repair tissue resulted in less cells than macroscopically normal cartilage. During expansion, ACI repair cells proliferated faster than MSCs but slower than chondrocytes. ACI repair cell immunoprofiles resembled chondrocytes, but their differentiation capacity matched MSCs.

CONCLUSION

This novel report demonstrates that human ACI repair cell phenotypes resemble both chondrocytes and MSCs but at different stages of their isolation and expansion in vitro.

Optimal variable selection for Fourier transform infrared spectroscopic analysis of articular cartilage composition

Articular cartilage (AC) is mainly composed of collagen, proteoglycans, chondrocytes, and water. These constituents are inhomogeneously distributed to provide unique biomechanical properties to the tissue. Characterization of the spatial distribution of these components in AC is important for understanding the function of the tissue and progress of osteoarthritis. Fourier transform infrared (FT-IR) absorption spectra exhibit detailed information about the biochemical composition of AC. However, highly specific FT-IR analysis for collagen and proteoglycans is challenging. In this study, a chemometric approach to predict the biochemical composition of AC from the FT-IR spectra was investigated. Partial least squares (PLS) regression was used to predict the proteoglycan content (n=32) and collagen content (n=28) of bovine cartilage samples from their average FT-IR spectra. The optimal variables for the PLS regression models were selected by using backward interval partial least squares and genetic algorithm. The linear correlation coefficients between the biochemical reference and predicted values of proteoglycan and collagen contents were r=0.923 (p<0.001) and r=0.896 (p<0.001), respectively. The results of the study show that variable selection algorithms can significantly improve the PLS regression models when the biochemical composition of AC is predicted.

Fourier transform infrared imaging and infrared fiber optic probe spectroscopy identify collagen type in connective tissues

Hyaline cartilage and mechanically inferior fibrocartilage consisting of mixed collagen types are frequently found together in repairing articular cartilage. The present study seeks to develop methodology to identify collagen type and other tissue components using Fourier transform infrared (FTIR) spectral evaluation of matrix composition in combination with multivariate analyses. FTIR spectra of the primary molecular components of repair cartilage, types I and II collagen, and aggrecan, were used to develop multivariate spectral models for discrimination of the matrix components of the tissues of interest. Infrared imaging data were collected from bovine bone, tendon, normal cartilage, meniscus and human repair cartilage tissues, and composition predicted using partial least squares analyses. Histology and immunohistochemistry results were used as standards for validation. Infrared fiber optic probe spectral data were also obtained from meniscus (a tissue with mixed collagen types) to evaluate the potential of this method for identification of collagen type in a minimally-invasive clinical application. Concentration profiles of the tissue components obtained from multivariate analysis were in excellent agreement with histology and immunohistochemistry results. Bone and tendon showed a uniform distribution of predominantly type I collagen through the tissue. Normal cartilage showed a distribution of type II collagen and proteoglycan similar to the known composition, while in repair cartilage, the spectral distribution of both types I and II collagen were similar to that observed via immunohistochemistry. Using the probe, the outer and inner regions of the meniscus were shown to be primarily composed of type I and II collagen, respectively, in accordance with immunohistochemistry data. In summary, multivariate analysis of infrared spectra can indeed be used to differentiate collagen type I and type II, even in the presence of proteoglycan, in connective tissues, using both imaging and fiber optic methodology. This has great potential for clinical in situ applications for monitoring tissue repair.

Infrared fiber optic probe evaluation of degenerative cartilage correlates to histological grading

BACKGROUND

Osteoarthritis (OA), a degenerative cartilage disease, results in alterations of the chemical and structural properties of tissue. Arthroscopic evaluation of full-depth tissue composition is limited and would require tissue harvesting, which is inappropriate in daily routine. Fourier transform infrared (FT-IR) spectroscopy is a modality based on molecular vibrations of matrix components that can be used in conjunction with fiber optics to acquire quantitative compositional data from the cartilage matrix.

PURPOSE

To develop a model based on infrared spectra of articular cartilage to predict the histological Mankin score as an indicator of tissue quality.

STUDY DESIGN

Comparative laboratory study.

METHODS

Infrared fiber optic probe (IFOP) spectra were collected from nearly normal and more degraded regions of tibial plateau articular cartilage harvested during knee arthroplasty (N = 61). Each region was graded using a modified Mankin score. A multivariate partial least squares algorithm using second-derivative spectra was developed to predict the histological modified Mankin score.

RESULTS

The partial least squares model derived from IFOP spectra predicted the modified Mankin score with a prediction error of approximately 1.4, which resulted in approximately 72% of the Mankin-scored tissues being predicted correctly and 96% being predicted within 1 grade of their true score.

CONCLUSION

These data demonstrate that IFOP spectral parameters correlate with histological tissue grade and can be used to provide information on tissue composition.

CLINICAL RELEVANCE

Infrared fiber optic probe studies have significant potential for the evaluation of cartilage tissue quality without the need for tissue harvest. Combined with arthroscopy, IFOP analysis could facilitate the definition of tissue margins in debridement procedures.