In this study, we established how the depth of penetration into cartilage varies throughout the NIR frequency range (4000–10 000 cm ⁻¹ ).

Advances in vibrational spectroscopy have propelled new insights into the molecular composition and structure of biological tissues. In this review, we discuss common modalities and techniques of vibrational spectroscopy, and present key examples to illustrate how they have been applied to enrich the assessment of connective tissues. In particular, we focus on applications of Fourier transform infrared (FTIR), near infrared (NIR) and Raman spectroscopy to assess cartilage and bone properties. We present strengths and limitations of each approach and discuss how the combination of spectrometers with microscopes (hyperspectral imaging) and fiber optic probes have greatly advanced their biomedical applications. We show how these modalities may be used to evaluate virtually any type of sample (ex vivo, in situ or in vivo) and how “spectral fingerprints” can be interpreted to quantify outcomes related to tissue composition and quality. We highlight the unparalleled advantage of vibrational spectroscopy as a label-free and often nondestructive approach to assess properties of the extracellular matrix (ECM) associated with normal, developing, aging, pathological and treated tissues. We believe this review will assist readers not only in better understanding applications of FTIR, NIR and Raman spectroscopy, but also in implementing these approaches for their own research projects.

Changes in the composition of the extracellular matrix (ECM) are characteristic of injury or disease in cartilage tissue. Various imaging modalities and biochemical techniques have been used to assess the changes in cartilage tissue but lack adequate sensitivity, or in the case of biochemical techniques, result in destruction of the sample. Fourier transform near infrared (FT-NIR) spectroscopy has shown promise for the study of cartilage composition. In the current study NIR spectroscopy was used to identify the contributions of individual components of cartilage in the NIR spectra by assessment of the major cartilage components, collagen and chondroitin sulfate, in pure component mixtures. The NIR spectra were obtained using homogenous pellets made by dilution with potassium bromide. A partial least squares (PLS) model was calculated to predict composition in bovine cartilage samples. Characteristic absorbance peaks between 4000 and 5000 cm(-1) could be attributed to components of cartilage, i.e. collagen and chondroitin sulfate. Prediction of the amount of collagen and chondroitin sulfate in tissues was possible within 8% (w/dw) of values obtained by gold standard biochemical assessment. These results support the use of NIR spectroscopy for in vitro and in vivo applications to assess matrix composition of cartilage tissues, especially when tissue destruction should be avoided.

Noninvasive assessment of engineered cartilage properties would enable better control of the developing tissue towards the desired structural and compositional endpoints through optimization of the biochemical environment in real time. The objective of this study is to assess the matrix constituents of cartilage using near-infrared spectroscopy (NIRS), a technique that permits full-depth assessment of developing engineered tissue constructs. Mid-infrared (mid-IR) and NIR data were acquired from full-thickness cartilage constructs that were grown up to 4 weeks with and without mechanical stimulation. Correlations were assessed between established mid-IR peak areas that reflect the relative amount of collagen (amide I, amide II, and 1338 cm⁻¹) and proteoglycan (PG), (850 cm⁻¹), and the integrated area of the NIR water absorbance at 5190 cm⁻¹. This analysis was performed to evaluate whether simple assessment of the NIR water absorbance could yield information about matrix development. It was found that an increase in the mid-IR PG absorbance at 850 cm⁻¹ correlated with the area of the NIR water peak (Spearman's rho = 0.95, p < 0.0001). In the second analysis, a partial least squares method (PLS1) was used to assess whether an extended NIR spectral range (5400–3800 cm⁻¹) could be utilized to predict collagen and proteoglycan content of the constructs based on mid-IR absorbances. A subset of spectra was randomly selected as an independent prediction set in this analysis. Average of the normalized root mean square errors of prediction of first-derivative NIR spectral models were 7% for 850 cm⁻¹ (PG), 11% for 1338 cm⁻¹ (collagen), 8% for amide II (collagen), and 8% for amide I (collagen). These results demonstrate the ability of NIRS to monitor macromolecular content of cartilage constructs and is the first step towards employing NIR to assess engineered cartilage in situ.