Measurement of cartilage sub‐component distributions through the surface by Raman spectroscopy‐based multivariate analysis

Abstract

Articular cartilage posesses unique material properties due to a complex depth-dependent composition of sub-components. Raman spectroscopy has proven valuable in quantifying this composition through cartilage crosssections. However, cross-sectioning requires tissue destruction and is not practical in situ. In this work, Raman spectroscopybased multivariate curve resolution (MCR) was employed in porcine cartilage samples (n = 12) to measure collagen, glycosaminoglycan, and water distributions through the surface for the first time; these were compared against cross-section standards. Through the surface Raman measurements proved reliable in predicting composition distribution up to a depth of approximately 0.5 mm. A fructose-based optical clearing agent (OCA) was also used in an attempt to further improve depth of resolution of this measurement method. However, it did not; mainly due to a high-spectral overlap with the Raman spectra of main cartilage sub-components. This measurement technique potentially could be used in situ, to better understand the etiology of joint diseases such as osteoarthritis (OA). K E Y W O R D S articular cartilage, multivariate analysis, optical clearing, Raman spectroscopy 1 | INTRODUCTION Articular cartilage serves as the bearing surface for boneto-bone load transmission, and enables nearly frictionfree joint movement. [1] Fulfilling this role requires unique material properties that are derived from its complex composition and organization. Past studies using Raman spectroscopy have reported the relative distribution of this composition in vitro with cross-sectioning, [2,3] and related it to concentrations determined from assay tests. However, quantifying the composition with depth through the surface will keep morphology intact, and enable in situ measurements. This could offer better insight into how joint diseases such as osteoarthritis (OA) develop, especially in the early stages, and how composition affects functionality. Cartilage consists of a dense extracellular matrix (ECM) predominantly made up of collagens, proteoglycans, and water as well as other proteins and molecules in lower concentrations. [1,4] Recently, tools such as Raman spectroscopy have proven capable of not only quantifying these sub-component concentrations, but also observing subtle variations in their structural organization. [5,6]

Characterization of Degraded Cartilage Using Confocal Raman Microscopy

“…Indeed, subtle molecular changes often cause detectable vibrational changes that can be detected by Raman analysis. In recent studies, Raman has been used either to more accurately quantify the distribution of cartilage subcomponents over its entire surface [25] or in some situations to establish the difference between different regions of the tissue over its entire depth the tissue surface [26].…”

Raman spectroscopy–based water measurements identify the origin of MRI T2 signal in human articular cartilage zones and predict histopathologic score

“…Because visual arthroscopic evaluation is highly subjective approach to assess cartilage degeneration, RS-based hydration status assessment may improve such clinical evaluation in near future. In fact, in a recent study, Mason et al [52] reported that it is possible to predict cartilage subcomponent distributions up to a depth of approximately 0.5 mm using multivariate curve resolution analysis of Raman spectra at "fingerprint region" (800-1800 cm À1 ) collected through the cartilage surface. This method could be also implemented for the high-wavenumber region to improve the sensitivity of water content measurement in the deeper zonal region of articular cartilage when the spectra are collected through the articular surface.…”

Vibrational Spectroscopy in Assessment of Early Osteoarthritis—A Narrative Review

“…The main components of articular cartilage are GAG and collagen [ 123 ], and changes in them can be used as indicators for the early diagnosis of OA. Mason et al [ 125 ] used Raman multivariate curve resolution (MCR) to analyze the cartilage surface, and their results showed that Raman MCR could accurately quantify the cartilage subcomponent distribution on the entire surface, with a depth of up to 0.5 mm. Jensen et al [ 126 ] collected Raman spectra from the cartilage tissue model and found that there were slight differences in the spectra of different tissue regions, which represented the orientation of collagen fibers, proving that polarized Raman spectroscopy can distinguish between collagen fiber orientations in the cartilage explant model system.…”