Near infrared spectroscopic imaging assessment of cartilage composition: Validation with mid infrared imaging spectroscopy

Spatial analysis of the osteoarthritis microenvironment: techniques, insights, and applications

Osteoarthritis (OA) is a debilitating degenerative disease affecting multiple joint tissues, including cartilage, bone, synovium, and adipose tissues. OA presents diverse clinical phenotypes and distinct molecular endotypes, including inflammatory, metabolic, mechanical, genetic, and synovial variants. Consequently, innovative technologies are needed to support the development of effective diagnostic and precision therapeutic approaches. Traditional analysis of bulk OA tissue extracts has limitations due to technical constraints, causing challenges in the differentiation between various physiological and pathological phenotypes in joint tissues. This issue has led to standardization difficulties and hindered the success of clinical trials. Gaining insights into the spatial variations of the cellular and molecular structures in OA tissues, encompassing DNA, RNA, metabolites, and proteins, as well as their chemical properties, elemental composition, and mechanical attributes, can contribute to a more comprehensive understanding of the disease subtypes. Spatially resolved biology enables biologists to investigate cells within the context of their tissue microenvironment, providing a more holistic view of cellular function. Recent advances in innovative spatial biology techniques now allow intact tissue sections to be examined using various -omics lenses, such as genomics, transcriptomics, proteomics, and metabolomics, with spatial data. This fusion of approaches provides researchers with critical insights into the molecular composition and functions of the cells and tissues at precise spatial coordinates. Furthermore, advanced imaging techniques, including high-resolution microscopy, hyperspectral imaging, and mass spectrometry imaging, enable the visualization and analysis of the spatial distribution of biomolecules, cells, and tissues. Linking these molecular imaging outputs to conventional tissue histology can facilitate a more comprehensive characterization of disease phenotypes. This review summarizes the recent advancements in the molecular imaging modalities and methodologies for in-depth spatial analysis. It explores their applications, challenges, and potential opportunities in the field of OA. Additionally, this review provides a perspective on the potential research directions for these contemporary approaches that can meet the requirements of clinical diagnoses and the establishment of therapeutic targets for OA.

Raman needle arthroscopy for in vivo molecular assessment of cartilage

The development of treatments for osteoarthritis (OA) is burdened by the lack of standardized biomarkers of cartilage health that can be applied in clinical trials. We present a novel arthroscopic Raman probe that can "optically biopsy" cartilage and quantify key extracellular matrix (ECM) biomarkers for determining cartilage composition, structure, and material properties in health and disease. Technological and analytical innovations to optimize Raman analysis include (1) multivariate decomposition of cartilage Raman spectra into ECM-constituent-specific biomarkers (glycosaminoglycan [GAG], collagen [COL], water [H₂ O] scores), and (2) multiplexed polarized Raman spectroscopy to quantify superficial zone (SZ) COL anisotropy via a partial least squares-discriminant analysis-derived Raman collagen alignment factor (RCAF). Raman measurements were performed on a series of ex vivo cartilage models: (1) chemically GAG-depleted bovine cartilage explants (n = 40), (2) mechanically abraded bovine cartilage explants (n = 30), (3) aging human cartilage explants (n = 14), and (4) anatomical-site-varied ovine osteochondral explants (n = 6). Derived Raman GAG score biomarkers predicted 95%, 66%, and 96% of the variation in GAG content of GAG-depleted bovine explants, human explants, and ovine explants, respectively (p < 0.001). RCAF values were significantly different for explants with abrasion-induced SZ COL loss (p < 0.001). The multivariate linear regression of Raman-derived ECM biomarkers (GAG and H₂ O scores) predicted 94% of the variation in elastic modulus of ovine explants (p < 0.001). Finally, we demonstrated the first in vivo Raman arthroscopy assessment of an ovine femoral condyle through intraarticular entry into the synovial capsule. This study advances Raman arthroscopy toward a transformative low-cost, minimally invasive diagnostic platform for objective monitoring of treatment outcomes from emerging OA therapies.

Nondestructive assessment of tissue engineered cartilage based on biochemical markers in cell culture media: application of attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy

ATR spectral data obtained from cell culture medium discards can be used to assess glucose and lactate content, which are shown here to be a surrogate for matrix development in tissue engineered cartilage.

Vibrational Spectroscopy in Assessment of Early Osteoarthritis-A Narrative Review

Osteoarthritis (OA) is a degenerative disease, and there is currently no effective medicine to cure it. Early prevention and treatment can effectively reduce the pain of OA patients and save costs. Therefore, it is necessary to diagnose OA at an early stage. There are various diagnostic methods for OA, but the methods applied to early diagnosis are limited. Ordinary optical diagnosis is confined to the surface, while laboratory tests, such as rheumatoid factor inspection and physical arthritis checks, are too trivial or time-consuming. Evidently, there is an urgent need to develop a rapid nondestructive detection method for the early diagnosis of OA. Vibrational spectroscopy is a rapid and nondestructive technique that has attracted much attention. In this review, near-infrared (NIR), infrared, (IR) and Raman spectroscopy were introduced to show their potential in early OA diagnosis. The basic principles were discussed first, and then the research progress to date was discussed, as well as its limitations and the direction of development. Finally, all methods were compared, and vibrational spectroscopy was demonstrated that it could be used as a promising tool for early OA diagnosis. This review provides theoretical support for the application and development of vibrational spectroscopy technology in OA diagnosis, providing a new strategy for the nondestructive and rapid diagnosis of arthritis and promoting the development and clinical application of a component-based molecular spectrum detection technology.

Applications of Vibrational Spectroscopy for Analysis of Connective Tissues

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.

Characterization of connective tissues using near-infrared spectroscopy and imaging

Near-infrared (NIR) spectroscopy is a powerful analytical method for rapid, non-destructive and label-free assessment of biological materials. Compared to mid-infrared spectroscopy, NIR spectroscopy excels in penetration depth, allowing intact biological tissue assessment, albeit at the cost of reduced molecular specificity. Furthermore, it is relatively safe compared to Raman spectroscopy, with no risk of laser-induced photothermal damage. A typical NIR spectroscopy workflow for biological tissue characterization involves sample preparation, spectral acquisition, pre-processing and analysis. The resulting spectrum embeds intrinsic information on the tissue's biomolecular, structural and functional properties. Here we demonstrate the analytical power of NIR spectroscopy for exploratory and diagnostic applications by providing instructions for acquiring NIR spectra, maps and images in biological tissues. By adapting and extending this protocol from the demonstrated application in connective tissues to other biological tissues, we expect that a typical NIR spectroscopic study can be performed by a non-specialist user to characterize biological tissues in basic research or clinical settings. We also describe how to use this protocol for exploratory study on connective tissues, including differentiating among ligament types, non-destructively monitoring changes in matrix formation during engineered cartilage development, mapping articular cartilage proteoglycan content across bovine patella and spectral imaging across the depth-wise zones of articular cartilage and subchondral bone. Depending on acquisition mode and experiment objectives, a typical exploratory study can be completed within 6 h, including sample preparation and data analysis.

Single shot multispectral multidimensional imaging using chaotic waves

Multispectral imaging technology is a valuable scientific tool for various applications in astronomy, remote sensing, molecular fingerprinting, and fluorescence imaging. In this study, we demonstrate a single camera shot, lensless, interferenceless, motionless, non-scanning, space, spectrum, and time resolved five-dimensional incoherent imaging technique using tailored chaotic waves with quasi-random intensity and phase distributions. Chaotic waves can distinctly encode spatial and spectral information of an object in single self-interference intensity distribution. In this study, a tailored chaotic wave with a nearly pure phase function and lowest correlation noise is generated using a quasi-random array of pinholes. A unique sequence of signal processing techniques is applied to extract all possible spatial and spectral channels with the least entropy. The depth-wavelength reciprocity is exploited to see colour from depth and depth from colour and the physics of beam propagation is exploited to see at one depth by calibrating at another.

Near infrared spectroscopic assessment of loosely and tightly bound cortical bone water

Water is an important component of bone and plays a key role in its mechanical and structural integrity. Water molecules in bone are present in different locations, including loosely or tightly bound to the matrix and/or mineral (biological apatite) phases. Identification of water location and interactions with matrix components impact bone function but have been challenging to assess. Here, we used near infrared (NIR) spectroscopy to identify loosely and tightly bound water present in cortical bone. In hydrated samples, NIR spectra have two primary water absorption bands at frequencies of ∼5200 and 7000 cm^-1. Using lyophilization and hydrogen-deuterium exchange assays, we showed that these absorption bands are primarily associated with loosely bound bone water. Using further demineralization assays, thermal denaturation, and comparison to standards, we found that these absorption bands have underlying components associated with water molecules tightly bound to bone. In dehydrated samples, the peak at ∼5200 cm^-1 was assigned to a combination of water tightly bound to collagen and to mineral, whereas the peak at 7000 cm^-1 was exclusively associated with tightly bound mineral water. We also found significant positive correlations between the NIR mineral absorption bands and the mineral content as determined by an established mid infrared spectroscopic parameter, phosphate/amide I. Moreover, the NIR water data showed correlation trends with tissue mineral density (TMD) in cortical bone tissues. These observations reveal the ability of NIR spectroscopy to non-destructively identify loosely and tightly bound water in bone, which could have further applications in biomineralization and biomedical studies.

Non-Destructive Spectroscopic Assessment of High and Low Weight Bearing Articular Cartilage Correlates with Mechanical Properties

OBJECTIVE

Autologous articular cartilage (AC) harvested for repair procedures of high weight bearing (HWB) regions of the femoral condyles is typically obtained from low weight bearing (LWB) regions, in part due to the lack of non-destructive techniques for cartilage composition assessment. Here, we demonstrate that infrared fiber optic spectroscopy can be used to non-destructively evaluate variations in compositional and mechanical properties of AC across LWB and HWB regions.

DESIGN

AC plugs (N = 72) were harvested from the patellofemoral groove of juvenile bovine stifle joints, a LWB region, and femoral condyles, a HWB region. Near-infrared (NIR) and mid-infrared (MIR) fiber optic spectra were collected from plugs, and indentation tests were performed to determine the short-term and equilibrium moduli, followed by gravimetric water and biochemical analysis.

RESULTS

LWB tissues had a significantly greater amount of water determined by NIR and gravimetric assay. The moduli generally increased in tissues from the patellofemoral groove to the condyles, with HWB condyle cartilage having significantly higher moduli. A greater amount of proteoglycan content was also found in HWB tissues, but no differences in collagen content. In addition, NIR-determined water correlated with short-term modulus and proteoglycan content (R = -0.40 and -0.31, respectively), and a multivariate model with NIR data was able to predict short-term modulus within 15% error.

CONCLUSIONS

The properties of tissues from LWB regions differ from HWB tissues and can be determined non-destructively by infrared fiber optic spectroscopy. Clinicians may be able to use this modality to assess AC prior to harvesting osteochondral grafts for focal defect repair.

Environmentally-Controlled Near Infrared Spectroscopic Imaging of Bone Water

We have designed an environmentally-controlled chamber for near infrared spectroscopic imaging (NIRSI) to monitor changes in cortical bone water content, an emerging biomarker related to bone quality assessment. The chamber is required to ensure repeatable spectroscopic measurements of tissues without the influence of atmospheric moisture. A calibration curve to predict gravimetric water content from human cadaveric cortical bone was created using NIRSI data obtained at six different lyophilization time points. Partial least squares (PLS) models successfully predicted bone water content that ranged from 0–10% (R = 0.96, p < 0.05, root mean square error of prediction (RMSEP) = 7.39%), as well as in the physiologic range of 4–10% of wet tissue weight (R = 0.87, p < 0.05, RMSEP = 14.5%). Similar results were obtained with univariate and bivariate regression models for prediction of water in the 0–10% range. Further, we identified two new NIR bone absorbances, at 6560 cm⁻¹ and 6688 cm⁻¹, associated with water and collagen respectively. Such data will be useful in pre-clinical studies that investigate changes in bone quality with disease, aging and with therapeutic use.

Raman spectroscopy-based water content is a negative predictor of articular human cartilage mechanical function

OBJECTIVE

Probing the change in water content is an emerging approach to assess early diagnosis of osteoarthritis (OA). We herein developed a new method to assess hydration status of cartilage nondestructively using Raman spectroscopy (RS), and showed association of Raman-based water and organic content measurement with mechanical properties of cartilage. We further compared Raman-based water measurement to gravimetric and magnetic resonance imaging (MRI)-based water measurement.

DESIGN

Eighteen cadaveric human articular cartilage plugs from 6 donors were evenly divided into two age groups: young (n = 9, mean age: 29.3 ± 6.6) and old (n = 9, mean age: 64.0 ± 1.5). Water content in cartilage was measured using RS, gravimetric, and MRI-based techniques. Using confined compression creep test, permeability and aggregate modulus were calculated. Regression analyses were performed among RS parameters, MRI parameter, permeability, aggregate modulus and gravimetrically measured water content.

RESULTS

Regardless of the method used to calculate water content (gravimetric, RS and MRI), older cartilage group consistently had higher water content compared to younger group. There was a stronger association between gravimetric and RS-based water measurement (R_g² = 0.912) than between gravimetric and MRI-based water measurement (R_c² = 0.530). Gravimetric and RS-based water contents were significantly correlated with permeability and aggregate modulus whereas MRI-based water measurement was not.

CONCLUSION

RS allows for quantification of different water compartments in cartilage nondestructively, and estimation of up to 82% of the variation observed in the permeability and aggregate modulus of articular cartilage. RS has the potential to be used clinically to monitor cartilage quality noninvasively or minimally invasively with Raman probe during arthroscopy procedures.

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.

Raman spectroscopic imaging for quantification of depth-dependent and local heterogeneities in native and engineered cartilage

Articular cartilage possesses a remarkable, mechanically-robust extracellular matrix (ECM) that is organized and distributed throughout the tissue to resist physiologic strains and provide low friction during articulation. The ability to characterize the make-up and distribution of the cartilage ECM is critical to both understand the process by which articular cartilage undergoes disease-related degeneration and to develop novel tissue repair strategies to restore tissue functionality. However, the ability to quantitatively measure the spatial distribution of cartilage ECM constituents throughout the tissue has remained a major challenge. In this experimental investigation, we assessed the analytical ability of Raman micro-spectroscopic imaging to semi-quantitatively measure the distribution of the major ECM constituents in cartilage tissues. Raman spectroscopic images were acquired of two distinct cartilage tissue types that possess large spatial ECM gradients throughout their depth: native articular cartilage explants and large engineered cartilage tissue constructs. Spectral acquisitions were processed via multivariate curve resolution to decompose the "fingerprint" range spectra (800-1800 cm-1) to the component spectra of GAG, collagen, and water, giving rise to the depth dependent concentration profile of each constituent throughout the tissues. These Raman spectroscopic acquired-profiles exhibited strong agreement with profiles independently acquired via direct biochemical assaying of spatial tissue sections. Further, we harness this spectroscopic technique to evaluate local heterogeneities through the depth of cartilage. This work represents a powerful analytical validation of the accuracy of Raman spectroscopic imaging measurements of the spatial distribution of biochemical components in a biological tissue and shows that it can be used as a valuable tool for quantitatively measuring the distribution and organization of ECM constituents in native and engineered cartilage tissue specimens.

Vibrational spectroscopy and imaging: applications for tissue engineering

Tissue engineering (TE) approaches strive to regenerate or replace an organ or tissue. The successful development and subsequent integration of a TE construct is contingent on a series of in vitro and in vivo events that result in an optimal construct for implantation. Current widely used methods for evaluation of constructs are incapable of providing an accurate compositional assessment without destruction of the construct. In this review, we discuss the contributions of vibrational spectroscopic assessment for evaluation of tissue engineered construct composition, both during development and post-implantation. Fourier transform infrared (FTIR) spectroscopy in the mid and near-infrared range, as well as Raman spectroscopy, are intrinsically label free, can be non-destructive, and provide specific information on the chemical composition of tissues. Overall, we examine the contribution that vibrational spectroscopy via fiber optics and imaging have to tissue engineering approaches.

Online quantitative monitoring of live cell engineered cartilage growth using diffuse fiber-optic Raman spectroscopy

Tissue engineering (TE) has the potential to improve the outcome for patients with osteoarthritis (OA). The successful clinical translation of this technique as part of a therapy requires the ability to measure extracellular matrix (ECM) production of engineered tissues in vitro, in order to ensure quality control and improve the likelihood of tissue survival upon implantation. Conventional techniques for assessing the ECM content of engineered cartilage, such as biochemical assays and histological staining are inherently destructive. Raman spectroscopy, on the other hand, represents a non-invasive technique for in situ biochemical characterization. Here, we outline current roadblocks in translational Raman spectroscopy in TE and introduce a comprehensive workflow designed to non-destructively monitor and quantify ECM biomolecules in large (>3 mm), live cell TE constructs online. Diffuse near-infrared fiber-optic Raman spectra were measured from live cell cartilaginous TE constructs over a 56-day culturing period. We developed a multivariate curve resolution model that enabled quantitative biochemical analysis of the TE constructs. Raman spectroscopy was able to non-invasively quantify the ECM components and showed an excellent correlation with biochemical assays for measurement of collagen (R2 = 0.84) and glycosaminoglycans (GAGs) (R2 = 0.86). We further demonstrated the robustness of this technique for online prospective analysis of live cell TE constructs. The fiber-optic Raman spectroscopy strategy developed in this work offers the ability to non-destructively monitor construct growth online and can be adapted to a broad range of TE applications in regenerative medicine toward controlled clinical translation.

Nanoassemblies of Tissue-Reactive, Polyoxazoline Graft-Copolymers Restore the Lubrication Properties of Degraded Cartilage

Osteoarthritis leads to an alteration in the composition of the synovial fluid, which is associated with an increase in friction and the progressive and irreversible destruction of the articular cartilage. In order to tackle this degenerative disease, there has been a growing interest in the medical field to establish effective, long-term treatments to restore cartilage lubrication after damage. Here we develop a series of graft-copolymers capable of assembling selectively on the degraded cartilage, resurfacing it, and restoring the lubricating properties of the native tissue. These comprise a polyglutamic acid backbone (PGA) coupled to brush-forming, poly-2-methyl-2-oxazoline (PMOXA) side chains, which provide biopassivity and lubricity to the surface, and to aldehyde-bearing tissue-reactive groups, for the anchoring on the degenerated cartilage via Schiff bases. Optimization of the graft-copolymer architecture (i.e., density and length of side chains and amount of tissue-reactive functions) allowed a uniform passivation of the degraded cartilage surface. Graft-copolymer-treated cartilage showed very low coefficients of friction within synovial fluid, reestablishing and in some cases improving the lubricating properties of the natural cartilage. Due to these distinctive properties and their high biocompatibility and stability under physiological conditions, cartilage-reactive graft-copolymers emerge as promising injectable formulations to slow down the progression of cartilage degradation, which characterizes the early stages of osteoarthritis.