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

Non-neotissue constituents as underestimated confounders in the assessment of tissue engineered constructs by near-infrared spectroscopy

Non-destructive assessments are required for the quality control of tissue-engineered constructs and the optimization of the tissue culture process. Near-infrared (NIR) spectroscopy coupled with machine learning (ML) provides a promising approach for such assessment. However, due to its nonspecific nature, each spectrum incorporates information on both neotissue and non-neotissue constituents of the construct; the effect of these constituents on the NIR-based assessments of tissue-engineered constructs has been overlooked in previous studies. This study investigates the effect of scaffolds, growth factors, and buffers on NIR-based assessments of tissue-engineered constructs. To determine if these non-neotissue constituents have a measurable effect on the NIR spectra of the constructs that can introduce bias in their assessment, nine ML algorithms were evaluated in classifying the NIR spectra of engineered cartilage according to the scaffold used to prepare the constructs, the growth factors added to the culture media, and the buffers used for storing the constructs. The effect of controlling for these constituents was also evaluated using controlled and uncontrolled NIR-based ML models for predicting tissue maturity as an example of neotissue-related properties of interest. Samples used in this study were prepared using norbornene-modified hyaluronic acid scaffolds with or without the conjugation of an N-cadherin mimetic peptide. Selected samples were supplemented with transforming growth factor-beta1 or bone morphogenetic protein-9 growth factor. Some samples were frozen in cell lysis buffer, while the remaining samples were frozen in PBS until required for NIR analysis. The ML models for classifying the spectra of the constructs according to the four constituents exhibited high to fair performances, with F1 scores ranging from 0.9 to 0.52. Moreover, controlling for the four constituents significantly improved the performance of the models for predicting tissue maturity, with improvement in F1 scores ranging from 0.09 to 0.77. In conclusion, non-neotissue constituents have measurable effects on the NIR spectra of tissue-engineered constructs that can be detected by ML algorithms and introduce bias in the assessment of the constructs by NIR spectroscopy. Therefore, controlling for these constituents is necessary for reliable NIR-based assessments of tissue-engineered constructs.

In Situ Assessment of Porcine Osteochondral Repair Tissue in the Visible-Near Infrared Spectral Region

Standard assessment of cartilage repair progression by visual arthroscopy can be subjective and may result in suboptimal evaluation. Visible-near infrared (Vis-NIR) fiber optic spectroscopy of joint tissues, including articular cartilage and subchondral bone, provides an objective approach for quantitative assessment of tissue composition. Here, we applied this technique in the 350-2,500 nm spectral region to identify spectral markers of osteochondral tissue during repair with the overarching goal of developing a new approach to monitor repair of cartilage defects in vivo. Full thickness chondral defects were created in Yucatan minipigs using a 5-mm biopsy punch, and microfracture (MFx) was performed as a standard technique to facilitate repair. Tissues were evaluated at 1 month (in adult pigs) and 3 months (in juvenile pigs) post-surgery by spectroscopy and histology. After euthanasia, Vis-NIR spectra were collected in situ from the defect region. Additional spectroscopy experiments were carried out in vitro to aid in spectral interpretation. Osteochondral tissues were dissected from the joint and evaluated using the conventional International Cartilage Repair Society (ICRS) II histological scoring system, which showed lower scores for the 1-month than the 3-month repair tissues. In the visible spectral region, hemoglobin absorbances at 540 and 570 nm were significantly higher in spectra from 1-month repair tissue than 3-month repair tissue, indicating a reduction of blood in the more mature repair tissue. In the NIR region, we observed qualitative differences between the two groups in spectra taken from the defect, but differences did not reach significance. Furthermore, spectral data also indicated that the hydrated environment of the joint tissue may interfere with evaluation of tissue water absorbances in the NIR region. Together, these data provide support for further investigation of the visible spectral region for assessment of longitudinal repair of cartilage defects, which would enable assessment during routine arthroscopy, particularly in a hydrated environment.

Near-Infrared Spectroscopy Enables Arthroscopic Histologic Grading of Human Knee Articular Cartilage

Purpose

To develop the means to estimate cartilage histologic grades and proteoglycan content in ex vivo arthroscopy using near-infrared spectroscopy (NIRS).

Methods

In this experimental study, arthroscopic NIR spectral measurements were performed on both knees of 9 human cadavers, followed by osteochondral block extraction and in vitro measurements: reacquisition of spectra and reference measurements (proteoglycan content, and three histologic scores). A hybrid model, combining principal component analysis and linear mixed-effects model (PCA-LME), was trained for each reference to investigate its relationship with in vitro NIR spectra. The performance of the PCA-LME model was validated with ex vivo spectra before and after the exclusion of outlying spectra. Model performance was evaluated based on Spearman rank correlation (ρ) and root-mean-square error (RMSE).

Results

The PCA-LME models performed well (independent test: average ρ = 0.668, RMSE = 0.892, P < .001) in the prediction of the reference measurements based on in vitro data. The performance on ex vivo arthroscopic data was poorer but improved substantially after outlier exclusion (independent test: average ρ = 0.462 to 0.614, RMSE = 1.078 to 0.950, P = .019 to .008).

Conclusions

NIRS is capable of nondestructive evaluation of cartilage integrity (i.e., histologic scores and proteoglycan content) under similar conditions as in clinical arthroscopy.

Clinical Relevance

There are clear clinical benefits to the accurate assessment of cartilage lesions in arthroscopy. Visual grading is the current standard of care. However, optical techniques, such as NIRS, may provide a more objective assessment of cartilage damage.

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.

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.

Approaches for In Situ Monitoring of Matrix Development in Hydrogel-Based Engineered Cartilage

Near infrared (NIR) spectroscopy using a fiber optic probe shows great promise for the nondestructive in situ monitoring of tissue engineered construct development; however, the NIR evaluation of matrix components in samples with high water content is challenging, as water absorbances overwhelm the spectra. In this study, we established approaches by which NIR spectroscopy can be used to select optimal individual engineered hydrogel constructs based on matrix content and mechanical properties. NIR spectroscopy of dry standard compounds allowed identification of several absorbances related to collagen and/or proteoglycan (PG), of which only two could be identified in spectra obtained from hydrated constructs, at ∼5940 and 5800 cm-1. In dry sample mixtures, the ratio of these peaks correlated positively to collagen and negatively to PG. In NIR spectra from engineered cartilage hydrogels, these peaks reflected higher collagen and PG content and dynamic modulus values, permitting the differentiation of constructs with poor and good matrix development. Similarly, the increasing baseline offset in raw NIR spectra also reflected matrix development in hydrated constructs. However, weekly monitoring of NIR spectra and the peaks at ∼5940 and 5800 cm-1 was not adequate to differentiate individual constructs based on matrix composition. Interestingly, changes in the baseline offset of raw spectra could be used to evaluate the growth trajectory of individual constructs. These results demonstrate an optimal approach for the use of fiber optic NIR spectroscopy for in situ monitoring of the development of engineered cartilage, which will aid in identifying individual constructs for implantation. Impact statement A current demand in tissue engineering is the establishment of nondestructive approaches to evaluate construct development during growth in vitro. In this article, we demonstrate original nondestructive approaches by which fiber optic NIR spectroscopy can be used to assess matrix (PG and collagen) formation and mechanical properties in hydrogel-based constructs. Our data provide a cohesive molecular-based approach for in situ longitudinal evaluation of construct development during growth in vitro. The establishment of these approaches is a valuable step toward the real-time identification and selection of constructs with optimal properties, which may lead to successful tissue integration upon in vivo implantation.

Heterogeneous matrix deposition in human tissue engineered cartilage changes the local shear modulus and resistance to local construct buckling

Human tissue engineered cartilage is a promising solution for focal cartilage defects, but these constructs do not have the same local mechanical properties as native tissue. Most clinically relevant engineered cartilage constructs seed human chondrocytes onto a collagen scaffold, which buckles at low loads and strains. This buckling creates local regions of high strain that could cause cell death and damage the engineered tissue. Since human tissue engineered cartilage is commonly grown in-vivo prior to implantation, new matrix deposition could improve the local implant mechanics and prevent local tissue buckling. However, the relationship between local biochemical composition and the local mechanics or local buckling probability has never been quantified. Therefore, this study correlated the local biochemical composition of human tissue engineered cartilage constructs using Fourier transform infrared spectroscopy (FTIR) with the local shear modulus and local buckling probability. The local shear modulus and local buckling probability were obtained using a confocal elastography technique. The local shear modulus increased with increases in local aggrecan content in the interior region (inside the scaffold). A minimum amount of aggrecan was required to prevent local construct buckling at physiologic strains. Since the original scaffold was primarily composed of collagen, increases in collagen content due to new matrix deposition was minimal and had little effect on the mechanical properties. Thus, we concluded that aggrecan deposition inside the scaffold pores is the most effective way to improve the mechanical function and prevent local tissue damage in human tissue engineered cartilage constructs.

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.

Arthroscopic near infrared spectroscopy enables simultaneous quantitative evaluation of articular cartilage and subchondral bone in vivo

Arthroscopic assessment of articular tissues is highly subjective and poorly reproducible. To ensure optimal patient care, quantitative techniques (e.g., near infrared spectroscopy (NIRS)) could substantially enhance arthroscopic diagnosis of initial signs of post-traumatic osteoarthritis (PTOA). Here, we demonstrate, for the first time, the potential of arthroscopic NIRS to simultaneously monitor progressive degeneration of cartilage and subchondral bone in vivo in Shetland ponies undergoing different experimental cartilage repair procedures. Osteochondral tissues adjacent to the repair sites were evaluated using an arthroscopic NIRS probe and significant (p < 0.05) degenerative changes were observed in the tissue properties when compared with tissues from healthy joints. Artificial neural networks (ANN) enabled reliable (ρ = 0.63–0.87, NMRSE = 8.5–17.2%, RPIQ = 1.93–3.03) estimation of articular cartilage biomechanical properties, subchondral bone plate thickness and bone mineral density (BMD), and subchondral trabecular bone thickness, bone volume fraction (BV), BMD, and structure model index (SMI) from in vitro spectral data. The trained ANNs also reliably predicted the properties of an independent in vitro test group (ρ = 0.54–0.91, NMRSE = 5.9–17.6%, RPIQ = 1.68–3.36). However, predictions based on arthroscopic NIR spectra were less reliable (ρ = 0.27–0.74, NMRSE = 14.5–24.0%, RPIQ = 1.35–1.70), possibly due to errors introduced during arthroscopic spectral acquisition. Adaptation of NIRS could address the limitations of conventional arthroscopy through quantitative assessment of lesion severity and extent, thereby enhancing detection of initial signs of PTOA. This would be of high clinical significance, for example, when conducting orthopaedic repair surgeries.

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.

Compositional Assessment of Human Tracheal Cartilage by Infrared Spectroscopy

Objectives To assess the potential of infrared fiber-optic spectroscopy to evaluate the compositional properties of human tracheal cartilage. Study Design Laboratory-based study. Methods Twenty human cadaveric distal tracheas were harvested (age range 20-78 years; 6 females, 14 males) for compositional analysis. Histologic staining, Fourier transform infrared imaging spectroscopy data on collagen and proteoglycan (PG) content, and near-infrared (NIR) fiber-optic probe spectroscopic data that reflect protein and water content were evaluated. NIR fiber-optic probe data were also obtained from the proximal trachea in 4 human cadavers (age range 51-65 years; 2 females, 2 males) in situ for comparison to distal trachea spectral data. Results In the distal trachea cohort, the spectroscopic-determined ratio of PG/amide I, indicative of the relative amount of PG, was significantly higher in the tissues from the younger group compared to the older group (0.37 ± 0.08 vs 0.32 ± 0.05, P = .05). A principal component analysis of the NIR spectral data enabled separation of spectra based on tracheal location, likely due to differences in both protein and water content. The NIR-determined water content based on the 5200-cm-1 peak was significantly higher in the distal trachea compared to the proximal trachea ( P < .001). Conclusions Establishment of normative compositional values and further elucidating differences between the segments of trachea will enable more directed research toward appropriate compositional end points in regenerative medicine for tracheal repair.

Near-Infrared Spectroscopy Predicts Compositional and Mechanical Properties of Hyaluronic Acid-Based Engineered Cartilage Constructs

Hyaluronic acid (HA) has been widely used for cartilage tissue engineering applications. However, the optimal time point to harvest HA-based engineered constructs for cartilage repair is still under investigation. In this study, we investigated the ability of a nondestructive modality, near-infrared spectroscopic (NIR) analysis, to predict compositional and mechanical properties of HA-based engineered cartilage constructs. NIR spectral data were collected from control, unseeded constructs, and twice per week by fiber optic from constructs seeded with chondrocytes during their development over an 8-week period. Constructs were harvested at 2, 4, 6, and 8 weeks, collagen and sulfated glycosaminoglycan content measured using biochemical assays, and the mechanical properties of the constructs evaluated using unconfined compression tests. NIR absorbances associated with the scaffold material, water, and engineered cartilage matrix, were identified. The NIR-determined matrix absorbance plateaued after 4 weeks of culture, which was in agreement with the biochemical assay results. Similarly, the mechanical properties of the constructs also plateaued at 4 weeks. A multivariate partial least square model based on NIR spectral input was developed to predict the moduli of the constructs, which resulted in a prediction error of 10% and R value of 0.88 for predicted versus actual values of dynamic modulus. Furthermore, the maximum increase in moduli was calculated from the first derivative of the curve fit of NIR-predicted and actual moduli values over time, and both occurred at ∼2 weeks. Collectively, these data suggest that NIR spectral data analysis could be an alternative to destructive biochemical and mechanical methods for evaluation of HA-based engineered cartilage construct properties.

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.

Monitoring osteoarthritis progression using near infrared (NIR) spectroscopy

We demonstrate in this study the potential of near infrared (NIR) spectroscopy as a tool for monitoring progression of cartilage degeneration in an animal model. Osteoarthritic degeneration was artificially induced in one joint in laboratory rats, and the animals were sacrificed at four time points: 1, 2, 4, and 6 weeks (3 animals/week). NIR spectra were acquired from both (injured and intact) knees. Subsequently, the joint samples were subjected to histological evaluation and glycosaminoglycan (GAG) content analysis, to assess disease severity based on the Mankin scoring system and to determine proteoglycan loss, respectively. Multivariate spectral techniques were then employed for classification (principal component analysis and support vector machines) and prediction (partial least squares regression) of the samples’ Mankin scores and GAG content from their NIR spectra. Our results demonstrate that NIR spectroscopy is sensitive to degenerative changes in articular cartilage, and is capable of distinguishing between mild (weeks 1&2; Mankin <=2) and advanced (weeks 4&6; Mankin =>3) cartilage degeneration. In addition, the spectral data contains information that enables estimation of the tissue’s Mankin score (error = 12.6%, R² = 86.2%) and GAG content (error = 7.6%, R² = 95%). We conclude that NIR spectroscopy is a viable tool for assessing cartilage degeneration post-injury, such as, post-traumatic osteoarthritis.

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.