Isaac Afara

In Vivo Evaluation of the Potential of High-Frequency Ultrasound for Arthroscopic Examination of the Shoulder Joint

Publisher: SAGE Publications

Date: 23-06-2016

DOI: 10.1177/1947603515617280

Abstract: Accurate arthroscopic evaluation of cartilage lesions could significantly improve the outcome of repair surgery. In this study, we investigated for the first time the potential of intra-articular ultrasound as an arthroscopic tool for grading cartilage defects in the human shoulder joint in vivo and compared the outcome to results from arthroscopic evaluation and magnetic resonance imaging findings. A total of 26 sites from 9 patients undergoing routine shoulder arthroscopy were quantitatively evaluated with a clinical intravascular (40MHz) ultrasound imaging system, using the regular arthroscopy portals. Reflection coefficient ( R), integrated reflection coefficient ( IRC), apparent integrated backscattering ( AIB), and ultrasound roughness index ( URI) were calculated, and high-resolution ultrasound images were obtained per site. Each site was visually graded according to the International Cartilage Repair Society (ICRS) system. “Ultrasound scores” corresponding to the ICRS system were determined from the ultrasound images. Magnetic resonance imaging was conducted and cartilage integrity at each site was classified into 5 grades (0 = normal, 4 = severely abnormal) by a radiologist. R and IRC were lower at sites with damaged cartilage surface ( P = 0.033 and P = 0.043, respectively) and correlated with arthroscopic ICRS grades ( r s = −0.444, P = 0.023 and r s = −0.426, P = 0.03, respectively). Arthroscopic ICRS grades and ultrasound scores were significantly correlated (rs = 0.472, P = 0.015), but no significant correlation was found between magnetic resonance imaging data and other parameters. The results suggest that ultrasound arthroscopy could facilitate quantitative clinical appraisal of articular cartilage integrity in the shoulder joint and provide information on cartilage lesion depth and severity for quantitative diagnostics in surgery.

Semi‐automated International Cartilage Repair Society scoring of equine articular cartilage lesions in optical coherence tomography images

Publisher: Wiley

Date: 20-10-2016

DOI: 10.1111/EVJ.12637

Abstract: Arthroscopic optical coherence tomography (OCT) is a promising tool for the detailed evaluation of articular cartilage injuries. However, OCT-based articular cartilage scoring still relies on the operator's visual estimation. To test the hypothesis that semi-automated International Cartilage Repair Society (ICRS) scoring of chondral lesions seen in OCT images could enhance intra- and interobserver agreement of scoring and its accuracy. Validation study using equine cadaver tissue. Osteochondral s les (n = 99) were prepared from 18 equine metacarpophalangeal joints and imaged using OCT. Custom-made software was developed for semi-automated ICRS scoring of cartilage lesions on OCT images. Scoring was performed visually and semi-automatically by five observers, and levels of inter- and intraobserver agreement were calculated. Subsequently, OCT-based scores were compared with ICRS scores based on light microscopy images of the histological sections of matching locations (n = 82). When semi-automated scoring of the OCT images was performed by multiple observers, mean levels of intraobserver and interobserver agreement were higher than those achieved with visual OCT scoring (83% vs. 77% and 74% vs. 33%, respectively). Histology-based scores from matching regions of interest agreed better with visual OCT-based scoring than with semi-automated OCT scoring however, the accuracy of the software was improved by optimising the threshold combinations used to determine the ICRS score. Images were obtained from cadavers. Semi-automated scoring software improved the reproducibility of ICRS scoring of chondral lesions in OCT images and made scoring less observer-dependent. The image analysis and segmentation techniques adopted in this study warrant further optimisation to achieve better accuracy with semi-automated ICRS scoring. In addition, studies on in vivo applications are required.

Estimation of articular cartilage properties using multivariate analysis of optical coherence tomography signal

Publisher: Elsevier BV

Date: 12-2015

DOI: 10.1016/J.JOCA.2015.05.034

Abstract: The aim was to investigate the applicability of multivariate analysis of optical coherence tomography (OCT) information for determining structural integrity, composition and mechanical properties of articular cartilage. Equine osteochondral s les (N = 65) were imaged with OCT, and their total attenuation and backscattering coefficients (μt and μb) were measured. Subsequently, the Mankin score, optical density (OD) describing the fixed charge density, light absorbance in amide I region (Aamide), collagen orientation, permeability, fibril network modulus (Ef) and non-fibrillar matrix modulus (Em) of the s les were determined. Partial least squares (PLS) regression model was calculated to predict tissue properties from the OCT signals of the s les. Significant correlations between the measured and predicted mean collagen orientation (R(2) = 0.75, P < 0.0001), permeability (R(2) = 0.74, P < 0.0001), mean OD (R(2) = 0.73, P < 0.0001), Mankin scores (R(2) = 0.70, P < 0.0001), Em (R(2) = 0.50, P < 0.0001), Ef (R(2) = 0.42, P < 0.0001), and Aamide (R(2) = 0.43, P 0.05). Multivariate analysis of OCT signal provided good estimates for tissue structure, composition and mechanical properties. This technique may significantly enhance OCT evaluation of articular cartilage integrity, and could be applied, for ex le, in delineation of degenerated areas around cartilage injuries during arthroscopic repair surgery.

Infrared fiber optic spectroscopy detects bovine articular cartilage degeneration

Publisher: Cold Spring Harbor Laboratory

Date: 20-05-2020

DOI: 10.1101/2020.05.18.101600

Abstract: Articular cartilage (AC) is a soft connective tissue that covers the ends of articulating bones. Joint injuries may lead to degeneration of cartilage tissue and initiate development of post-traumatic osteoarthritis (OA). Arthroscopic surgeries can be used to treat joint injuries, but arthroscopic evaluation of cartilage quality is subjective. Therefore, new methods are needed for objective assessment of cartilage degeneration. Fourier transform infrared (FTIR) spectroscopy can be used to assess tissue composition based on the fundamental molecular vibrations. When combined with fiber optics and attenuated total reflectance (ATR) crystal, the measurements can be done flexibly without any s le processing. We hypothesize that Fourier transform infrared attenuated total reflection (FTIR-ATR) spectroscopy can detect enzymatically and mechanically induced changes similar to changes occurring during progression of OA. Fresh bovine patellar cartilage plugs ( n = 60) were extracted and degraded enzymatically and mechanically. Adjacent untreated control s les ( n = 60) were utilized as controls. Enzymatic degradation was implemented by 90-min and 24-hour collagenase as well as 30-min trypsin treatments. Mechanical damage was induced by: 1) dropping a weight impactor on the cartilage plugs, and 2) abrading the cartilage surface with a rotating sandpaper. Fiber optic FTIR-ATR spectroscopic measurements were conducted for control and degraded s les, and spectral changes were assessed with random forest (RF), partial least squares discriminant analysis (PLS-DA), and support vector machine (SVM) classifiers. RF (accuracy 93.1 % to 79.2 %), PLS-DA (accuracy 95.8% to 81.9%), and SVM (accuracy 91.7% to 80.6%) all had excellent classification performance for detecting the different enzymatic and mechanical damage on cartilage matrix. The results suggest that fiber optic FTIR-ATR spectroscopy is a viable way to detect minor degeneration of AC.

Optical spectroscopic characterization of human meniscus biomechanical properties

Publisher: SPIE-Intl Soc Optical Eng

Date: 23-12-2017

DOI: 10.1117/1.JBO.22.12.125008

Resolving the Near-Infrared Spectrum of Articular Cartilage

Publisher: SAGE Publications

Date: 13-10-2021

DOI: 10.1177/19476035211035417

Abstract: Spectroscopic techniques, such as near-infrared (NIR) spectroscopy, are gaining significant research interest for characterizing connective tissues, particularly articular cartilage, because there is still a largely unmet need for rapid, accurate and objective methods for assessing tissue integrity in real-time during arthroscopic surgery. This study aims to identify the NIR spectral range that is optimal for characterizing cartilage integrity by ( a) identifying the contribution of its major constituents (collagen and proteoglycans) to its overall spectrum using proxy constituent models and ( b) determining constituent-specific spectral contributions that can be used for assessment of cartilage in its physiological state. The NIR spectra of cartilage matrix constituent models were measured and compared with specific molecular components of organic compounds in the NIR spectral range in order to identify their bands and molecular assignments. To verify the identified bands, spectra of the model compounds were compared with those of native cartilage. Since water obscures some bands in the NIR range, spectral measurements of the native cartilage were conducted under conditions of decreasing water content to lify features of the solid matrix components. The identified spectral bands were then compared and examined in the resulting spectra of the intact cartilage s les. As water was progressively eliminated from cartilage, the specific contribution of the different matrix components was observed to correspond with those identified from the proxy cartilage component models. Spectral peaks in the regions 5500 to 6250 cm −1 and 8100 to 8600 cm −1 were identified to be effective for characterizing cartilage proteoglycan and collagen contents, respectively.

Non-destructive evaluation of articular cartilage defects using near-infrared (NIR) spectroscopy in osteoarthritic rat models and its direct relation to Mankin Score

Publisher: Elsevier BV

Date: 11-2012

DOI: 10.1016/J.JOCA.2012.07.007

Abstract: The aim of this study was to demonstrate the potential of near-infrared (NIR) spectroscopy for categorizing cartilage degeneration induced in animal models. Three models of osteoarthritic degeneration were induced in laboratory rats via one of the following methods: (1) menisectomy (MSX) (2) anterior cruciate ligament transection (ACLT) and (3) intra-articular injection of mono-ido-acetate (1 mg) (MIA), in the right knee joint, with 12 rats per model group. After 8 weeks, the animals were sacrificed and tibial knee joints were collected. A custom-made near-infrared (NIR) probe of diameter 5 mm was placed on the cartilage surface and spectral data were acquired from each specimen in the wave number range 4,000-12,500 cm(-1). Following spectral data acquisition, the specimens were fixed and Safranin-O staining was performed to assess disease severity based on the Mankin scoring system. Using multivariate statistical analysis based on principal component analysis and partial least squares regression, the spectral data were then related to the Mankin scores of the s les tested. Mild to severe degenerative cartilage changes were observed in the subject animals. The ACLT models showed mild cartilage degeneration, MSX models moderate, and MIA severe cartilage degenerative changes both morphologically and histologically. Our result demonstrates that NIR spectroscopic information is capable of separating the cartilage s les into different groups relative to the severity of degeneration, with NIR correlating significantly with their Mankin score (R(2) = 88.85%). We conclude that NIR is a viable tool for evaluating articular cartilage health and physical properties such as change in thickness with degeneration.

Characterization of Articular Cartilage Recovery and Its Correlation with Optical Response in the Near-Infrared Spectral Range

Publisher: SAGE Publications

Date: 10-08-2016

DOI: 10.1177/1947603516662502

Abstract: In this study, we examine the capacity of a new parameter, based on the recovery response of articular cartilage, to distinguish between healthy and damaged tissues. We also investigate whether or not this new parameter correlates with the near-infrared (NIR) optical response of articular cartilage. Normal and artificially degenerated (proteoglycan-depleted) bovine cartilage s les were nondestructively probed using NIR spectroscopy. Subsequently they were subjected to a load and unloading protocol, and the recovery response was logged during unloading. The recovery parameter, elastic rebound ( E R ), is based on the strain energy released as the s les underwent instantaneous elastic recovery. Our results reveal positive relationship between the rebound parameter and cartilage proteoglycan content (normal s les: 2.20 ± 0.10 N mm proteoglycan-depleted s les: 0.50 ± 0.04 N mm for 1 hour of enzymatic treatment and 0.13 ± 0.02 N mm for 4 hours of enzymatic treatment). In addition, multivariate analysis using partial least squares regression was employed to investigate the relationship between E R and NIR spectral data. The results reveal significantly high correlation ( R 2 cal = 98.35% and R 2 val = 79.87% P 0.0001), with relatively low error (14%), between the recovery and optical response of cartilage in the combined NIR regions 5,450 to 6,100 cm −1 and 7,500 to 12,500 cm −1 . We conclude that E R can indicate the mechanical condition and state of health of articular cartilage. The correlation of E R with cartilage optical response in the NIR range could facilitate real-time evaluation of the tissue’s integrity during arthroscopic surgery and could also provide an important tool for cartilage assessment in tissue engineering and regeneration research.

Optimal Regression Method for Near-Infrared Spectroscopic Evaluation of Articular Cartilage

Publisher: SAGE Publications

Date: 22-08-2017

DOI: 10.1177/0003702817726766

Abstract: Near-infrared (NIR) spectroscopy has been successful in nondestructive assessment of biological tissue properties, such as stiffness of articular cartilage, and is proposed to be used in clinical arthroscopies. Near-infrared spectroscopic data include absorbance values from a broad wavelength region resulting in a large number of contributing factors. This broad spectrum includes information from potentially noisy variables, which may contribute to errors during regression analysis. We hypothesized that partial least squares regression (PLSR) is an optimal multivariate regression technique and requires application of variable selection methods to further improve the performance of NIR spectroscopy-based prediction of cartilage tissue properties, including instantaneous, equilibrium, and dynamic moduli and cartilage thickness. To test this hypothesis, we conducted for the first time a comparative analysis of multivariate regression techniques, which included principal component regression (PCR), PLSR, ridge regression, least absolute shrinkage and selection operator (Lasso), and least squares version of support vector machines (LS-SVM) on NIR spectral data of equine articular cartilage. Additionally, we evaluated the effect of variable selection methods, including Monte Carlo uninformative variable elimination (MC-UVE), competitive adaptive reweighted s ling (CARS), variable combination population analysis (VCPA), backward interval PLS (BiPLS), genetic algorithm (GA), and jackknife, on the performance of the optimal regression technique. The PLSR technique was found as an optimal regression tool (R 2 Tissue thickness = 75.6%, R 2 Dynamic modulus = 64.9%) for cartilage NIR data variable selection methods simplified the prediction models enabling the use of lesser number of regression components. However, the improvements in model performance with variable selection methods were found to be statistically insignificant. Thus, the PLSR technique is recommended as the regression tool for multivariate analysis for prediction of articular cartilage properties from its NIR spectra.

Application of near infrared (NIR) spectroscopy for determining the thickness of articular cartilage

Publisher: Elsevier BV

Date: 2013

DOI: 10.1016/J.MEDENGPHY.2012.04.003

Abstract: The determination of the characteristics of articular cartilage such as thickness, stiffness and swelling, especially in the form that can facilitate real-time decisions and diagnostics is still a matter for research and development. This paper correlates near infrared spectroscopy with mechanically measured cartilage thickness to establish a fast, non-destructive, repeatable and precise protocol for determining this tissue property. Statistical correlation was conducted between the thickness of bovine cartilage specimens (n=97) and regions of their near infrared spectra. Nine regions were established along the full absorption spectrum of each s le and were correlated with the thickness using partial least squares (PLS) regression multivariate analysis. The coefficient of determination (R²) varied between 53 and 93%, with the most predictive region (R²=93.1%, p<0.0001) for cartilage thickness lying in the region (wavenumber) 5350-8850 cm⁻¹. Our results demonstrate that the thickness of articular cartilage can be measured spectroscopically using NIR light. This protocol is potentially beneficial to clinical practice and surgical procedures in the treatment of joint disease such as osteoarthritis.

Deep Learning Classification of Cartilage Integrity Using Near Infrared Spectroscopy

Publisher: OSA

Date: 2018

DOI: 10.1364/TRANSLATIONAL.2018.JTU3A.27

Near infrared spectroscopy for rapid determination of Mankin score components: A potential tool for quantitative characterization of articular cartilage at surgery

Publisher: Elsevier BV

Date: 09-2014

DOI: 10.1016/J.ARTHRO.2014.04.097

Abstract: The purpose of this study was to demonstrate the potential of near infrared (NIR) spectroscopy for characterizing the health and degenerative state of articular cartilage based on the components of the Mankin score. Three models of osteoarthritic degeneration induced in laboratory rats by anterior cruciate ligament (ACL) transection, meniscectomy (MSX), and intra-articular injection of monoiodoacetate (1 mg) (MIA) were used in this study. Degeneration was induced in the right knee joint each model group consisted of 12 rats (N = 36). After 8 weeks, the animals were euthanized and knee joints were collected. A custom-made diffuse reflectance NIR probe of 5-mm diameter was placed on the tibial and femoral surfaces, and spectral data were acquired from each specimen in the wave number range of 4,000 to 12,500 cm(-1). After spectral data acquisition, the specimens were fixed and safranin O staining (SOS) was performed to assess disease severity based on the Mankin scoring system. Using multivariate statistical analysis, with spectral preprocessing and wavelength selection technique, the spectral data were then correlated to the structural integrity (SI), cellularity (CEL), and matrix staining (SOS) components of the Mankin score for all the s les tested. ACL models showed mild cartilage degeneration, MSX models had moderate degeneration, and MIA models showed severe cartilage degenerative changes both morphologically and histologically. Our results reveal significant linear correlations between the NIR absorption spectra and SI (R(2) = 94.78%), CEL (R(2) = 88.03%), and SOS (R(2) = 96.39%) parameters of all s les in the models. In addition, clustering of the s les according to their level of degeneration, with respect to the Mankin components, was also observed. NIR spectroscopic probing of articular cartilage can potentially provide critical information about the health of articular cartilage matrix in early and advanced stages of osteoarthritis (OA). This rapid nondestructive method can facilitate clinical appraisal of articular cartilage integrity during arthroscopic surgery.

Accounting for spatial dependency in multivariate spectroscopic data

Publisher: Elsevier BV

Date: 11-2018

DOI: 10.1016/J.CHEMOLAB.2018.09.010

Load-unloading response of intact and artificially degraded articular cartilage correlated with near infrared (NIR) absorption spectra

Publisher: Elsevier BV

Date: 04-2013

DOI: 10.1016/J.JMBBM.2012.11.022

Abstract: The conventional mechanical properties of articular cartilage, such as compressive stiffness, have been demonstrated to be limited in their capacity to distinguish intact (visually normal) from degraded cartilage s les. In this paper, we explore the correlation between a new mechanical parameter, namely the reswelling of articular cartilage following unloading from a given compressive load, and the near infrared (NIR) spectrum. The capacity to distinguish mechanically intact from proteoglycan-depleted tissue relative to the "reswelling" characteristic was first established, and the result was subsequently correlated with the NIR spectral data of the respective tissue s les. To achieve this, normal intact and enzymatically degraded s les were subjected to both NIR probing and mechanical compression based on a load-unload-reswelling protocol. The parameter δr, characteristic of the osmotic "reswelling" of the matrix after unloading to a constant small load in the order of the osmotic pressure of cartilage, was obtained for the different s le types. Multivariate statistics was employed to determine the degree of correlation between δr and the NIR absorption spectrum of relevant specimens using Partial Least Squared (PLS) regression. The results show a strong relationship (R(2)=95.89%, p<0.0001) between the spectral data and δr. This correlation of δr with NIR spectral data suggests the potential for determining the reswelling characteristics non-destructively. It was also observed that δr values bear a significant relationship with the cartilage matrix integrity, indicated by its proteoglycan content, and can therefore differentiate between normal and artificially degraded proteoglycan-depleted cartilage s les. It is therefore argued that the reswelling of cartilage, which is both biochemical (osmotic) and mechanical (hydrostatic pressure) in origin, could be a strong candidate for characterizing the tissue, especially in regions surrounding focal cartilage defects in joints.

Detection of enzymatically and mechanically induced degradation of bovine articular cartilage tissue with mid-infrared spectroscopy

Publisher: Elsevier BV

Date: 04-2019

DOI: 10.1016/J.JOCA.2019.02.035

Bactericidal effects of natural nanotopography of dragonfly wing on Escherichia coli

Publisher: American Chemical Society (ACS)

Date: 16-02-2017

DOI: 10.1021/ACSAMI.6B13666

Abstract: Nanotextured surfaces (NTSs) are critical to organisms as self-adaptation and survival tools. These NTSs have been actively mimicked in the process of developing bactericidal surfaces for erse biomedical and hygiene applications. To design and fabricate bactericidal topographies effectively for various applications, understanding the bactericidal mechanism of NTS in nature is essential. The current mechanistic explanations on natural bactericidal activity of nanopillars have not utilized recent advances in microscopy to study the natural interaction. This research reveals the natural bactericidal interaction between E. coli and a dragonfly wing's (Orthetrum villosovittatum) NTS using advanced microscopy techniques and proposes a model. Contrary to the existing mechanistic models, this experimental approach demonstrated that the NTS of Orthetrum villosovittatum dragonfly wings has two prominent nanopillar populations and the resolved interface shows membrane damage occurred without direct contact of the bacterial cell membrane with the nanopillars. We propose that the bacterial membrane damage is initiated by a combination of strong adhesion between nanopillars and bacterium EPS layer as well as shear force when immobilized bacterium attempts to move on the NTS. These findings could help guide the design of novel biomimetic nanomaterials by maximizing the synergies between biochemical and mechanical bactericidal effects.

Porosity predicted from ultrasound backscatter using multivariate analysis can improve accuracy of cortical bone thickness assessment

Publisher: Acoustical Society of America (ASA)

Date: 2017

DOI: 10.1121/1.4973572

Abstract: A rapidly growing area of interest in quantitative ultrasound assessment of bone is to determine cortical bone porosity from ultrasound backscatter. Current backscatter analyses are based on numerical simulations, while there are no published reports of successful experimental measurements. In this study, multivariate analysis is applied to ultrasound reflections and backscatter to predict cortical bone porosity. The porosity is then applied to estimate cortical bone radial speed of sound (SOS) and thickness using ultrasound backscatter signals obtained at 2.25 and 5 MHz center frequencies from cortical bone s les (n = 43) extracted from femoral diaphyses. The study shows that the partial least squares regression technique could be employed to successfully predict (R2 = 0.71–0.73) cortical porosity. It is found that this multivariate approach can reduce uncertainty in pulse-echo assessment of cortical bone thickness from 0.220 to 0.045 mm when porosity based radial SOS was applied, instead of a constant value from literature. Upon further validation, accurate estimation of cortical bone porosity and thickness may be applied as a financially viable option for fracture risk assessment of in iduals.

Effect of decellularization on the load-bearing characteristics of articular cartilage matrix

Publisher: Springer Science and Business Media LLC

Date: 10-2015

DOI: 10.1007/S13770-014-0083-Y

Near Infrared Spectroscopic Evaluation of Ligament and Tendon Biomechanical Properties

Publisher: Springer Science and Business Media LLC

Date: 20-09-2019

DOI: 10.1007/S10439-018-02125-9

Abstract: Knee ligaments and tendons are collagen-rich viscoelastic connective tissues that provide vital mechanical stabilization and support to the knee joint. Deterioration of ligaments has an adverse effect on the health of the knee and can eventually lead to ligament rupture and osteoarthritis. In this study, the feasibility of near infrared spectroscopy (NIRS) was, for the first time, tested for evaluation of ligament and tendon mechanical properties by performing measurements on bovine stifle joint ligament (N = 40) and patellar tendon (N = 10) s les. The mechanical properties of the s les were determined using a uniaxial tensile testing protocol. Partial least squares regression models were then developed to determine if morphological, viscoelastic, and quasi-static properties of the s les could be predicted from the NIR spectra. Best performance of NIRS in predicting mechanical properties was observed for toughness at yield point (median [Formula: see text], median normalized [Formula: see text]), toughness at failure point (median [Formula: see text], median normalized [Formula: see text]), and the ultimate strength of the ligament/tendon (median [Formula: see text], median normalized [Formula: see text]). Thus, we show that NIRS is capable of estimating ligament and tendon biomechanical properties, especially in parameters related to tissue failure. We believe this method could substantially enhance the currently limited arthroscopic evaluation of ligaments and tendons.

Optical spectroscopic determination of human meniscus composition

Publisher: Wiley

Date: 27-08-2015

DOI: 10.1002/JOR.23025

Abstract: This study investigates the correlation between the composition of human meniscus and its absorption spectrum in the visible (VIS) and near infrared (NIR) spectral range. Meniscus s les (n = 24) were obtained from nonarthritic knees of human cadavers with no history of joint diseases. Specimens (n = 72) were obtained from three distinct sections of the meniscus, namely anterior, center, posterior. Absorption spectra were acquired from each specimen in the VIS and NIR spectral range (400-1,100 nm). Following spectroscopic probing, the specimens were subjected to biochemical analyses to determine the matrix composition, that is water, hydroxyproline, and uronic acid contents. Multivariate analytical techniques, including principal component analysis (PCA) and partial least squares (PLS) regression, were then used to investigate the correlation between the matrix composition and it spectral response. Our results indicate that the optical absorption of meniscus matrix is related to its composition, and this relationship is optimal in the NIR spectral range (750-1,100 nm). High correlations (R(2) (uronic) = 86.9%, R(2) (water) = 83.8%, R(2) (hydroxyproline) = 81.7%, p < 0.0001) were obtained between the spectral predicted and measured meniscus composition, thus suggesting that spectral data in the NIR range can be utilized for estimating the matrix composition of human meniscus. In conclusion, optical spectroscopy, particularly in the NIR spectral range, is a potential method for evaluating the composition of human meniscus. This presents a promising technique for rapid and nondestructive evaluation of meniscus integrity in real-time during arthroscopic surgery.

Impact of experimental setup parameters on the measurement of articular cartilage optical properties in the visible and short near-infrared spectral bands

Publisher: Optica Publishing Group

Date: 15-06-2023

DOI: 10.1364/BOE.488801

Abstract: There is increasing research on the potential application of diffuse optical spectroscopy and hyperspectral imaging for characterizing the health of the connective tissues, such as articular cartilage, during joint surgery. These optical techniques facilitate the rapid and objective diagnostic assessment of the tissue, thus providing unprecedented information toward optimal treatment strategy. Adaption of optical techniques for diagnostic assessment of musculoskeletal disorders, including osteoarthritis, requires precise determination of the optical properties of connective tissues such as articular cartilage. As every indirect method of tissue optical properties estimation consists of a measurement step followed by a computational analysis step, there are parameters associated with these steps that could influence the estimated values of the optical properties. In this study, we report the absorption and reduced scattering coefficients of articular cartilage in the spectral band of 400-1400 nm. We assess the impact of the experimental setup parameters, including surrounding medium, s le volume, and scattering anisotropy factor on the reported optical properties. Our results suggest that the absorption coefficient of articular cartilage is sensitive to the variation in the surrounding medium, whereas its reduced scattering coefficient is invariant to the experimental setup parameters.

Optical absorption spectra of human articular cartilage correlate with biomechanical properties, histological score and biochemical composition

Publisher: IOP Publishing

Date: 06-08-2015

DOI: 10.1088/0967-3334/36/9/1913

Abstract: This study investigates the relationship between the optical response of human articular cartilage in the visible (VIS) and near infrared (NIR) spectral range and its matrix properties.Full-thickness osteochondral cores (dia. = 16 mm, n = 50) were extracted from human cadaver knees (N = 13) at four anatomical locations and ided into quadrants. Absorption spectra were acquired in the spectral range 400-1100 nm from one quadrant. Reference biomechanical, biochemical composition, histological, and cartilage thickness measurements were obtained from two other quadrants. A multivariate statistical technique based on partial least squares (PLS) regression was then employed to investigate the correlation between the absorption spectra and tissue properties.Our results demonstrate that cartilage optical response correlates with its function, composition and morphology, as indicated by the significant relationship between spectral predicted and measured biomechanical (79.0% ⩽ R(2) ⩽ 80.3%, p < 0.0001), biochemical (65.1% ⩽ R(2) ⩽ 81.0%, p < 0.0001), and histological scores ([Formula: see text] = 83.3%, p < 0.0001) properties. Significant correlation was also obtained with the non-calcified cartilage thickness ([Formula: see text] = 83.2%, p < 0.0001).We conclude that optical absorption of human cartilage in the VIS and NIR spectral range correlates with the overall tissue properties, thus providing knowledge that could facilitate development of systems for rapid assessment of tissue integrity.

Near-infrared (NIR) spectroscopic evaluation of articular cartilage: A review of current and future trends

Publisher: Informa UK Limited

Date: 20-10-2016

DOI: 10.1080/05704928.2016.1250010

Multi-spectral fiber spectroscopy methods as solutions for label-free medical diagnostics (Conference Presentation)

Publisher: SPIE

Date: 04-03-2019

DOI: 10.1117/12.2509174

Combination of optical coherence tomography and near infrared spectroscopy enhances determination of articular cartilage composition and structure

Publisher: Springer Science and Business Media LLC

Date: 06-09-2017

DOI: 10.1038/S41598-017-10973-Z

Abstract: Conventional arthroscopic evaluation of articular cartilage is subjective and poorly reproducible. Therefore, implementation of quantitative diagnostic techniques, such as near infrared spectroscopy (NIRS) and optical coherence tomography (OCT), is essential. Locations ( n = 44) with various cartilage conditions were selected from mature equine fetlock joints ( n = 5). These locations and their surroundings were measured with NIRS and OCT ( n = 530). As a reference, cartilage proteoglycan (PG) and collagen contents, and collagen network organization were determined using quantitative microscopy. Additionally, lesion severity visualized in OCT images was graded with an automatic algorithm according to International Cartilage Research Society (ICRS) scoring system. Artificial neural network with variable selection was then employed to predict cartilage composition in the superficial and deep zones from NIRS data, and the performance of two models, generalized (including all s les) and condition-specific models (based on ICRS-grades), was compared. Spectral data correlated significantly ( p 0.002) with PG and collagen contents, and collagen orientation in the superficial and deep zones. The combination of NIRS and OCT provided the most reliable outcome, with condition-specific models having lower prediction errors (9.2%) compared to generalized models (10.4%). Therefore, the results highlight the potential of combining both modalities for comprehensive evaluation of cartilage during arthroscopy.

Near infrared (NIR) absorption spectra correlates with subchondral bone micro-CT parameters in osteoarthritic rat models

Publisher: Elsevier BV

Date: 04-2013

DOI: 10.1016/J.BONE.2012.12.042

Abstract: Determining the properties and integrity of subchondral bone in the developmental stages of osteoarthritis, especially in a form that can facilitate real-time characterization for diagnostic and decision-making purposes, is still a matter for research and development. This paper presents relationships between near infrared absorption spectra and properties of subchondral bone obtained from 3 models of osteoarthritic degeneration induced in laboratory rats via: (i) menisectomy (MSX) (ii) anterior cruciate ligament transaction (ACL) and (iii) intra-articular injection of mono-ido-acetate (1mg) (MIA), in the right knee joint, with 12 rats per model group (N=36). After 8weeks, the animals were sacrificed and knee joints were collected. A custom-made diffuse reflectance NIR probe of diameter 5mm was placed on the tibial surface and spectral data were acquired from each specimen in the wavenumber range 4000-12500cm(-1). After spectral acquisition, micro computed tomography (micro-CT) was performed on the s les and subchondral bone parameters namely: bone volume (BV) and bone mineral density (BMD) were extracted from the micro-CT data. Statistical correlation was then conducted between these parameters and regions of the near infrared spectra using multivariate techniques including principal component analysis (PCA), discriminant analysis (DA), and partial least squares (PLS) regression. Statistically significant linear correlations were found between the near infrared absorption spectra and subchondral bone BMD (R(2)=98.84%) and BV (R(2)=97.87%). In conclusion, near infrared spectroscopic probing can be used to detect, qualify and quantify changes in the composition of the subchondral bone, and could potentially assist in distinguishing healthy from OA bone as demonstrated with our laboratory rat models.

Mid-infrared and Near infrared spectroscopic analysis of mechanically and enzymatically damaged cartilage

Publisher: OSA

Date: 2019

DOI: 10.1364/BODA.2019.JT4A.37

Deep learning enables sleep staging from photoplethysmogram for patients with suspected sleep apnea

Publisher: Oxford University Press (OUP)

Date: 21-05-2020

DOI: 10.1093/SLEEP/ZSAA098

Abstract: Accurate identification of sleep stages is essential in the diagnosis of sleep disorders (e.g. obstructive sleep apnea [OSA]) but relies on labor-intensive electroencephalogram (EEG)-based manual scoring. Furthermore, long-term assessment of sleep relies on actigraphy differentiating only between wake and sleep periods without identifying specific sleep stages and having low reliability in identifying wake periods after sleep onset. To address these issues, we aimed to develop an automatic method for identifying the sleep stages from the photoplethysmogram (PPG) signal obtained with a simple finger pulse oximeter. PPG signals from the diagnostic polysomnographies of susptected OSA patients (n = 894) were utilized to develop a combined convolutional and recurrent neural network. The deep learning model was trained in idually for three-stage (wake/NREM/REM), four-stage (wake/N1+N2/N3/REM), and five-stage (wake/N1/N2/N3/REM) classification of sleep. The three-stage model achieved an epoch-by-epoch accuracy of 80.1% with Cohen’s κ of 0.65. The four- and five-stage models achieved 68.5% (κ = 0.54), and 64.1% (κ = 0.51) accuracies, respectively. With the five-stage model, the total sleep time was underestimated with a mean bias error (SD) of of 7.5 (55.2) minutes. The PPG-based deep learning model enabled accurate estimation of sleep time and differentiation between sleep stages with a moderate agreement to manual EEG-based scoring. As PPG is already included in ambulatory polygraphic recordings, applying the PPG-based sleep staging could improve their diagnostic value by enabling simple, low-cost, and reliable monitoring of sleep and help assess otherwise overlooked conditions such as REM-related OSA.

Arthroscopic Near-Infrared Spectroscopic Prediction of Human Meniscus Properties

Publisher: OSA

Date: 2019

DOI: 10.1364/BODA.2019.JT4A.35

Detailed Assessment of Sleep Architecture With Deep Learning and Shorter Epoch-to-Epoch Duration Reveals Sleep Fragmentation of Patients With Obstructive Sleep Apnea

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 07-2021

DOI: 10.1109/JBHI.2020.3043507

Near‐Infrared Spectroscopic Characterization of Cardiac and Renal Fibrosis in Fixed and Fresh Rat Tissue

Publisher: Wiley

Date: 11-08-2023

DOI: 10.1002/ANSE.202200030

Abstract: Clinical diagnosis of fibrosis is currently reliant on conventional methods. The current “gold standard” for fibrosis diagnosis is histological examination of a biopsy, which is labour intensive and requires extensive s le preparation. Here we show that a portable handheld near‐infrared spectrometer coupled with machine learning algorithms can discriminate between kidney and cardiac fibrosis in a rat model of kidney failure compared to healthy rats without kidney failure. The most significant changes in the spectra of fibrotic tissue included shifts in absorption bands at 1509, 1581, 1689 and 1725 nm attributed to collagen components. The best discrimination of fibrosis was achieved in kidney tissue (AUC=0.962), which showed a higher level of fibrosis compared to cardiac tissue (AUC=0.882). The results show the potential of the NIR spectroscopy to detect and to quantify fibrosis in the heart and kidney that in the future could be applied as an intraoperative surgical tool to guide surgical procedures.

A Comparison of the Histochemical and Image-Derived Proteoglycan Content of Articular Cartilage

Publisher: OMICS Publishing Group

Date: 2013

DOI: 10.4172/2161-0940.1000120

Infrared Fiber-Optic Spectroscopy Detects Bovine Articular Cartilage Degeneration

Publisher: SAGE Publications

Date: 20-02-2021

DOI: 10.1177/1947603521993221

Abstract: Joint injuries may lead to degeneration of cartilage tissue and initiate development of posttraumatic osteoarthritis. Arthroscopic surgeries can be used to treat joint injuries, but arthroscopic evaluation of articular cartilage quality is subjective. Fourier transform infrared spectroscopy combined with fiber optics and attenuated total reflectance crystal could be used for the assessment of tissue quality during arthroscopy. We hypothesize that fiber-optic mid-infrared spectroscopy can detect enzymatically and mechanically induced damage similar to changes occurring during progression of osteoarthritis. Bovine patellar cartilage plugs were extracted and degraded enzymatically and mechanically. Adjacent untreated s les were utilized as controls. Enzymatic degradation was done using collagenase and trypsin enzymes. Mechanical damage was induced by (1) dropping a weight impactor on the cartilage plugs and (2) abrading the cartilage surface with a rotating sandpaper. Fiber-optic mid-infrared spectroscopic measurements were conducted before and after treatments, and spectral changes were assessed with random forest, partial least squares discriminant analysis, and support vector machine classifiers. All models had excellent classification performance for detecting the different enzymatic and mechanical damage on cartilage matrix. Random forest models achieved accuracies between 90.3% and 77.8%, while partial least squares model accuracies ranged from 95.8% to 84.7%, and support vector machine accuracies from 91.7% to 80.6%. The results suggest that fiber-optic Fourier transform infrared spectroscopy attenuated total reflectance spectroscopy is a viable way to detect minor and major degeneration of articular cartilage. Objective measures provided by fiber-optic spectroscopic methods could improve arthroscopic evaluation of cartilage damage.

Characterization of connective tissues using near-infrared spectroscopy and imaging

Publisher: Springer Science and Business Media LLC

Date: 18-01-2021

DOI: 10.1038/S41596-020-00468-Z

Abstract: 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 s le 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 s le preparation and data analysis.

Multimodality scoring of chondral injuries in the equine fetlock joint ex vivo

Publisher: Elsevier BV

Date: 05-2017

DOI: 10.1016/J.JOCA.2016.12.007

Abstract: We investigate the potential of a prototype multimodality arthroscope, combining ultrasound, optical coherence tomography (OCT) and arthroscopic indentation device, for assessing cartilage lesions, and compare the reliability of this approach with conventional arthroscopic scoring ex vivo. Areas of interest (AIs, N = 43) were selected from equine fetlock joints (N = 5). Blind-coded AIs were independently scored by two equine surgeons employing International Cartilage Repair Society (ICRS) scoring system via conventional arthroscope and multimodality arthroscope, in which high-frequency ultrasound and OCT catheters were attached to an arthroscopic indentation device. In addition, cartilage stiffness was measured with the indentation device, and lesions in OCT images scored using custom-made automated software. Measurements and scorings were performed twice in two separate rounds. Finally, the scores were compared to histological ICRS scores. OCT and arthroscopic examinations showed the highest average agreements (55.2%) between the scoring by surgeons and histology scores, whereas ultrasound had the lowest (50.6%). Average intraobserver agreements of surgeons and interobserver agreements between rounds were, respectively, for conventional arthroscope (68.6%, 69.8%), ultrasound (68.6%, 68.6%), OCT (65.1%, 61.7%) and automated software (65.1%, 59.3%). OCT imaging supplemented with the automated software provided the most reliable lesion scoring. However, limited penetration depth of light limits the clinical potential of OCT in assessing human cartilage thickness thus, the combination of OCT and ultrasound could be optimal for reliable diagnostics. Present findings suggest imaging and quantitatively analyzing the entire articular surface to eliminate surgeon-related variation in the selection of the most severe lesion to be scored.

Front Cover: Near‐Infrared Spectroscopic Characterization of Cardiac and Renal Fibrosis in Fixed and Fresh Rat Tissue (Anal. Sens. 1/2023)

Publisher: Wiley

Date: 12-12-2023

DOI: 10.1002/ANSE.202200105

Near‐Infrared Spectroscopic Characterization of Cardiac and Renal Fibrosis in Fixed and Fresh Rat Tissue

Publisher: Wiley

Date: 13-12-2023

DOI: 10.1002/ANSE.202200106

Abstract: Invited for this month‘s cover are the collaborating group(s) of Center for Biospectroscopy at Monash University and Austin Health at the University of Melbourne, University of Eastern Finland and the University of Queensland. The cover‐art shows a handheld near‐infrared spectroscopic probe to detect fibrosis in real time using a murine model. More information can be found in the Research Article by John A. Adegoke, Jaishankar Raman, Bayden R. Wood, and co‐workers .

Arthroscopic Determination of Cartilage Proteoglycan Content and Collagen Network Structure with Near-Infrared Spectroscopy

Publisher: Springer Science and Business Media LLC

Date: 06-05-2019

DOI: 10.1007/S10439-019-02280-7

Corrigendum to “Multimodality scoring of chondral injuries in the equine fetlock joint ex vivo” [Osteoarthritis Cartilage 25 (5) (2017 May) 790–798]

Publisher: Elsevier BV

Date: 08-2017

DOI: 10.1016/J.JOCA.2017.05.010

Tissue optical properties combined with machine learning enables estimation of articular cartilage composition and functional integrity

Publisher: Optica Publishing Group

Date: 19-10-2020

DOI: 10.1364/BOE.402929

Abstract: Absorption and reduced scattering coefficients ( μ a , μ s ′ ) of biological tissues have shown significant potential in biomedical applications. Thus, they are effective parameters for the characterization of tissue integrity and provide vital information on the health of biological tissues. This study investigates the potential of optical properties ( μ a , μ s ′ ) for estimating articular cartilage composition and biomechanical properties using multivariate and machine learning techniques. The results suggest that μ a could optimally estimate cartilage proteoglycan content in the superficial zone, in addition to its equilibrium modulus. While μ s ′ could effectively estimate the proteoglycan content of the middle and deep zones in addition to the instantaneous and dynamic moduli of articular cartilage.

Biomaterial scaffolds in cartilage-subchondral bone defects influencing the repair of autologous articular cartilage transplants

Publisher: SAGE Publications

Date: 08-06-2013

DOI: 10.1177/0885328211431310

Abstract: The repair of articular cartilage typically involves the repair of cartilage–subchondral bone tissue defects. Although various bioactive materials have been used to repair bone defects, how these bioactive materials in subchondral bone defects influence the repair of autologous cartilage transplant remains unclear. The aim of this study was to investigate the effects of different subchondral biomaterial scaffolds on the repair of autologous cartilage transplant in a sheep model. Cylindrical cartilage–subchondral bone defects were created in the right femoral knee joint of each sheep. The subchondral bone defects were implanted with hydroxyapatite–β-tricalcium phosphate (HA–TCP), poly lactic-glycolic acid (PLGA)-HA–TCP dual-layered composite scaffolds (PLGA/HA–TCP scaffolds), or autologous bone chips. The autologous cartilage layer was placed on top of the subchondral materials. After 3 months, the effect of different subchondral scaffolds on the repair of autologous cartilage transplant was systematically studied by investigating the mechanical strength, structural integration, and histological responses. The results showed that the transplanted cartilage layer supported by HA–TCP scaffolds had better structural integration and higher mechanical strength than that supported by PLGA/HA–TCP scaffolds. Furthermore, HA–TCP-supported cartilage showed higher expression of acid mucosubstances and glycol-amino-glycan contents than that supported by PLGA/HA–TCP scaffolds. Our results suggested that the physicochemical properties, including the inherent mechanical strength and material chemistry of the scaffolds, play important roles in influencing the repair of autologous cartilage transplants. The study may provide useful information for the design and selection of proper subchondral biomaterials to support the repair of both subchondral bone and cartilage defects.

Near-infrared Spectroscopy: A Potential Tool for Mapping Meniscus Properties

Publisher: OSA

Date: 2018

DOI: 10.1364/TRANSLATIONAL.2018.JW3A.38

Characterizing human subchondral bone properties using near-infrared (NIR) spectroscopy

Publisher: Springer Science and Business Media LLC

Date: 27-06-2018

DOI: 10.1038/S41598-018-27786-3

Abstract: Degenerative joint conditions are often characterized by changes in articular cartilage and subchondral bone properties. These changes are often associated with subchondral plate thickness and trabecular bone morphology. Thus, evaluating subchondral bone integrity could provide essential insights for diagnosis of joint pathologies. This study investigates the potential of optical spectroscopy for characterizing human subchondral bone properties. Osteochondral s les (n = 50) were extracted from human cadaver knees (n = 13) at four anatomical locations and subjected to NIR spectroscopy. The s les were then imaged using micro-computed tomography to determine subchondral bone morphometric properties, including: plate thickness (Sb.Th), trabecular thickness (Tb.Th), volume fraction (BV/TV), and structure model index (SMI). The relationship between the subchondral bone properties and spectral data in the 1 st (650–950 nm), 2 nd (1100–1350 nm) and 3 rd (1600–1870 nm) optical windows were investigated using partial least squares (PLS) regression multivariate technique. Significant correlations (p 0.0001) and relatively low prediction errors were obtained between spectral data in the 1 st optical window and Sb.Th (R 2 = 92.3%, error = 7.1%), Tb.Th (R 2 = 88.4%, error = 6.7%), BV/TV (R 2 = 83%, error = 9.8%) and SMI (R 2 = 79.7%, error = 10.8%). Thus, NIR spectroscopy in the 1 st tissue optical window is capable of characterizing and estimating subchondral bone properties, and can potentially be adapted during arthroscopy.

Automated Preprocessing of Near Infrared Spectroscopic Data

Publisher: OSA

Date: 2019

DOI: 10.1364/BODA.2019.DS2A.6

Author Correction: Artificial neural network analysis of the oxygen saturation signal enables accurate diagnostics of sleep apnea

Publisher: Springer Science and Business Media LLC

Date: 13-03-2020

DOI: 10.1038/S41598-020-62003-0

Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Tribological efficacy and stability of phospholipid-based membrane lubricants in varying pH chemical conditions

Publisher: American Vacuum Society

Date: 04-01-2016

DOI: 10.1116/1.4939246

Abstract: In this study, the authors examine the influence of joint chemical environment by measuring changes in the tribological properties (friction coefficient and charge density) of contacting surfaces of normal and degenerated cartilage s les in bath solutions of varying pH (2.0–9.0). Bovine articular cartilage s les (n = 54) were subjected to several surface measurements, including interfacial energy, contact angle, and friction coefficient, at varying pH. The s les were delipidized and then subjected to the same measurement protocols. Our results reveal that the interfacial energy and charge density, which have been shown to be related to friction coefficient, decrease with pH in the acidic range and approach constant values at physiological (or synovial fluid) pH of 7.4 and beyond it, i.e., toward basic pH domain. The authors conclude that this rather complex response explains the long-term efficacy with respect to ageing and associated pH changes, of the phospholipid layers that facilitate the almost frictionless, hydration–lubrication involving contact in the mammalian musculoskeletal system.

Spatial mapping of proteoglycan content in articular cartilage using near-infrared (NIR) spectroscopy

Publisher: The Optical Society

Date: 15-12-2015

DOI: 10.1364/BOE.6.000144

Refractive index of human articular cartilage varies with tissue structure and composition.

Publisher: Optica Publishing Group

Date: 23-10-2023

DOI: 10.1364/JOSAA.498722

Near-infrared Spectroscopy Based Arthroscopic Evaluation of Human Knee Joint Cartilage, Through Automated Selection of an Anatomically Specific Regression Model

Publisher: OSA

Date: 2018

DOI: 10.1364/OTS.2018.OF4D.3

Accurate Deep Learning-Based Sleep Staging in a Clinical Population with Suspected Obstructive Sleep Apnea

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 2019

DOI: 10.1109/JBHI.2019.2951346

A new mechanical indentation framework for functional assessment of articular cartilage

Publisher: Elsevier BV

Date: 05-2018

DOI: 10.1016/J.JMBBM.2018.02.028

Abstract: The conventional mechanical properties of articular cartilage, such as compressive stiffness, have been shown to have limited capacity to distinguish visually normal from degraded cartilage s les. In this study, a new mechanical indentation framework for assessing functional properties of articular cartilage during loading/unloading, i.e. deformation and recovery, was established. The capacity of a ring-shaped indenter integrated with an ultrasound transducer to distinguish mechanically intact from proteoglycan-depleted tissue was investigated. To achieve this, normal and enzymatically degraded bovine osteochondral s les were subjected to loading/unloading while the response of the tissue at the middle was captured by ultrasound at the same time. The enzymatic degradation model was characterized by amount of proteoglycan content, glycosaminoglycan release and proteomic analysis. The mechanical response of a wider continuum of articular cartilage in the loaded area and its surrounding region was captured in this framework leading to investigate two parameters, L and TS, related to the surrounding tissue of the loaded area for functional assessment of cartilage. L is the distance between the ultrasound transducer and articular cartilage surface and TS is the transient strain of articular cartilage during loading and unloading. Classification Analysis based on Principal Component Analysis was used to investigate the capacity of the new parameters to assess the functionality of the tissue. Multivariate statistics based on Partial Least Squares regression was employed to identify the correlation between the response of the tissue in the indented area and its surrounding cartilage. The results of this study indicate that L during loading (deformation) can differentiate normal and mildly proteoglycan-depleted s les from severely depleted s les and L during unloading (recovery) can distinguish between normal and proteoglycan-depleted tissue. However, TS during deformation and recovery is unable to discriminate normal cartilage s les from proteoglycan-depleted tissue. The results also demonstrate a strong correlation between mechanical properties of the loaded area with the response of its surrounding cartilage during recovery. It is therefore concluded that L in this newly established framework can discriminate between normal and proteoglycan-depleted cartilage s les. However, more s les will be needed to verify the demarcation between s les degraded for varying amount of time.

Spectroscopic Evaluation of Post-Traumatic Osteoarthritis in Shetland Ponies

Publisher: OSA

Date: 2018

DOI: 10.1364/OTS.2018.OTU4D.5

Mid-infrared Spectroscopic Assessment of Cartilage Degeneration

Publisher: OSA

Date: 2019

DOI: 10.1364/BODA.2019.DS1A.3

Potential enhancement of articular cartilage histological grading with collagen integrity

Publisher: Elsevier BV

Date: 07-2018

DOI: 10.1016/J.CLINBIOMECH.2018.04.016

Abstract: Histological evaluation of articular cartilage, such as using the Mankin scoring system, is the gold standard for characterization of tissue integrity. This scoring system takes into account several parameters indicative of the tissue's health however, the collagen integrity, which is a primary indicator of cartilage health is not taken into consideration. Thus, there is need to enhance histological grading of articular cartilage by incorporating explicit scoring of collagen degeneration into the Modified Mankin grading system. This paper explores a new histological grading parameter for collagen network degradation and how this information can be used to augment a widely used grading scheme like the Modified Mankin grading system. Intact and degenerated human cartilage were examined histologically and then subjected to second harmonic generation imaging, leading to qualitative and quantitative description of collagen disruption emanating from the surface to subsurface layers of the tissue. This data was then incorporated into the Modified Mankin grading system. Second harmonic generation image analysis reveals a relationship between changes in collagen architecture and histologically observed tissue disruption in degenerated articular cartilage. Histological tissue disruption in degenerated human articular cartilage is directly related to the reorganization of collagen fibrils in the form of intense fibril aggregation, either as a result of degeneration or aging. This method of mapping disrupted tissue regions to quantitative collagen fibril damage can be coded into cartilage grading systems and could inform clinical practice and scientific research.

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

Publisher: Springer Science and Business Media LLC

Date: 07-09-2018

DOI: 10.1038/S41598-018-31670-5

Abstract: 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 ex le, when conducting orthopaedic repair surgeries.

Raman spectroscopy is sensitive to biochemical changes related to various cartilage injuries

Publisher: Wiley

Date: 07-01-2021

DOI: 10.1002/JRS.6062

Machine Learning Classification of Articular Cartilage Integrity Using Near Infrared Spectroscopy

Publisher: Springer Science and Business Media LLC

Date: 09-03-2020

DOI: 10.1007/S12195-020-00612-5

Abstract: Assessment of cartilage integrity during arthroscopy is limited by the subjective visual nature of the technique. To address this shortcoming in diagnostic evaluation of articular cartilage, near infrared spectroscopy (NIRS) has been proposed. In this study, we evaluated the capacity of NIRS, combined with machine learning techniques, to classify cartilage integrity. Rabbit ( n = 14) knee joints with artificial injury, induced via unilateral anterior cruciate ligament transection (ACLT), and the corresponding contra-lateral (CL) joints, including joints from separate non-operated control (CNTRL) animals ( n = 8), were used. After sacrifice, NIR spectra (1000–2500 nm) were acquired from different anatomical locations of the joints ( n TOTAL = 313: n CNTRL = 111, n CL = 97, n ACLT = 105). Machine and deep learning methods (support vector machines–SVM, logistic regression–LR, and deep neural networks–DNN) were then used to develop models for classifying the s les based solely on their NIR spectra. The results show that the model based on SVM is optimal of distinguishing between ACLT and CNTRL s les (ROC_AUC = 0.93, kappa = 0.86), LR is capable of distinguishing between CL and CNTRL s les (ROC_AUC = 0.91, kappa = 0.81), while DNN is optimal for discriminating between the different classes (multi-class classification, kappa = 0.48). We show that NIR spectroscopy, when combined with machine learning techniques, is capable of holistic assessment of cartilage integrity, with potential for accurately distinguishing between healthy and diseased cartilage.

Articular cartilage optical properties in the near-infrared (NIR) spectral range vary with depth and tissue integrity

Publisher: Optica Publishing Group

Date: 07-09-2021

DOI: 10.1364/BOE.430053

Abstract: Optical properties of biological tissues in the NIR spectral range have demonstrated significant potential for in vivo diagnostic applications and are critical parameters for modelling light interaction in biological tissues. This study aims to investigate the optical properties of articular cartilage as a function of tissue depth and integrity. The results suggest consistent wavelength-dependent variation in optical properties between cartilage depth-wise zones, as well as between healthy and degenerated tissue. Also, statistically significant differences (p .05) in both optical properties were observed between the different cartilage depth-wise zones and as a result of tissue degeneration. When taken into account, the outcome of this study could enable accurate modelling of light interaction in cartilage matrix and could provide useful diagnostic information on cartilage integrity.

Near-infrared spectroscopy enables quantitative evaluation of human cartilage biomechanical properties during arthroscopy

Publisher: Elsevier BV

Date: 08-2019

DOI: 10.1016/J.JOCA.2019.04.008

Abstract: To investigate the feasibility of near-infrared (NIR) spectroscopy (NIRS) for evaluation of human articular cartilage biomechanical properties during arthroscopy. A novel arthroscopic NIRS probe designed in our research group was utilized by an experienced orthopedic surgeon to measure NIR spectra from articular cartilage of human cadaver knee joints (ex vivo, n = 18) at several measurement locations during an arthroscopic surgery. Osteochondral s les (n = 265) were extracted from the measurement sites for reference analysis. NIR spectra were remeasured in a controlled laboratory environment (in vitro), after which the corresponding cartilage thickness and biomechanical properties were determined. Hybrid multivariate regression models based on principal component analysis and linear mixed effects modeling (PCA-LME) were utilized to relate cartilage in vitro spectra and biomechanical properties, as well as to account for the spatial dependency. Additionally, a k-nearest neighbors (kNN) classifier was employed to reject outlying ex vivo NIR spectra resulting from a non-optimal probe-cartilage contact. Model performance was evaluated for both in vitro and ex vivo NIR spectra via Spearman's rank correlation (ρ) and the ratio of performance to interquartile range (RPIQ). Regression models accurately predicted cartilage thickness and biomechanical properties from in vitro NIR spectra (Model: 0.77 ≤ ρ ≤ 0.87, 2.03 ≤ RPIQ ≤ 3.0 Validation: 0.74 ≤ ρ ≤ 0.84, 1.87 ≤ RPIQ ≤ 2.90). When predicting cartilage properties from ex vivo NIR spectra (0.33 ≤ ρ ≤ 0.57 and 1.02 ≤ RPIQ ≤ 2.14), a kNN classifier enhanced the accuracy of predictions (0.52 ≤ ρ ≤ 0.87 and 1.06 ≤ RPIQ ≤ 1.88). Arthroscopic NIRS could substantially enhance identification of damaged cartilage by enabling quantitative evaluation of cartilage biomechanical properties. The results demonstrate the capacity of NIRS in clinical applications.

Artificial neural network analysis of the oxygen saturation signal enables accurate diagnostics of sleep apnea

Publisher: Springer Science and Business Media LLC

Date: 13-09-2019

DOI: 10.1038/S41598-019-49330-7

Abstract: The severity of obstructive sleep apnea (OSA) is classified using apnea-hypopnea index (AHI). Accurate determination of AHI currently requires manual analysis and complicated registration setup making it expensive and labor intensive. Partially for these reasons, OSA is a heavily underdiagnosed disease as only 7% of women and 18% of men suffering from OSA have diagnosis. To resolve these issues, we introduce an artificial neural network (ANN) that estimates AHI and oxygen desaturation index (ODI) using only the blood oxygen saturation signal (SpO2), recorded during ambulatory polygraphy, as an input. Therefore, hypopneas associated only with an arousal were not considered in this study. SpO2 signals from 1692 patients were used for training and 99 for validation. Two test sets were used consisting of 198 and 1959 patients. In the primary test set, the median absolute errors of ANN estimated AHI and ODI were 0.78 events/hour and 0.68 events/hour respectively. Based on the ANN estimated AHI and ODI, 90.9% and 94.4% of the test patients were classified into the correct OSA severity category. In conclusion, AHI and ODI can be reliably determined using neural network analysis of SpO2 signal. The developed method may enable a more affordable screening of OSA.

The role of lamellate phospholipid bilayers in lubrication of joints

Publisher: Institute of Machine Design and Operation, Wrocław University of Technology, Wrocław

Date: 2012

DOI: 10.5277/ABB120411

Structural, compositional, and functional effects of blunt and sharp cartilage damage on the joint: A 9‐month equine groove model study

Publisher: Wiley

Date: 23-01-2021

DOI: 10.1002/JOR.24971

Abstract: This study aimed to quantify the long‐term progression of blunt and sharp cartilage defects and their effect on joint homeostasis and function of the equine carpus. In nine adult Shetland ponies, the cartilage in the radiocarpal and middle carpal joint of one front limb was grooved (blunt or sharp randomized). The ponies were subjected to an 8‐week exercise protocol and euthanized at 39 weeks. Structural and compositional alterations in joint tissues were evaluated in vivo using serial radiographs, synovial biopsies, and synovial fluid s les. Joint function was monitored by quantitative gait analysis. Macroscopic, microscopic, and biomechanical evaluation of the cartilage and assessment of subchondral bone parameters were performed ex vivo. Grooved cartilage showed higher OARSI microscopy scores than the contra‐lateral sham‐operated controls ( p 0.0001). Blunt‐grooved cartilage scored higher than sharp‐grooved cartilage ( p = 0.007) and fixed charge density around these grooves was lower ( p = 0.006). Equilibrium and instantaneous moduli trended lower in grooved cartilage than their controls (significant for radiocarpal joints). Changes in other tissues included a threefold to sevenfold change in interleukin‐6 expression in synovium from grooved joints at week 23 ( p = 0.042) and an increased CPII/C2C ratio in synovial fluid extracted from blunt‐grooved joints at week 35 ( p = 0.010). Gait analysis outcome revealed mild, gradually increasing lameness. In conclusion, blunt and, to a lesser extent, sharp grooves in combination with a period of moderate exercise, lead to mild degeneration in equine carpal cartilage over a 9‐month period, but the effect on overall joint health remains limited.

Monitoring osteoarthritis progression using near infrared (NIR) spectroscopy

Publisher: Springer Science and Business Media LLC

Date: 13-09-2017

DOI: 10.1038/S41598-017-11844-3

Abstract: 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 s les 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 s les’ 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& Mankin =2) and advanced (weeks 4& Mankin = ) cartilage degeneration. In addition, the spectral data contains information that enables estimation of the tissue’s Mankin score (error = 12.6%, R 2 = 86.2%) and GAG content (error = 7.6%, R 2 = 95%). We conclude that NIR spectroscopy is a viable tool for assessing cartilage degeneration post-injury, such as, post-traumatic osteoarthritis.

Near Infrared Spectroscopic Mapping of Functional Properties of Equine Articular Cartilage

Publisher: Springer Science and Business Media LLC

Date: 27-05-2016

DOI: 10.1007/S10439-016-1659-6

Abstract: Mechanical properties of articular cartilage are vital for normal joint function, which can be severely compromised by injuries. Quantitative characterization of cartilage injuries, and evaluation of cartilage stiffness and thickness by means of conventional arthroscopy is poorly reproducible or impossible. In this study, we demonstrate the potential of near infrared (NIR) spectroscopy for predicting and mapping the functional properties of equine articular cartilage at and around lesion sites. Lesion and non-lesion areas of interests (AI, N = 44) of equine joints (N = 5) were ided into grids and NIR spectra were acquired from all grid points (N = 869). Partial least squares (PLS) regression was used to investigate the correlation between the absorbance spectra and thickness, equilibrium modulus, dynamic modulus, and instantaneous modulus at the grid points of 41 AIs. Subsequently, the developed PLS models were validated with spectral data from the grid points of 3 independent AIs. Significant correlations were obtained between spectral data and cartilage thickness (R

Dataset on equine cartilage near infrared spectra, composition, and functional properties

Publisher: Springer Science and Business Media LLC

Date: 30-08-2019

DOI: 10.1038/S41597-019-0170-Y

Abstract: Near infrared (NIR) spectroscopy is a well-established technique that is widely employed in agriculture, chemometrics, and pharmaceutical engineering. Recently, the technique has shown potential in clinical orthopaedic applications, for ex le, assisting in the diagnosis of various knee-related diseases ( e . g ., osteoarthritis) and their pathologies. NIR spectroscopy (NIRS) could be especially useful for determining the integrity and condition of articular cartilage, as the current arthroscopic diagnostics is subjective and unreliable. In this work, we present an extensive dataset of NIRS measurements for evaluating the condition, mechanical properties, structure, and composition of equine articular cartilage. The dataset contains NIRS measurements from 869 different locations across the articular surfaces of five equine fetlock joints. A comprehensive library of reference values for each measurement location is also provided, including results from a mechanical indentation testing, digital densitometry imaging, polarized light microscopy, and Fourier transform infrared spectroscopy. The published data can either be used as a model of human cartilage or to advance equine veterinary research.

Near Infrared for Non-Destructive Testing of Articular Cartilage

Publisher: Springer Netherlands

Date: 30-09-2011

DOI: 10.1007/978-94-007-0723-8_58

3D T₁ relaxation time measurements in an equine model of subtle post‐traumatic osteoarthritis using MB‐SWIFT

Publisher: Wiley

Date: 31-05-2023

DOI: 10.1002/JOR.25629

Abstract: The aim of this study is to assess whether articular cartilage changes in an equine model of post‐traumatic osteoarthritis (PTOA), induced by surgical creation of standard (blunt) grooves, and very subtle sharp grooves, could be detected with ex vivo T 1 relaxation time mapping utilizing three‐dimensional (3D) readout sequence with zero echo time. Grooves were made on the articular surfaces of the middle carpal and radiocarpal joints of nine mature Shetland ponies and osteochondral s les were harvested at 39 weeks after being euthanized under respective ethical permissions. T 1 relaxation times of the s les ( n = 8 + 8 for experimental and n = 12 for contralateral controls) were measured with a variable flip angle 3D multiband‐sweep imaging with Fourier transform sequence. Equilibrium and instantaneous Young's moduli and proteoglycan (PG) content from OD of Safranin‐O‐stained histological sections were measured and utilized as reference parameters for the T 1 relaxation times. T 1 relaxation time was significantly ( p 0.05) increased in both groove areas, particularly in the blunt grooves, compared with control s les, with the largest changes observed in the superficial half of the cartilage. T 1 relaxation times correlated weakly ( R s ≈ 0.33) with equilibrium modulus and PG content ( R s ≈ 0.21). T 1 relaxation time in the superficial articular cartilage is sensitive to changes induced by the blunt grooves but not to the much subtler sharp grooves, at the 39‐week timepoint post‐injury. These findings support that T 1 relaxation time has potential in detection of mild PTOA, albeit the most subtle changes could not be detected.

Can Proteoglycan Change in Articular Cartilage be Detected by Ultrasound Evaluation?

Publisher: Springer Netherlands

Date: 30-09-2011

DOI: 10.1007/978-94-007-0723-8_57

Effects of body mass on microstructural features of the osteochondral unit: A comparative analysis of 37 mammalian species

Publisher: Elsevier BV

Date: 10-2019

DOI: 10.1016/J.BONE.2019.07.001

Abstract: Since Galileo's days the effect of size on the anatomical characteristics of the structural elements of the body has been a subject of interest. However, the effects of scaling at tissue level have received little interest and virtually no data exist on the subject with respect to the osteochondral unit in the joint, despite this being one of the most lesion-prone and clinically relevant parts of the musculoskeletal system. Imaging techniques, including Fourier transform infrared imaging, polarized light microscopy and micro computed tomography, were combined to study the response to increasing body mass of the osteochondral unit. We analyzed the effect of scaling on structural characteristics of articular cartilage, subchondral plate and the supporting trabecular bone, across a wide range of mammals at microscopic level. We demonstrated that, while total cartilage thickness scales to body mass in a negative allometric fashion, thickness of different cartilage layers did not. Cartilage tissue layers were found to adapt to increasing loads principally in the deep zone with the superficial layers becoming relatively thinner. Subchondral plate thickness was found to have no correlation to body mass, nor did bone volume fraction. The underlying trabecular bone was found to have thicker trabeculae (r=0.75, p<0.001), as expected since this structure carries most loads and plays a role in force mitigation. The results of this study suggest that the osteochondral tissue structure has remained remarkably preserved across mammalian species during evolution, and that in particular, the trabecular bone carries the adaptation to the increasing body mass.

Impact of Nanoparticle Uptake on the Biophysical Properties of Cell for Biomedical Engineering Applications

Publisher: Springer Science and Business Media LLC

Date: 10-04-2019

DOI: 10.1038/S41598-019-42225-7

Abstract: Nanomaterials are currently the state-of-the-art in the development of advanced biomedical devices and applications where classical approaches have failed. To date, majority of the literature on nanomaterial interaction with cells have largely focused on the biological responses of cells obtained via assays, with little interest on their biophysical responses. However, recent studies have shown that the biophysical responses of cells, such as stiffness and adhesive properties, play a significant role in their physiological function. In this paper, we investigate cell biophysical responses after uptake of nanoparticles. Atomic force microscopy was used to study changes in cell stiffness and adhesion upon boron nitride (BN) and hydroxyapatite (HAP) nanoparticle uptake. Results show increase in cell stiffness with varying nanoparticle (BN and HAP) concentration, while a decrease in cell adhesion trigger by uptake of HAP. In addition, changes in the biochemical response of the cell membrane were observed via Raman spectroscopy of nanoparticle treated cells. These findings have significant implications in biomedical applications of nanoparticles, e.g. in drug delivery, advanced prosthesis and surgical implants.

University Of Queensland

Location: Australia

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University Of Eastern Finland

Location: Finland

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University Of Lagos

Location: Nigeria

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Queensland University Of Technology

Location: Australia

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Computational Modelling In Spectroscopic Characterization Of Connective Tissues In Osteoarthritis (COMPaCT)

Start Date: 2018

End Date: 2023

Funder: Academy of Finland

Near Infrared Spectroscopy For Arthroscopic Diagnostics Of Cartilage And Meniscus Degeneration

Start Date: 2016

End Date: 2019

Funder: Suomen Kulttuurirahasto

Computational Modelling In Spectroscopic Characterization Of Connective Tissues In Osteoarthritis (COMPaCT)

Start Date: 2018

End Date: 2021

Funder: Academy of Finland

Discovery Projects - Grant ID: DP210103342

Start Date: 05-2021

End Date: 05-2024

Amount: $473,712.00

Funder: Australian Research Council