Near Infrared Spectroscopic Mapping of Functional Properties of Equine Articular Cartilage

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 divided 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 = 70.3%, p< 0.0001), equilibrium modulus (R = 67.8%, p< 0.0001), dynamic modulus (R = 68.9%, p< 0.0001) and instantaneous modulus (R = 41.8%, p< 0.0001). Relatively low errors were observed in the predicted thickness (5.9%) and instantaneous modulus (9.0%) maps. Thus, if well implemented, NIR spectroscopy could enable arthroscopic evaluation and mapping of cartilage functional properties at and around lesion sites.

Machine Learning Classification of Articular Cartilage Integrity Using Near Infrared Spectroscopy

“…There has been growing interest in utilizing fast optical methods, particularly near infrared spectroscopy (NIRS), for the evaluation of cartilage conditions. 1,2,[5][6][7]19,22,27,28,33 NIRS is capable of characterizing cartilage physical 5,27 and functional 6,27 properties, and composition. 1,22,28 Furthermore, NIRS has been proposed for assessing 4,23,32 cartilage integrity and monitoring the progression of OA using an animal model, 3 which provides in vivo and ex vivo data during methods development and optimization.…”

“…Classification of cartilage integrity based on NIRS harnesses the capacity of the spectrum, which encodes latent and inherent properties of the cartilage matrix, to provide a holistic assessment of the tissue. For example, features in the spectrum, such as spectral peaks and shapes and shapes due to absorption and scattering associated with the composition and structure of cartilage, encode information on tissue thickness 5 and biomechanical 27 properties. In this study, we compared the performance of traditional machine learning techniques, including support vector machines (SVM) and logistic regression (LR), with deep learning methods, particularly deep neural networks (DNN), for classification of cartilage integrity based on NIRS.…”

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

“…Also, the determination of cartilage stiffness with the arthroscopic device (Artscan 200) was found to be time-consuming and prone to errors related to the need for perpendicular alignment of the indenter against the articular surface as observed by the high CV between the rounds. Based on the recent studies a rapid nondestructive method, such as NIR spectroscopy 15,19 , could be one feasible solution for estimation of cartilage mechanical properties.…”

“…Several non-destructive techniques, including intra-articular ultrasound (US) 13,16 , optical coherence tomography (OCT) 14,17 , near infrared (NIR) spectroscopy 15,18,19 and arthroscopic indentation 20,21 , have been proposed for arthroscope guided quantitative and objective evaluation of cartilage integrity. US and OCT provide cross-sectional images of tissue structure, but are also complementary to each other: the superior resolution of OCT enables the high-resolution characterization of the articular surface, whereas US provides detailed information on the inner structures of cartilage 22 and enables subchondral bone evaluation 13 .…”

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

“…This study was conducted on NIR spectral data collected from equine cartilage, used in an earlier study. 33 Near infrared (NIR) spectral measurements were performed three times (with realignment of the measurement probe) on all 869 points, and the three measurements were averaged for each point. The biomechanical measurements were conducted once due to long protocol times.…”