The development of treatments for osteoarthritis (OA) is burdened by the lack of standardized biomarkers of cartilage health that can be applied in clinical trials. We present a novel arthroscopic Raman probe that can "optically biopsy" cartilage and quantify key extracellular matrix (ECM) biomarkers for determining cartilage composition, structure, and material properties in health and disease. Technological and analytical innovations to optimize Raman analysis include (1) multivariate decomposition of cartilage Raman spectra into ECM-constituent-specific biomarkers (glycosaminoglycan [GAG], collagen [COL], water [H 2 O] scores), and (2) multiplexed polarized Raman spectroscopy to quantify superficial zone (SZ) COL anisotropy via a partial least squares-discriminant analysisderived Raman collagen alignment factor (RCAF). Raman measurements were performed on a series of ex vivo cartilage models: (1) chemically GAG-depleted bovine cartilage explants (n = 40), (2) mechanically abraded bovine cartilage explants (n = 30), (3) aging human cartilage explants (n = 14), and (4) anatomical-site-varied ovine osteochondral explants (n = 6). Derived Raman GAG score biomarkers predicted 95%, 66%, and 96% of the variation in GAG content of GAG-depleted bovine explants, human explants, and ovine explants, respectively (p < 0.001). RCAF values were significantly different for explants with abrasion-induced SZ COL loss (p < 0.001). The multivariate linear regression of Raman-derived ECM biomarkers (GAG and H 2 O scores) predicted 94% of the variation in elastic modulus of ovine explants (p < 0.001). Finally, we demonstrated the first in vivo Raman arthroscopy assessment of an ovine femoral condyle through intraarticular entry into the synovial capsule. This study advances Raman arthroscopy toward a transformative low-cost, minimally invasive diagnostic platform for objective monitoring of treatment outcomes from emerging OA therapies.
The development of treatments for osteoarthritis (OA) is burdened by the lack of standardized biomarkers of cartilage health that can be applied in clinical trials. We present a novel arthroscopic Raman probe that can optically biopsy cartilage and quantify key ECM biomarkers for determining cartilage composition, structure, and material properties in health and disease. Technological and analytical innovations to optimize Raman analysis include: 1) multivariate decomposition of cartilage Raman spectra into ECM-constituent-specific biomarkers (glycosaminoglycan [GAG], collagen [COL], water [H2O] scores), and 2) multiplexed polarized Raman spectroscopy to quantify superficial zone collagen anisotropy via a PLS-DA-derived Raman collagen alignment factor (RCAF). Raman measurements were performed on a series of ex vivo cartilage models: 1) chemically GAG-depleted bovine cartilage explants (n=40), 2) mechanically abraded bovine cartilage explants (n=30), 3) aging human cartilage explants (n=14), and 4) anatomical-site-varied ovine osteochondral explants (n=6). Derived Raman GAG score biomarkers predicted 95%, 66%, and 96% of the variation in GAG content of GAG-depleted bovine explants, human explants, and ovine explants, respectively (p<0.001). RCAF values were significantly different for explants with abrasion-induced superficial zone collagen loss (p<0.001). The multivariate linear regression of Raman-derived ECM biomarkers (GAG and H2O scores) predicted 94% of the variation in elastic modulus of ovine explants (p<0.001). Finally, we demonstrated the first in vivo Raman arthroscopy assessment of an ovine femoral condyle through intraarticular entry into the synovial capsule. This work advances Raman arthroscopy towards a transformative low cost, minimally invasive diagnostic platform for objective monitoring of treatment outcomes from emerging OA therapies.
This study examines the theoretical foundations for the damage mechanics of biological tissues in relation to viscoelasticity. Its primary goal is to provide a mechanistic understanding of well-known experimental observations in biomechanics, which show that the ultimate tensile strength of viscoelastic biological tissues typically increases with increasing strain rate. The basic premise of this framework is that tissue damage occurs when strong bonds, such as covalent bonds in the solid matrix of a biological tissue, break in response to loading. This type of failure is described as elastic damage, under the idealizing assumption that strong bonds behave elastically. Viscoelasticity arises from three types of dissipative mechanisms: (1) Friction between molecules of the same species, which is represented by the tissue viscosity. (2) Friction between fluid and solid constituents of a porous medium, which is represented by the tissue hydraulic permeability. (3) Dissipative reactions arising from weak bonds breaking in response to loading, and reforming in a stress-free state, such as hydrogen bonds and other weak electrostatic bonds. When a viscoelastic tissue is subjected to loading, some of that load may be temporarily supported by those frictional and weak bond forces, reducing the amount of load supported by elastic strong bonds and thus, the extent of elastic damage sustained by those bonds. This protective effect depends on the characteristic time response of viscoelastic mechanisms in relation to the loading history. This study formalizes these concepts by presenting general equations that can model the damage mechanics of viscoelastic tissues.
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