K. Emanuel (Maastricht, NL)
Maastricht UniversityPresenter Of 2 Presentations
P015 - Feasibility of Near-Infrared Reflective Spectroscopy to Measure Local Variations in Cartilage Quality: A Human and Animal Cadaveric Study
Abstract
Purpose
There is a clinical demand for a tool for peri-surgical, non-destructive evaluation of local cartilage quality. Such a tool can be used for evaluation of treatment necessity, determination of (viable) borders of a cartilage defect, and evaluation of repair tissue during second-look surgeries. Therefore, the aim of this study was to assess the feasibility of near-infrared spectroscopy as a tool for non-destructive, minimally-invasive measurement of cartilage quality.
Methods and Materials
A custom-developed 2-mm optical-fibre probe was attached to a 350-1830nm wavelength spectrometer. 450 diffuse reflectance spectra were obtained from 90 cartilage sites on eight fresh-frozen human cadaveric knees. Local glycosaminoglycan, hydroxyproline and water content; cartilage thickness; Young’s modulus (using micro-indentation); T1rho and T2-mapping MRI images; and macroscopic osteoarthritis score were obtained. With 35 spectral features, related to water, lipids and blood, a linear regression model was used to assess the relation to physiological outcome parameters. Moreover, a linear discriminant classification model was used to study the discriminative power between weight-bearing and non-weight-bearing areas. Additionally, in a mini-pig cartilage-defect model, the difference between defect and nearby control areas (40 measurements over 8 defects) was classified directly post-mortem.
Results
The linear models showed the best correlation with osteoarthritis score (R2=0.72), cartilage thickness (R2=0.70), and hydroxyproline content (R2=0.61), and the weakest with Young’s modulus (R2=0.42). Higher correlation to T2 mapping than T1rho (R2=0.55 vs 0.45) was found, suggesting higher sensitivity to matrix organization than concentration. Weight-bearing and non-weight-bearing parts were classified with high accuracy (90.9%). Spectral measurements in- and outside the cartilage defects in the mini-pigs (Fig. 1) could be classified with 100% accuracy.
Conclusion
Good correlations between spectral features and osteoarthritis-related measures were found. Further validation in vivo is needed. The discriminative classification between healthy and damaged cartilage was excellent, suggesting that applications for cartilage defect (repair) evaluation are feasible.
P017 - The relation between the Biochemical Composition of Knee articular Cartilage and Quantitative MRI: A Systematic Review and Meta-analysis
Abstract
Purpose
Non-invasive detection of early stages of osteoarthritis (OA) is required to enable early treatment and monitoring of interventions. The earliest signs of OA include proteoglycan-content decrease and disruption of collagen network integrity. The aim of this study was to establish the relations between quantitative magnetic resonance imaging (MRI) and biochemical content and collagen organization in knee articular cartilage, measured by a biochemical assay or polarized light microscopy (PLM).
Methods and Materials
A preregistered systematic literature review was performed using the databases PubMed and Embase. Papers were included if a quantified correlation was described between quantitative MRI measures and either a biochemical assay measurement of proteoglycan/collagen concentration, or PLM measures for collagen organization. The extracted correlations were pooled using a random effects model, if the heterogeneity allowed it.
Results
21 papers were identified. The strongest pooled correlation was found for delayed gadolinium-enhanced MRI of cartilage (dGEMRIC) versus proteoglycan concentration (r=0.59, fig. 1). T1ρ relaxation times were inversely correlated to proteoglycan concentration (r=-0.54). A weak correlation between T2 relaxation times and proteoglycans was found (r=-0.38). No correlation between T2 relaxation time and collagen concentration was found (r=-0.02). A heterogeneous set of correlations between T2 relaxation times and PLM were identified, including strong correlations to anisotropy.
Conclusion
dGEMRIC showed the strongest correlation to proteoglycan concentration. The required injection of contrast agent is however a disadvantage; the T1ρ sequence was found as the non-invasive alternative. Remarkably, no correlation was found between T2 relaxation times and collagen concentration. T2 relaxation times is related to organization, rather than concentration of collagen fibers.
Presenter Of 2 Presentations
P015 - Feasibility of Near-Infrared Reflective Spectroscopy to Measure Local Variations in Cartilage Quality: A Human and Animal Cadaveric Study
Abstract
Purpose
There is a clinical demand for a tool for peri-surgical, non-destructive evaluation of local cartilage quality. Such a tool can be used for evaluation of treatment necessity, determination of (viable) borders of a cartilage defect, and evaluation of repair tissue during second-look surgeries. Therefore, the aim of this study was to assess the feasibility of near-infrared spectroscopy as a tool for non-destructive, minimally-invasive measurement of cartilage quality.
Methods and Materials
A custom-developed 2-mm optical-fibre probe was attached to a 350-1830nm wavelength spectrometer. 450 diffuse reflectance spectra were obtained from 90 cartilage sites on eight fresh-frozen human cadaveric knees. Local glycosaminoglycan, hydroxyproline and water content; cartilage thickness; Young’s modulus (using micro-indentation); T1rho and T2-mapping MRI images; and macroscopic osteoarthritis score were obtained. With 35 spectral features, related to water, lipids and blood, a linear regression model was used to assess the relation to physiological outcome parameters. Moreover, a linear discriminant classification model was used to study the discriminative power between weight-bearing and non-weight-bearing areas. Additionally, in a mini-pig cartilage-defect model, the difference between defect and nearby control areas (40 measurements over 8 defects) was classified directly post-mortem.
Results
The linear models showed the best correlation with osteoarthritis score (R2=0.72), cartilage thickness (R2=0.70), and hydroxyproline content (R2=0.61), and the weakest with Young’s modulus (R2=0.42). Higher correlation to T2 mapping than T1rho (R2=0.55 vs 0.45) was found, suggesting higher sensitivity to matrix organization than concentration. Weight-bearing and non-weight-bearing parts were classified with high accuracy (90.9%). Spectral measurements in- and outside the cartilage defects in the mini-pigs (Fig. 1) could be classified with 100% accuracy.
Conclusion
Good correlations between spectral features and osteoarthritis-related measures were found. Further validation in vivo is needed. The discriminative classification between healthy and damaged cartilage was excellent, suggesting that applications for cartilage defect (repair) evaluation are feasible.
P017 - The relation between the Biochemical Composition of Knee articular Cartilage and Quantitative MRI: A Systematic Review and Meta-analysis
Abstract
Purpose
Non-invasive detection of early stages of osteoarthritis (OA) is required to enable early treatment and monitoring of interventions. The earliest signs of OA include proteoglycan-content decrease and disruption of collagen network integrity. The aim of this study was to establish the relations between quantitative magnetic resonance imaging (MRI) and biochemical content and collagen organization in knee articular cartilage, measured by a biochemical assay or polarized light microscopy (PLM).
Methods and Materials
A preregistered systematic literature review was performed using the databases PubMed and Embase. Papers were included if a quantified correlation was described between quantitative MRI measures and either a biochemical assay measurement of proteoglycan/collagen concentration, or PLM measures for collagen organization. The extracted correlations were pooled using a random effects model, if the heterogeneity allowed it.
Results
21 papers were identified. The strongest pooled correlation was found for delayed gadolinium-enhanced MRI of cartilage (dGEMRIC) versus proteoglycan concentration (r=0.59, fig. 1). T1ρ relaxation times were inversely correlated to proteoglycan concentration (r=-0.54). A weak correlation between T2 relaxation times and proteoglycans was found (r=-0.38). No correlation between T2 relaxation time and collagen concentration was found (r=-0.02). A heterogeneous set of correlations between T2 relaxation times and PLM were identified, including strong correlations to anisotropy.
Conclusion
dGEMRIC showed the strongest correlation to proteoglycan concentration. The required injection of contrast agent is however a disadvantage; the T1ρ sequence was found as the non-invasive alternative. Remarkably, no correlation was found between T2 relaxation times and collagen concentration. T2 relaxation times is related to organization, rather than concentration of collagen fibers.