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Microscale strain concentrations in tissue-engineered osteochondral implants are dictated by local compositional
Byumsu Kim1, Terri-Ann N Kelly2, Hyung Jin Jung2
1Sibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, NY, United States.
Journal of Biomechanics
|December 9, 2023
Summary
Tissue-engineered cartilage mechanics depend on composition. Low aggrecan and high collagen concentrations significantly increase strain in engineered cartilage, crucial for predicting implant performance.
Area of Science:
- Biomaterials Science
- Tissue Engineering
- Biomechanics
Background:
- Tissue-engineered osteochondral implants show promise for cartilage repair.
- Current methods can replicate bulk mechanical properties but lack understanding of micro-level relationships.
- Predicting in vivo performance requires knowledge of architectural, compositional, and micromechanical interactions.
Purpose of the Study:
- To investigate the relationships between architectural features, composition, and micromechanical behavior in tissue-engineered osteochondral implants.
- To identify critical parameters influencing the performance of cell-based cartilage constructs.
Main Methods:
- Utilized fast-confocal microscopy and strain mapping for micromechanical analysis under quasi-static loading.
- Employed Fourier Transform Infrared Spectroscopy to assess local compositional distributions.
- Analyzed architectural features, compositional distributions, and strain distributions during tissue maturation.
Main Results:
- Cell-based aggregates deformed and moved under compression, leading to high local strain at boundaries.
- High strain regions correlated with low aggrecan and high collagen concentrations.
- A threshold relationship was identified: aggrecan < 0.015 A.U. and collagen > 0.15 A.U. resulted in > threefold increase in compressive strain.
Conclusions:
- Local compositional features are the primary determinants of the micromechanical environment in engineered cartilage.
- Findings provide insights into potential quality control parameters for manufacturing effective tissue-engineered constructs.
- Understanding these relationships is key to improving the predictability of in vivo performance for cartilage repair.

