Adel Abdalla, Ahlam A; Pendegrass, Catherine J; (2023) Biological approaches to the repair and regeneration of the rotator cuff tendon-bone enthesis: a literature review. Biomaterials Translational , 4 (2) pp. 85-103. 10.12336/biomatertransl.2023.02.004.

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Abstract

Entheses are highly specialised organs connecting ligaments and tendons to bones, facilitating force transmission, and providing mechanical strengths to absorb forces encountered. Two types of entheses, fibrocartilaginous and fibrous, exist in interfaces. The gradual fibrocartilaginous type is in rotator cuff tendons and is more frequently injured due to the poor healing capacity that leads to loss of the original structural and biomechanical properties and is attributed to the high prevalence of retears. Fluctuating methodologies and outcomes of biological approaches are challenges to overcome for them to be routinely used in clinics. Therefore, stratifying the existing literature according to different categories (chronicity, extent of tear, and studied population) would effectively guide repair approaches. This literature review supports tissue engineering approaches to promote rotator cuff enthesis healing employing cells, growth factors, and scaffolds period. Outcomes suggest its promising role in animal studies as well as some clinical trials and that combination therapies are more beneficial than individualized ones. It then highlights the importance of tailoring interventions according to the tear extent, chronicity, and the population being treated. Contributing factors such as loading, deficiencies, and lifestyle habits should also be taken into consideration. Optimum results can be achieved if biological, mechanical, and environmental factors are approached. It is challenging to determine whether variations are due to the interventions themselves, the animal models, loading regimen, materials, or tear mechanisms. Future research should focus on tailoring interventions for different categories to formulate protocols, which would best guide regenerative medicine decision making.

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