Six-Year-Old Sheep as a Clinically Relevant Large Animal Model for Aortic Valve Replacement Using Tissue-Engineered Grafts Based on Decellularized Allogenic Matrix

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Abstract

Tissue-engineered (TE) grafts based on decellularized grafts have shown very promising results in preclinical and clinical studies. However, in animal models valves have either been tested in juvenile models or in the clinically less relevant pulmonary valve position. In this study, we tested the grafts in the aortic valve (AV) position of 6-year-old sheep, as geriatric patients in need of an AV substitute due to calcification are the largest patient group benefiting from TE grafts. Decellularized AV (DAV; n = 4) and DAV additionally re-endothelialized with autologous cells (n = 3) were implanted in the AV position of 6-year-old female sheep. Function was investigated at implantation and explantation 12 months later. Regeneration capacity was analyzed by the repopulation degree of the graft with recipient's cells, by the generation of a new endothelial layer and by intracellular staining against pro-collagen type I. DAV and re-endothelialized AV demonstrated excellent function with only two valves developing mild insufficiencies (1°). Of the repopulating cells only few cells were identified as inflammation cells, while the majority was found to be interstitial cells producing procollagen type I. Endothelial coverage was found, but seemed to be reduced. The regenerative capacity of decellularized matrix is not only a feature exhibited when implanted in juvenile individuals but also is evident when implanted in the high-pressure AV position of older sheep, revealing the potential of TE grafts in age-advanced patients.

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Theodoridis, K., Tudorache, I., Cebotari, S., Calistru, A., Meyer, T., Sarikouch, S., … Hilfiker, A. (2017). Six-Year-Old Sheep as a Clinically Relevant Large Animal Model for Aortic Valve Replacement Using Tissue-Engineered Grafts Based on Decellularized Allogenic Matrix. Tissue Engineering - Part C: Methods, 23(12), 953–963. https://doi.org/10.1089/ten.tec.2017.0163

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