Computational modeling guides tissue-engineered heart valve design for long-term in vivo performance in a translational sheep model.

Valvular heart disease is a major cause of morbidity and mortality worldwide. Current heart valve prostheses have considerable clinical limitations due to their artificial, nonliving nature without regenerative capacity. To overcome these limitations, heart valve tissue engineering (TE) aiming to develop living, native-like heart valves with self-repair, remodeling, and regeneration capacity has been suggested as next-generation technology. A major roadblock to clinically relevant, safe, and robust TE solutions has been the high complexity and variability inherent to bioengineering approaches that rely on cell-driven tissue remodeling. For heart valve TE, this has limited long-term performance in vivo because of uncontrolled tissue remodeling phenomena, such as valve leaflet shortening, which often translates into valve failure regardless of the bioengineering methodology used to develop the implant. We tested the hypothesis that integration of a computationally inspired heart valve design into our TE methodologies could guide tissue remodeling toward long-term functionality in tissue-engineered heart valves (TEHVs). In a clinically and regulatory relevant sheep model, TEHVs implanted as pulmonary valve replacements using minimally invasive techniques were monitored for 1 year via multimodal in vivo imaging and comprehensive tissue remodeling assessments. TEHVs exhibited good preserved long-term in vivo performance and remodeling comparable to native heart valves, as predicted by and consistent with computational modeling. TEHV failure could be predicted for nonphysiological pressure loading. Beyond previous studies, this work suggests the relevance of an integrated in silico, in vitro, and in vivo bioengineering approach as a basis for the safe and efficient clinical translation of TEHVs.