Leaflet Design

The general approach in heart valve tissue engineering is to mimic the shape of the native valve in the attempt to recreate the natural haemodynamics. In this article, we report the fabrication of the first tissue-engineered heart valve (TEHV) based on a tubular leaflet design, where the function of the leaflets of semilunar heart valves is performed by a simple tubular construct sutured along a circumferential line at the root and at three single points at the sinotubular junction. The tubular design is a recent development in pericardial (nonviable) bioprostheses, which has attracted interest because of the simplicity of the construction and the reliability of the implantation technique. Here we push the potential of the concept further from the fabrication and material point of view to realize the tube-in-tube valve: an autologous, living HV with remodelling and growing capability, physiological haemocompatibility, simple to construct and fast to implant. We developed two different fabrication/conditioning procedures and produced fibrin-based constructs embedding cells from the ovine umbilical cord artery according to the two different approaches. Tissue formation was confirmed by histology and immunohistology. The design of the tube-in-tube foresees the possibility of using a textile coscaffold (here demonstrated with a warp-knitted mesh) to achieve enhanced mechanical properties in vision of implantation in the aortic position. The tube-in-tube represents an attractive alternative to the conventional design of TEHVs aiming at reproducing the valvular geometry.

Transcatheter aortic valve implantation of (nonviable) bioprosthetic valves has been proven a valid alternative to conventional surgical implantation in patients at high or prohibitive mortality risk. In this study we present the in vitro proof-of-principle of a newly developed tissue-engineered heart valve for minimally invasive implantation, with the ultimate aim of adding the unique advantages of a living tissue with regeneration capabilities to the continuously developing transcatheter technologies. The tube-in-stent is a fibrin-based tissue-engineered valve with a tubular leaflet design. It consists of a tubular construct sewn into a self-expandable nitinol stent at three commissural attachment points and along a circumferential line so that it forms three coaptating leaflets by collapsing under diastolic back pressure. The tubular constructs were molded with fibrin and human umbilical vein cells. After 3 weeks of conditioning in a bioreactor, the valves were fully functional with unobstructed opening (systolic phase) and complete closure (diastolic phase). Tissue analysis showed a homogeneous cell distribution throughout the valve's thickness and deposition of collagen types I and III oriented along the longitudinal direction. Immunohistochemical staining against CD31 and scanning electron microscopy revealed a confluent endothelial cell layer on the surface of the valves. After harvesting, the valves underwent crimping for 20 min to simulate the catheter-based delivery. This procedure did not affect the valvular functionality in terms of orifice area during systole and complete closure during diastole. No influence on the extracellular matrix organization, as assessed by immunohistochemistry, nor on the mechanical properties was observed. These results show the potential of combining tissue engineering and minimally invasive implantation technology to obtain a living heart valve with a simple and robust tubular design for transcatheter delivery. The effect of the in vivo remodeling on the functionality of the tube-in-stent valve remains to be tested.

Artificial heart valves, used to replace diseased human heart valves, are life-saving medical devices. Currently, at the device development stage, new artificial valves are primarily assessed through time-consuming and expensive benchtop tests or animal implantation studies. Computational stress analysis using the finite element (FE) method presents an attractive alternative to physical testing. However, FE computational analysis requires a complex process of numeric modeling and simulation, as well as in-depth engineering expertise. In this proof of concept study, our objective was to develop machine learning (ML) techniques that can estimate the stress and deformation of a transcatheter aortic valve (TAV) from a given set of TAV leaflet design parameters. Two deep neural networks were developed and compared: the autoencoder-based ML-models and the direct ML-models. The ML-models were evaluated through Monte Carlo cross validation. From the results, both proposed deep neural networks could accurately estimate the deformed geometry of the TAV leaflets and the associated stress distributions within a second, with the direct ML-models (ML-model-d) having slightly larger errors. In conclusion, although this is a proof-of-concept study, the proposed ML approaches have demonstrated great potential to serve as a fast and reliable tool for future TAV design.