Densified collagen tubular grafts for human tissue replacement and disease modelling applications.

There is a significant need across multiple indications for an off-the-shelf bioengineered tubular graft which fulfils the mechanical and biological requirements for implantation and function but does not necessarily require cells for manufacture or deployment. Herein, we present a tissue-like tubular construct using a cell-free, materials-based method of manufacture, utilizing densified collagen hydrogel. Our tubular grafts are seamless, mechanically strong, customizable in terms of lumen diameter and wall thickness, and display a uniform fibril density across the wall thickness and along the tube length. While the method enables acellular grafts to be generated rapidly, inexpensively, and to a wide range of specifications, the cell-compatible densification process also enables a high density of cells to be incorporated uniformly into the walls of the tubes, which we show can be maintained under perfusion culture. Additionally, the method enables tubes consisting of distinct cell domains with cellular configurations at the boundaries which may be useful for modelling aortic disease. Further, we demonstrate additional steps which allow for luminal surface patterning. These results highlight the universality of this approach and its potential for developing the next generation of bioengineered grafts.

3D Printable Vascular Networks Generated by Accelerated Constrained Constructive Optimization for Tissue Engineering.

One of the greatest challenges in fabricating artificial tissues and organs is the incorporation of vascular networks to support the biological requirements of the embedded cells, encouraging tissue formation and maturation. With the advent of 3D printing technology, significant progress has been made with respect to generating vascularized artificial tissues. Current algorithms to generate arterial/venous trees are computationally expensive and offer limited freedom to optimize the resulting structures. Furthermore, there is no method for algorithmic generation of vascular networks that can recapitulate the complexity of the native vasculature for more than two trees, and export directly to a 3D printing format. Here, we report such a method, using an accelerated constructive constrained optimization approach, by decomposing the process into construction, optimization, and collision resolution stages. The new approach reduces computation time to minutes at problem sizes where previous implementations have reported days. With the optimality criterion of maximizing the volume of useful tissue which could be grown around such a network, an approach of alternating stages of construction and batch optimization of all node positions is introduced and shown to yield consistently more optimal networks. The approach does not place a limit on the number of interpenetrating networks that can be constructed in a given space; indeed we demonstrate a biomimetic, liver-like tissue model. Methods to account for the limitations of 3D printing are provided, notably the minimum feature size and infill at sharp angles, through padding and angle reduction, respectively.