Devising tissue ingrowth metrics: a contribution to the computational characterization of engineered soft tissue healing.

The paradigm shift brought about by the expansion of tissue engineering and regenerative medicine away from the use of biomaterials, currently questions the value of histopathologic methods in the evaluation of biological changes. To date, the available tools of evaluation are not fully consistent and satisfactory for these advanced therapies. We have developed a new, simple and inexpensive quantitative digital approach that provides key metrics for structural and compositional characterization of the regenerated tissues. For example, metrics provide the tissue ingrowth rate (TIR) which integrates two separate indicators; the cell ingrowth rate (CIR) and the total collagen content (TCC) as featured in the equation, TIR% = CIR% + TCC%. Moreover a subset of quantitative indicators describing the directional organization of the collagen (relating structure and mechanical function of tissues), the ratio of collagen I to collagen III (remodeling quality) and the optical anisotropy property of the collagen (maturity indicator) was automatically assessed as well. Using an image analyzer, all metrics were extracted from only two serial sections stained with either Feulgen & Rossenbeck (cell specific) or Picrosirius Red F3BA (collagen specific). To validate this new procedure, three-dimensional (3D) scaffolds were intraperitoneally implanted in healthy and in diabetic rats. It was hypothesized that quantitatively, the healing tissue would be significantly delayed and of poor quality in diabetic rats in comparison to healthy rats. In addition, a chemically modified 3D scaffold was similarly implanted in a third group of healthy rats with the assumption that modulation of the ingrown tissue would be quantitatively present in comparison to the 3D scaffold-healthy group. After 21 days of implantation, both hypotheses were verified by use of this novel computerized approach. When the two methods were run in parallel, the quantitative results revealed fine details and differences not detected by the semi-quantitative assessment, demonstrating the importance of quantitative analysis in the performance evaluation of soft tissue healing. This automated and supervised method reduced operator dependency and proved to be simple, sensitive, cost-effective and time-effective. It supports objective therapeutic comparisons and helps to elucidate regeneration and the dynamics of a functional tissue.