Model-based data analysis of tissue growth in thin 3D printed scaffolds. (7th November 2021)

• Record Type: Journal Article
• Authors: Browning, Alexander P.; Maclaren, Oliver J.; Buenzli, Pascal R.; Lanaro, Matthew; Allenby, Mark C.; Woodruff, Maria A.; Simpson, Matthew J.
• Is Part Of: Journal of theoretical biology. Volume 528(2021)
• Publication Date: 2021-11-07
• Subjects: Tissue engineering -- Uncertainty quantification -- 3D printing -- Parameter estimation -- Porous-Fisher -- Reaction-diffusion; Biology -- Periodicals; Biological Science Disciplines -- Periodicals; Biology -- Periodicals; Biologie -- Périodiques; Theoretische biologie; Biology; Periodicals; 571.05
• DOI: 10.1016/j.jtbi.2021.110852
• Languages: English
• ISSNs: 0022-5193

Abstract

Highlights: 3D printed scaffolds allow exploration of cell behavior in realistic geometries. Mathematically model tissue growth in terms of cell proliferation and migration. Parameter estimates and uncertainty quantify reveal consistency in cell behaviour. Analysis identifies two distinct stages of tissue growth in 3D scaffolds. Abstract: Tissue growth in three-dimensional (3D) printed scaffolds enables exploration and control of cell behaviour in more biologically realistic geometries than that allowed by traditional 2D cell culture. Cell proliferation and migration in these experiments have yet to be explicitly characterised, limiting the ability of experimentalists to determine the effects of various experimental conditions, such as scaffold geometry, on cell behaviour. We consider tissue growth by osteoblastic cells in melt electro-written scaffolds that comprise thin square pores with sizes that were deliberately increased between experiments. We collect highly detailed temporal measurements of the average cell density, tissue coverage, and tissue geometry. To quantify tissue growth in terms of the underlying cell proliferation and migration processes, we introduce and calibrate a mechanistic mathematical model based on the Porous-Fisher reaction–diffusion equation. Parameter estimates and uncertainty quantification through profile likelihood analysis reveal consistency in the rate of cell proliferation and steady-state cell density between pore sizes. This analysis also serves as an important model verification tool: while the use of reaction–diffusion models in biology is widespread, the appropriateness of these models to describe tissue growth in 3D scaffolds has yet to be explored. We find that the Porous-Fisher model is able to capture features relating to the cell density and tissue coverage, but is not able to capture geometric features relating to the circularity of the tissue interface. Our analysis identifies two distinct stages of tissue growth, suggests several areas for model refinement, and provides guidance for future experimental work that explores tissue growth in 3D printed scaffolds.