Combining μ-MRI with cellular automata simulation for an improved insight into cell growth within scaffolds

Tissue engineering scaffolds are pivotal for modern healthcare research. However, studying cell-cell and cell-
material interactions within these scaffolding networks is time consuming and technically demanding. In
most cases, the cells within the scaffolds are not visible to classical imaging technologies, so what happens
within remains unknown. An emerging non-destructive option for studying cells within scaffolds is micro-
magnetic resonance imaging (μ-MRI). In this research, its applications to imaging cells within tissue engineer-
ing scaffolds during different periods and quantifying colonization processes within pyrolytic carbon net-
works for their special physical-chemical properties are explored and discussed. Additionally, toward
resource-efficient tissue engineering, in silico approaches are raising the attention of the research commu-
nity. These simulations can be performed employing cellular automata interacting with computer-aided
design (CAD) models, which mimic cell colonization of scaffolds. Our study demonstrates that μ-MRI proves
a remarkable technology for fine-tuning these computational models