An in-silico approach to meniscus tissue regeneration: Modeling, numerical simulation, and experimental analysis

TL;DR

This work addresses meniscus tissue regeneration by developing a multiscale mathematical framework that couples MSC differentiation to chondrocytes with ECM production within a hyaluron-impregnated PET scaffold under perfusion. The authors derive macroscopic $RDTEs$ for two cell phenotypes through upscaling from subcellular receptor binding and mesoscale transport, incorporating an anisotropic diffusion tensor that encodes scaffold fiber topology. They further couple the cell dynamics to a poroelastic Biot model to account for mechanical stimulation and scaffold deformation, with the differentiation rates $\alpha_1$ and $\alpha_2$ modulated by the mechanical stimulus $S$. Experimental data from scaffold fabrication, micro-CT fiber analysis using an angular central Gaussian model, and biomechanical tests calibrate and validate the model, demonstrating that scaffold anisotropy and flow-induced mechanics steer tissue patterning and MSC fate. The integrated in vitro–in silico approach provides a predictive platform to optimize scaffold design and bioreactor conditions for meniscus regeneration and points to avenues for rigorous mathematical analysis and scalable numerical methods.

Abstract

We develop a model the dynamics of human mesenchymal stem cells (hMSCs) and chondrocytes evolving in a nonwoven polyethylene terephtalate (PET) scaffold impregnated with hyaluron and supplied with a differentiation medium. The scaffold and the cells are assumed to be contained in a bioreactor with fluid perfusion. The differentiation of hMSCs into chondrocytes favors the production of extracellular matrix (ECM) and is influenced by fluid stress. The model takes deformations of ECM and PET scaffold into account. The scaffold structure is explicitly included by statistical assessment of the fibre distribution from CT images. The effective macroscopic equations are obtained by appropriate upscaling from dynamics on lower (microscopic and mesoscopic) scales and feature in the motility terms an explicit cell diffusion tensor encoding the assessed anisotropic scaffold structure. Numerical simulations show its influence on the overall cell and tissue dynamics.

Figures (12)

• Figure 1: Sketch of in-vitro experiment
• Figure 2: Shape of mapping connecting mechanical stimulus $S$ with (de)differentiation rates
• Figure 3: Sectional image of the CT scan of sample 1 (left). The area marked by a red box is magnified 5 times (right) to enhance the visibility of the fiber structure.
• Figure 4: Spherical density plots of the empirical fiber orientation distribution (left) and of the fitted ACG model (right) for sample 1.
• Figure 5: The PET scaffolds were mechanically investigated using two different testing methods: A) spatial indentation mapping was performed on the surface of the entire PET scaffold. Subsequently, cylindrical samples were punched out of the scaffolds to further analyse the biomechanical properties under B) confined-compression conditions.