Abstract
Scaffold design plays an essential role in tissue engineering of articular cartilage by providing the appropriate mechanical and biological environment for chondrocytes to proliferate and function. Optimization of scaffold design to generate tissue-engineered cartilage has traditionally been conducted using in-vitro and in-vivo models. Recent advances in computational analysis allow us to significantly decrease the time and cost of scaffold optimization using finite element analysis (FEA). FEA is an in-silico analysis technique that allows for scaffold design optimization by predicting mechanical responses of cells and scaffolds under applied loads. Finite element analyses can potentially mimic the morphology of cartilage using mesh elements (tetrahedral, hexahedral), material properties (elastic, hyperelastic, poroelastic, composite), physiological loads by applying loading conditions (static, dynamic), and constitutive stress–strain equations (linear, porous–elastic, biphasic). Furthermore, FEA can be applied to the study of the effects of dynamic loading, material properties cell differentiation, cell activity, scaffold structure optimization, and interstitial fluid flow, in isolated or combined multi-scale models. This review covers recent studies and trends in the use of FEA for cartilage tissue engineering and scaffold design.
Highlights
Articular cartilage is predominantly made up of chondrocytes that are differentiated from mesenchymal stem cells (MSCs) [1]
The spatial orientation of cartilage is defined by the organization of chondrocytes and the extracellular matrix in three distinct layers [2]
We will review recent advancements in finite element analysis (FEA) for cartilage scaffold design, optimization, and the impact this has on improving scaffold design
Summary
Articular cartilage is predominantly made up of chondrocytes that are differentiated from mesenchymal stem cells (MSCs) [1]. FEA is a computational mechanics tool that performs stress–strain analysis within a body (scaffold) by dividing it into smaller blocks (elements) of an approximately regular shape. These shapes can be 2D (planer triangle or quadrilateral) or 3D (tetrahedral or hexahedral) and are formed by placing nodes on the solid geometry. Finer mesh models with higher numbers of nodes increase the capability of predicting cellular responses to mechanical loading [22] These cellular models identify the optimal design and mechanical stimuli needed for mechanotransduction [23]. We will review recent advancements in FEA for cartilage scaffold design, optimization, and the impact this has on improving scaffold design
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