Prediction of the mechanical response of a 3D (bio)printed hybrid scaffold for improving bone tissue regeneration by structural finite element analysis.
J Mech Behav Biomed Mater
; 142: 105822, 2023 06.
Article
em En
| MEDLINE
| ID: mdl-37116309
ABSTRACT
Scaffolds for bone tissue engineering should be osteoinductive, osteoconductive, biocompatible, biodegradable, and, at the same time, exhibit proper mechanical properties. The present study investigated the mechanical properties of a coprinted hybrid scaffold made of polycaprolactone (PCL) and an alginate-based hydrogel, which was conceived to possess a double function of in vivo bio-integration (due to the ability of the hydrogel to release lyosecretome, a freeze-dried formulation of mesenchymal stem cell secretome with osteoinductive and osteoconductive properties) and withstanding loads (due to the presence of polycaprolactone, which provides mechanical resistance). To this end, an in-silico study was conducted to predict mechanical properties. Structural finite element analysis (FEA) of the hybrid scaffold under compression was performed to compare the numerical results with the corresponding experimental data. The impact of alginate inclusion and infill patterns on scaffold stiffness was investigated. Results show an increase in mechanical properties by changing the scaffold infill pattern (linear 145.38±28.90 vs. honeycomb 278.96±50.19, mean and standard deviation, n = 8), while alginate inclusion does not always impact the mechanical performance of the hybrid scaffold (stiffness 145.38±28.90 vs. 195.42±38.68 N/mm, with vs without hydrogel inclusion, respectively). This is confirmed by FEA analysis, in which a good correspondence between experimental and numerical stiffness is shown (142±28.94 vs. 117.18, respectively, linear scaffold with hydrogel inclusion). In conclusion, the computational framework is a valid tool for predicting the mechanical performance of scaffolds and is promising for future clinical applications in the maxillofacial field.
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Bases de dados:
MEDLINE
Assunto principal:
Engenharia Tecidual
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Alicerces Teciduais
Tipo de estudo:
Prognostic_studies
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Risk_factors_studies
Idioma:
En
Revista:
J Mech Behav Biomed Mater
Assunto da revista:
ENGENHARIA BIOMEDICA
Ano de publicação:
2023
Tipo de documento:
Article