Biomechanical testing of virtual meniscus implants made from a bi-phasic silk fibroin-based hydrogel and polyurethane via finite element analysis

丝素 材料科学 有限元法 聚氨酯 复合材料 丝绸 结构工程 工程类
作者
Anna‐Christina Moser,Jürgen Fritz,Andreas Kesselring,Florian Schüssler,Alexander Otahal,Stefan Nehrer
出处
期刊:Journal of The Mechanical Behavior of Biomedical Materials [Elsevier BV]
卷期号:162: 106830-106830 被引量:4
标识
DOI:10.1016/j.jmbbm.2024.106830
摘要

OBJECTIVE: To investigate the suitability of different material compositions and structural designs for 3D-printed meniscus implants using finite element analysis (FEA) to improve joint function after meniscal injury and guide future implant development. DESIGN: This experimental study involved in-silico testing of a meniscus model developed from two materials: a specially formulated hydrogel composed of silk fibroin (SF), gelatine, and decellularized meniscus-derived extracellular matrix (MD-dECM), and polyurethane (PU) with stiffness levels of 54 and 205 MPa. Both single-material implants and a two-volumetric meniscus model with an SF/gelatine/MD-dECM core and a PU shell were analysed using FEA to simulate the biomechanical performance under physiological conditions. RESULTS: The hydrogel alone was found to be unsuitable for long-term use due to instability in material properties beyond two weeks. PU 54 closely replicated the biomechanical properties of an intact meniscus, particularly in terms of contact pressure and stress distribution. However, hybrid implants combining PU 54 with hydrogel showed potential but required further optimization to reduce stress peaks. In contrast, implants with a PU 205 shell generated higher induced stresses, increasing the risk of material failure. CONCLUSIONS: FEA proves to be a valuable tool in the design and optimization of meniscal implants. The findings suggest that softer PU 54 is a promising material for mimicking natural meniscus properties, while stiffer materials may require design modifications to mitigate stress concentrations. These insights are crucial for refining implant designs and selecting appropriate material combinations before physical prototype production, potentially reducing costs, time, and the risk of implant failure.
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