Šušteršič Tijana, Simsek Gorkem Muttalip, Yapici Guney Guven, Nikolić Milica, Vulović Radun, Filipovic Nenad, Vrana Nihal Engin
Faculty of Engineering, University of Kragujevac (FINK), Kragujevac, Serbia.
Steinbeis Advanced Risk Technologies Institute Doo Kragujevac (SARTIK), Kragujevac, Serbia.
Front Bioeng Biotechnol. 2021 Sep 7;9:718026. doi: 10.3389/fbioe.2021.718026. eCollection 2021.
The release of metal particles and ions due to wear and corrosion is one of the main underlying reasons for the long-term complications of implantable metallic implants. The rather short-term focus of the established biocompatibility tests cannot take into account such effects. Corrosion behavior of metallic implants mostly investigated in body-like environments for long time periods and their coupling with long-term experiments are not practical. Mathematical modeling and modeling the corrosion mechanisms of metals and alloys is receiving a considerable attention to make predictions in particular for long term applications by decreasing the required experimental duration. By using such approaches, the corrosion conditions for later stages can be mimicked immediately in i experiments. For this end, we have developed a mathematical model for multi-pit corrosion based on Cellular Automata (CA). The model consists of two sub-models, corrosion initialization and corrosion progression, each driven by a set of rules. The model takes into account several environmental factors (pH, temperature, potential difference, etc.), as well as stochastic component, present in phenomena such as corrosion. The selection of NiTi was based on the risk of Ni release from the implant surface as it leads to immune reactions. We have also performed experiments with Nickel Titanium (NiTi) shape memory alloys. The images both from simulation and experiments can be analyzed using a set of statistical methods, also investigated in this paper (mean corrosion, standard deviation, entropy etc.). For more widespread implementation, both simulation model, as well as analysis of output images are implemented as a web tool. Described methodology could be applied to any metal provided that the parameters for the model are available. Such tool can help biomedical researchers to test their new metallic implant systems at different time points with respect to ion release and corrosion and couple the obtained information directly with tests.
由于磨损和腐蚀导致的金属颗粒和离子释放是可植入金属植入物长期并发症的主要潜在原因之一。既定生物相容性测试相当短期的关注点无法考虑到此类影响。金属植入物的腐蚀行为大多在类似人体的环境中进行长时间研究，而将其与长期实验相结合并不实际。金属和合金腐蚀机制的数学建模正受到相当多的关注，以便通过减少所需的实验持续时间来对长期应用进行预测。通过使用此类方法，可以在实验中立即模拟后期的腐蚀条件。为此，我们基于细胞自动机（CA）开发了一种多坑腐蚀数学模型。该模型由两个子模型组成，即腐蚀初始化和腐蚀进展，每个子模型都由一组规则驱动。该模型考虑了几个环境因素（pH值、温度、电位差等）以及腐蚀等现象中存在的随机成分。选择镍钛合金是基于植入物表面镍释放的风险，因为这会导致免疫反应。我们还对镍钛（NiTi）形状记忆合金进行了实验。模拟和实验得到的图像都可以使用一组统计方法进行分析，本文也对这些方法进行了研究（平均腐蚀、标准偏差、熵等）。为了更广泛地应用，模拟模型以及输出图像分析都作为一个网络工具来实现。只要有模型参数，所描述的方法可以应用于任何金属。这样的工具可以帮助生物医学研究人员在不同时间点测试他们新的金属植入系统的离子释放和腐蚀情况，并将获得的信息直接与测试相结合。
