Huo Yi, Lyu Yongtao, Bosiakov Sergei, Han Feng
Department of Engineering Mechanics, Dalian University of Technology, Dalian 116024, China.
DUT-BSU Joint Institute, Dalian University of Technology, Dalian 116024, China.
Materials (Basel). 2021 Dec 26;15(1):153. doi: 10.3390/ma15010153.
With the change of people's living habits, bone trauma has become a common clinical disease. A large number of bone joint replacements is performed every year around the world. Bone joint replacement is a major approach for restoring the functionalities of human joints caused by bone traumas or some chronic bone diseases. However, the current bone joint replacement products still cannot meet the increasing demands and there is still room to increase the performance of the current products. The structural design of the implant is crucial because the performance of the implant relies heavily on its geometry and microarchitecture. Bionic design learning from the natural structure is widely used. With the progress of technology, machine learning can be used to optimize the structure of bone implants, which may become the focus of research in the future. In addition, the optimization of the microstructure of bone implants also has an important impact on its performance. The widely used design algorithm for the optimization of bone joint replacements is reviewed in the present study. Regarding the manufacturing of the implant, the emerging additive manufacturing technique provides more room for the design of complex microstructures. The additive manufacturing technique has enabled the production of bone joint replacements with more complex internal structures, which makes the design process more convenient. Numerical modeling plays an important role in the evaluation of the performance of an implant. For example, theoretical and numerical analysis can be carried out by establishing a musculoskeletal model to prepare for the practical use of bone implants. Besides, the in vitro and in vivo testing can provide mechanical properties of bone implants that are more in line with the implant recipient's situation. In the present study, the progress of the design, manufacture, and evaluation of the orthopedic implant, especially the joint replacement, is critically reviewed.
随着人们生活习惯的改变,骨创伤已成为临床常见疾病。全球每年都有大量的骨关节置换手术。骨关节置换是恢复因骨创伤或某些慢性骨病导致的人体关节功能的主要方法。然而,目前的骨关节置换产品仍无法满足日益增长的需求,现有产品的性能仍有提升空间。植入物的结构设计至关重要,因为其性能在很大程度上依赖于几何形状和微观结构。借鉴自然结构的仿生设计被广泛应用。随着技术的进步,机器学习可用于优化骨植入物的结构,这可能成为未来的研究重点。此外,骨植入物微观结构的优化对其性能也有重要影响。本研究综述了广泛用于骨关节置换优化的设计算法。关于植入物的制造,新兴的增材制造技术为复杂微观结构的设计提供了更多空间。增材制造技术能够生产具有更复杂内部结构的骨关节置换物,使设计过程更加便捷。数值模拟在评估植入物性能方面发挥着重要作用。例如,可以通过建立肌肉骨骼模型进行理论和数值分析,为骨植入物的实际应用做准备。此外,体外和体内测试可以提供更符合植入物接受者情况的骨植入物力学性能。在本研究中,对骨科植入物,尤其是关节置换物的设计、制造和评估进展进行了批判性综述。