Dipartimento di Meccanica, Matematica e Management, Politecnico di Bari, Bari 70126, Italy.
Dipartimento di Meccanica, Matematica e Management, Politecnico di Bari, Bari 70126, Italy.
Mater Sci Eng C Mater Biol Appl. 2018 Feb 1;83:51-66. doi: 10.1016/j.msec.2017.09.004. Epub 2017 Sep 29.
In a context more and more oriented towards customized medical solutions, we propose a mechanobiology-driven algorithm to determine the optimal geometry of scaffolds for bone regeneration that is the most suited to specific boundary and loading conditions. In spite of the huge number of articles investigating different unit cells for porous biomaterials, no studies are reported in the literature that optimize the geometric parameters of such unit cells based on mechanobiological criteria. Parametric finite element models of scaffolds with rhombicuboctahedron unit cell were developed and incorporated into an optimization algorithm that combines them with a computational mechanobiological model. The algorithm perturbs iteratively the geometry of the unit cell until the best scaffold geometry is identified, i.e. the geometry that allows to maximize the formation of bone. Performances of scaffolds with rhombicuboctahedron unit cell were compared with those of other scaffolds with hexahedron unit cells. We found that scaffolds with rhombicuboctahedron unit cell are particularly suited for supporting medium-low loads, while, for higher loads, scaffolds with hexahedron unit cells are preferable. The proposed algorithm can guide the orthopaedic/surgeon in the choice of the best scaffold to be implanted in a patient-specific anatomic region.
在越来越倾向于定制化医疗解决方案的背景下，我们提出了一种基于力学生物学的算法，用于确定最适合特定边界和载荷条件的骨再生支架的最佳几何形状。尽管有大量的文章研究了多孔生物材料的不同单元，但文献中没有报道根据力学生物学标准优化这些单元的几何参数的研究。我们开发了具有菱方-八角面体单元的支架的参数有限元模型，并将其纳入到一个优化算法中，该算法将它们与计算力学生物学模型相结合。该算法通过迭代方式扰动单元的几何形状，直到确定最佳支架几何形状，即允许最大化骨形成的几何形状。我们比较了菱方-八角面体单元的支架与具有六面体单元的其他支架的性能。我们发现，菱方-八角面体单元的支架特别适合于支撑中低载荷，而对于更高的载荷，六面体单元的支架更可取。所提出的算法可以指导矫形外科医生/外科医生选择要植入患者特定解剖区域的最佳支架。
