Parametric Modeling of Biomimetic Cortical Bone Microstructure for Additive Manufacturing

Area of Science:

• Biomaterials Engineering
• Computational Biology
• Additive Manufacturing

Background:

• Cortical bone microstructure is complex and challenging to replicate.
• Existing methods for creating biomimetic bone lack the necessary detail and customization.
• Additive manufacturing offers potential for fabricating patient-specific bone implants.

Purpose of the Study:

• To develop a novel algorithm for generating in-silico biomimetic models of cortical bone microstructure.
• To enable the creation of virtual prototypes that accurately represent the complexity of natural bone.
• To facilitate the additive manufacturing of biomimetic bone with user-defined porosity.

Main Methods:

• Development of a software tool for in-silico modeling of cortical bone microstructure.
• Experimental validation using Digital Light Processing (DLP) of a thermoset polymer resin.
• Characterization of manufactured specimens using Scanning Electron Microscopy with Focused Ion Beam (SEM/FIB) and Computer Tomography (CT).

Main Results:

• The algorithm successfully generated in-silico models of cortical bone, incorporating osteon density, cement line thickness, and vascular channels.
• Manufactured prototypes using DLP showed correspondence with natural bone tissue, including healthy and osteoporotic states.
• Achieved a dynamic in-silico porosity range of 13.37–21.49%, with manufactured samples showing 5.79–16.16% porosity.

Conclusions:

• The proposed methodology represents a significant step towards developing refined and lifelike porous structures for biomimetic bone.
• The developed tool allows for the creation of user-designated bone porosity matching literature values.
• Further research is needed for full validation and patient-specific customization of synthetic bone.