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Direct Bio-printing with Heterogeneous Topology Design
Amm Nazmul Ahsan1, Ruinan Xie1, Bashir Khoda1
1Industrial and Manufacturing Engineering, North Dakota State University, Fargo, ND, 58102, USA.
Procedia Manufacturing
|February 17, 2018
Summary
This study introduces a novel topology-based scaffold design method for bio-additive manufacturing. It accurately represents complex tissue structures, enabling precise fabrication of heterogeneous porous scaffolds for tissue regeneration without traditional STL files.
Area of Science:
- Biomaterials Science
- Tissue Engineering
- Additive Manufacturing
Background:
- Tissue and organ microstructures are inherently anisotropic, heterogeneous, and porous.
- Traditional CAD modeling struggles to accurately represent complex biological heterogeneity.
- STL conversion in bio-printing workflows leads to information loss and cumulative errors.
Purpose of the Study:
- To develop a topology-based scaffold design methodology for accurate representation of heterogeneous tissue architectures.
- To enable direct fabrication of complex porous scaffolds for tissue regeneration.
- To overcome limitations of traditional CAD and STL conversion in bio-additive manufacturing.
Main Methods:
- Image analysis to digitize topology information from medical images.
- Weighted topology reconstruction algorithm to represent heterogeneity with parametric functions.
- Direct transfer of parametric data to 3D bio-printers, bypassing STL files.
Main Results:
- Successful implementation of the topology-based design methodology.
- Accurate representation of heterogeneous internal tissue architecture.
- Fabrication of a complex porous tissue scaffold using a deposition-based bio-additive manufacturing system without STL conversion.
Conclusions:
- The proposed topology-based approach accurately captures tissue heterogeneity for scaffold design.
- Direct data transfer to bio-printers enables precise manufacturing of complex scaffolds.
- This method enhances bio-additive manufacturing for advanced tissue regeneration applications.
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