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Automated 3D Optical Coherence Tomography to Elucidate Biofilm Morphogenesis Over Large Spatial Scales
Published on: August 21, 2019
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Continuous and highly accurate multi-material extrusion-based bioprinting with optical coherence tomography imaging
Jin Wang1, Chen Xu1, Shanshan Yang1
1School of Automation, Hangzhou Dianzi University, Hangzhou, Zhejiang, China.
International Journal of Bioprinting
|June 5, 2023
Summary
This study introduces automated models using optical coherence tomography (OCT) to precisely align multi-material filaments in extrusion-based bioprinting, significantly reducing errors and improving scaffold accuracy.
Area of Science:
- Biomedical Engineering
- Materials Science
- Additive Manufacturing
Background:
- Extrusion-based bioprinting is vital for tissue engineering but faces challenges with multi-material printing accuracy.
- Printing errors like filament mismatch and material deposition inaccuracies (under/over-extrusion) compromise the mechanical and biological properties of printed constructs.
- Existing manual correction methods are inefficient, necessitating automated solutions for improved precision and speed.
Purpose of the Study:
- To develop and validate automated models for enhancing accuracy and efficiency in extrusion-based multi-material bioprinting.
- To enable precise registration of printing filaments from different materials.
- To minimize material deposition errors at nozzle connection points.
Main Methods:
- Utilized optical coherence tomography (OCT) for real-time monitoring of the bioprinting process.
- Developed a multi-material static model correlating filament metrics (size, layer thickness) with printing parameters (speed, pressure) for different materials.
- Implemented a time-related control model to adjust nozzle parameters for correcting deposition errors.
Main Results:
- The multi-material static model facilitated rapid selection of printing parameters for accurate filament registration.
- The time-related control model effectively reduced material deposition errors at connection points.
- Experimental results demonstrated elimination of material deposition errors and achieved uniform layer thickness across different materials in single and multi-layer scaffolds.
Conclusions:
- The proposed automated models significantly improve the precision and efficiency of extrusion-based multi-material bioprinting.
- These models offer a practical solution for accurate scaffold fabrication, overcoming limitations of traditional methods.
- The developed approach enhances the quality and reliability of bioprinted structures for tissue engineering applications.
