Page 69 - IJB-9-1

International Journal of Bioprinting In situ defect detection and feedback control with P-OCT

using a high-speed OCT system. Simultaneously, data Foundation of China (No. 31927801), and Key Research
processing can be accelerated by software by software. and Development Foundation, Science and Technology
Furthermore, 3D P-OCT, with its advantage of 3D long- Department of Zhejiang Province (No. 2022C01123).
term and nondestructive imaging, provides a powerful
monitoring tool for 4D bioprinting. [25,26] In this study, Conflict of interest
the extrusion bioprinter was considered in 3D P-OCT. In The authors declare that they have no known competing
theory, OCT can be used in other printers with different financial interests or personal relationships that could have
integration methods and imaging results for different appeared to influence the work reported in this paper.
materials. For the extrusion printer, the droplet-based
printer , or microfluidic printer , OCT imaging Author contributions
[27]
[28]
probe is easier to be integrated with small changes to the Conceptualization: Ling Wang, Shanshan Yang, Xu Mingen
original printer. However, larger changes are required to Investigation: Shanshan Yang, Qi Chen, Ling Wang, Xu
integrate OCT imaging probe with other printers, such as Mingen
stereolithography, selective laser sintering, and selective Software: Qi Chen, Shanshan Yang
laser melting. Formal analysis: Shanshan Yang, Qi Chen,
In conclusion, the “monitoring and feedback-as-you- Writing – original draft: Shanshan Yang, Qi Chen
build” mechanism was presented based on 3D P-OCT, Writing – review & editing: Shanshan Yang
defect detection, and the pre-built feedback mechanism. Ethics approval and consent to participate
To the best of our knowledge, this is the first time that 3D
P-OCT has been applied for in situ defect detection and Not applicable.
feedback control to achieve high-fidelity printing from Consent for publication
shape to function. The 3D FS and LT analysis methods
ensured accurate defect detection and location for Not applicable.
feedback and repair. The pre-built feedback mechanism
provided reasonable feedback support for timely Availability of data
feedback control and adjustment of the input parameters. All data that support the findings of this study have been
Based on the “monitoring and feedback-as-you-build” included in the article.
mechanism, the single-layer structure and multi-
layer scaffold showed that in situ defect detection and References
feedback control could ensure less FS and LT errors to 1. Matai I, Kaur G, Seyedsalehi A, et al., 2009, Progress in
achieve high-fidelity printing from structure to function. 3D bioprinting technology for tissue/organ regenerative
The layer fidelity and overall fidelity showed that the engineering. Biomaterials, 226: 119536.
structures after the feedback were much closer to the https://doi.org/10.1016/j.biomaterials.2019.119536
design model. The reconstruction model of 3D P-OCT,
3D volume parameter quantification of VP and PC, and 2. Yang Q, Lian Q, Xu F, 2017, Perspective: Fabrication of
integrated organ-on-a-chip via bioprinting. Biomicrofluidics,
FEA results demonstrated that the scaffold function 11: 031301.
fidelity after feedback was more advantageous, especially
in bone tissue engineering. The presented “monitoring https://doi.org/10.1063/1.4982945
and feedback-as-you-build” quality assurance system can 3. De Moor L, Merovci I, Baetens S, et al., 2018, High-
improve printing efficiency, reduce material waste, and throughput fabrication of vascularized spheroids for
ensure high-fidelity printing from structure to function. bioprinting. Biofabrication, 10: 035009.
3D P-OCT enables in situ defect detection and location, https://doi.org/10.1088/1758-5090/aac7e6
timely feedback control and defect repair, thus promoting 4. Memic A, Navaei A, Mirani B, et al., 2017, Bioprinting
the application of 3D bioprinting in organ transplantation technologies for disease modeling. Biotechnol Lett, 39: 1279–90.
and disease modeling.
https://doi.org/10.1007/s10529-017-2360-z
Acknowledgment 5. Kim JH, Yoo JJ, Lee SJ, 2016, Three-dimensional cell-based
None. bioprinting for soft tissue regeneration. Tissue Eng Regen
Med, 13: 647–662.
Funding https://doi.org/10.1007/s13770-016-0133-8
This work was supported by the National Natural Science 6. Armstrong AA, Norato J, Alleyne AG, et al., 2019, Direct

Volume 9 Issue 1 (2023) 61 https://doi.org/10.18063/ijb.v9i1.624