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The field of bioprinting has experienced significant progress in recent years, particularly with the development of methods that enable in-situ bioprinting. Reliable in-situ bioink deposition requires accounting for physiological movements, as even under anesthesia, the body can still move due to breathing or involuntary movements. These motions can interfere with the quality of the printed structure [1]. Advances in sensor technologies and robotic have led to the development of motion compensation techniques that address this challenge. Here, we demonstrate that real-time motion compensation can maintain print quality in Laser-Induced Side Transfer (LIST), a drop-on-demand bioprinting technology [2, 3].
LIST was initially developed using a fixed printing head [2, 3]. Here, we modified LIST for portability by replacing the open-space beam delivery system with an optical fiber (FG105LCA-Multimode Fiber). A water-glycerol mixture was used as model ink. An Optical Coherence Tomography (OCT) fiber-based sensor and the fiber-based LIST printhead were mounted on a Dorna 2 robotic arm for real-time compensation (Fig.1(a)). The OCT sensor measures the printhead-to-substrate distance in real-time, providing feedback to the robot to maintain a constant gap. Microscope slides mounted on a translation stage (Z825B, Thorlabs) simulated breathing motion.
Fig. 1. a) Integration of the robotic arm and OCT sensor, b) The different scenario with their corespond printed pattern.
A square pattern of the model ink was printed at 5 Hz on a microscope slide with each droplet spaced 1.5 mm apart. Fig. 1 (b) shows the printed patterns in three conditions: (1)constant 3 mm printhead-to-substrate distance, (2) substrate movement from 3 to 24 mm, and (3) dynamic compensation in which the substrate moves from 3 to 24 mm while the printhead actively maintains a 3 mm distance. A quantitative analysis of printing quality criteria including position accuracy (mm), circularity, printed droplet area (mm²), and splatter coverage was performed to assess compensation performance. The measured criteria with and without compensation are as follows: position accuracy (0.25 ± 0.09 mm vs 0.38 ± 0.23 mm; p = 0.09), circularity (0.82 ± 0.14 vs 0.69 ± 0.18; p= 0.0029), splatter coverage (2.32 ± 1.83% vs 37.36±13.01 %; p = 0.00038), and printed droplet area (1.27 ± 0.47 mm² vs 1.08 ± 0.31 mm² p= 0.017).
Our statistical analysis showed a significant difference in most metrics for compensated vs non-compensated printing. Metrics from compensated printing closely match those from fixed substrate printing, confirming that real-time compensation preserves print quality under dynamic conditions. This highlights the critical role of compensation in in-situ DoD bioprinting. Our ongoing work focuses on refining the robotic control for fast-moving targets that demand both lateral and vertical compensation.
References: [1].O'Neill, J.J., et al. 3D bioprinting directly onto moving human anatomy. in 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 2017. IEEE. [2]. Ebrahimi Orimi, H., et al., Drop-on-demand cell bioprinting via Laser Induced Side Transfer (LIST). Scientific reports, 2020. 10(1): p. 9730. [3]. Roversi, K., et al., Bioprinting of adult dorsal root ganglion (DRG) neurons using laser-induced side transfer (LIST). Micromachines, 2021. 12(8): p. 865.
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