| Tissue engineering aims to perform tissue or organ construction in vitro or in vivo,providing an effective method to overcome the challenges posed by organ shortages due to disease,trauma and population aging.The inclusion of a vascular system in the in vitro construction of tissue models or organs is necessary to deliver nutrients,oxygen,and remove metabolic waste,thereby increasing the survival rate and tissue thickness of the in vitro constructed tissue.Therefore,internal vascularization of tissue constructs is a challenging issue that must be faced as tissue engineering technology moves forward.Currently,bio-3D printing technology provides a new solution for building complex vascularized tissues,and perfusion culture of vascularized tissues based on microfluidic chip technology provides assurance of in vivo microfluidic field environment simulation.However,the monitoring of the real 3D microfluidic field environment inside the microfluidic chip is still one of the major obstacles to the fabrication of bionic,large-sized vascularized tissues or organs.The discrepancies between actual vascularized tissue morphology and design values;meanwhile,complex fluid properties lead to deviations between flow field simulation results and actual flow field distribution,and too fast or too slow nutrient flow rates often bring adverse effects on cell growth.Therefore,an in situ,large field of view,three-dimensional microfluidic field monitoring technique is urgently needed to realize perfusion culture of 3D printed vascularized tissues based on microfluidic chip technology.Optical Coherence Tomography(OCT)based angiography(OCTA)enables the extraction of dynamic information within the 3D microfluidic field by using intensity,phase or complex signals from OCT data.In this study,we propose the CCd-OCTA algorithm based on the complex correlation difference OCTA(CCd-OCTA)to monitor the flow velocity in the three-dimensional space inside the microfluidic chip.The main research contents and innovations are as follows:(1)In this study,a CCd-OCTA algorithm based on the complex inter-correlation difference was proposed.A perfusion platform was built to perfuse capillary glass tubes with different flow rates,and the CCd-OCTA signal was calculated by combining MB and BM data acquisition strategies,and the relationship curve between CCd-OCTA and flow rate was established.In MB mode,CCd-OCTA can detect flow velocities from 5-600 mm/s,but the detection of flow velocities below 5 mm/s is poor due to the weak signal;in BM mode,the CCd algorithm can detect flow velocities from 0-5 mm/s,but it cannot detect flow velocities above 5 mm/s due to the signal saturating too quickly.By combining the adaptive selection of MB and BM scanning strategies,accurate and wide range(0-600mm/s)flow velocity detection is achieved.(2)In situ printing of tissues containing vascular-like networks within microfluidic chips based on extrusion-based bio-3D technology.We designed and fabricated a PDMS and PMMA-based microfluidic chip with a chamber size of 5mm*5mm*1mm and a microfluidic channel size of 5mm*1mm*1mm,designed a scaffold structure containing secondary branches,and printed a scaffold containing a vascular-like network in situ within the chamber of the microfluidic chip based on an extrusion-based biologic 3D printer and a sacrificial material strategy.After dissolution of the sacrificial material,microfluidic field data acquisition was performed and the effect of the vascular-like network printing was evaluated within the microfluidic chip.(3)To visualize the 3D microfluidic field within the microfluidic chip.Perfusion experiments with different flow rates were performed on the vascular network-like scaffold inside the microfluidic chip based on a microinjection pump;OCTA data were collected to calculate the CCd-OCTA signal distribution within the 3D microfluidic field,and the microfluidic field was visualized and analyzed based on the correspondence between CCd-OCTA and flow rate.To enhance the contrast of microfluidic field imaging,a sliding average of the CC values involved in the calculation was performed using a three-dimensional mean sliding window.In summary,the CCd-OCTA algorithm based on adaptive time interval proposed in this paper can accurately detect and visualize a wide range of flow velocities from 0-600 mm/s in three dimensions,providing a new method to detect the three-dimensional microfluidic field environment inside the microfluidic chip and guaranteeing the accurate control of the flow velocity inside the perfusion-cultured microfluidic chip. |
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