Capture and subtype identification of circulating tumor cells using a hyperuniform-patterned microchip
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Abstract
A microfluidic chip (microchip) is a technology that brought the lab change from macro system to the micro system. This technology makes it possible for researchers to do experiments in a device with at least one dimension on the micrometer scale. The demand for accuracy and high throughput chips is increasing with more and more applications people found in different device designs. With the digital simulation and 3D printing method, the new chip designs can be easily modified to meet the additional requirements. One critical application of microchips is separating and identifying circulating tumor cells (CTCs). CTCs separated from the patient blood can give a clearer condition for clinic diagnosis. The primary purpose of this dissertation is to design and fabricate a new microchip with the characteristic of hyperuniform (HU) and apply this new design to CTC separation and label-free identification. In Chapter 2, a three-dimensional (3D) printed microscope mask alignment adapter (MMAA) was designed that can be compatible with regular optical microscopes and ultraviolet (UV) light exposure systems. Then the optimized MMAA was tested by 2 and 4 layers of the 3D structures. The results showed a successful fabrication of the multilayer microstructure and can be used in designing the microchips. In Chapter 3, a HU patterned post microchip (HU-chip) was designed. Then a CFD simulation was used to discover the flow conditions. Several tests, including the vector-formed and angular averaged spectral analysis of ordered lattice, random, and HU configurations, were made to further identify the flow pattern generated by the HU-chip. The results proved that the flow field, which has the characteristic of hyperuniform, can be generated under relevant low post packing fraction and flow rate. This unique flow pattern created by HU-chip was then applied in CTCs capture. In Chapter 4, HU-chips were made and applied in CTCs capture, and the results show the potential of CTC subtype identification. Multiple CTC cell lines were captured in HU-chip with good capture efficiency. Then, force and shear analyses were performed. And a database was built to match the locations in the HU-chip with the capture locations and related physical properties. In Chapter 5, a CTC subtype prediction model was built. Based on the locations, several visualized features from the experiment and simulation were found and used as the factors in the model. The final prediction accuracy of this model was 80%, with a specificity of 90%. In Chapter 6, the main conclusions, and scientific contributions of this dissertation, are followed by a list of recommendations for future study.
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