Cancer is a major health issue that has been associated with over 80 million deaths worldwide in the last decade. Recently, significant improvements have been made in terms of treatment and diagnosis. However, despite these advancements there is still a demand for low-cost, high-accuracy, and easy-to-use technologies capable of classifying cells. Analysis of cell behavior in microfluidic deformability assays provides a label-free method of observing cell response to physical and chemical stimuli. This body of work shows advancements made toward reaching our goal of a robust and cost-effective biosensing device that allows for the identification of normal and cancer cells. These devices can also monitor cell responses to physical and chemical stimuli in the form of mechanical deformation and chemotherapeutic drugs, respectively. Our initial design was a microfluidic device that consisted of three channels with varying deformation and relaxation regions. Cell velocities from the deformations regions allowed us to distinguish between normal and cancer cells at the single-cell level. The next design used a singular deformation channel that was embedded with an array of electrodes in order to measure entry time, transit time and velocities as a single cell passes through the channel. These factors were found to reveal information about the biomechanical properties of single cells. Embedded electrodes were implemented in order to reduce post processing times of the data analysis and provide more insight into the bioelectrical information of cells. Finally, we report a microfluidic device with parallel deformation channels and a single electrode pair to improve throughput and automate data collection of deformability assays. This thesis demonstrates how microfluidic deformability assays, with and without embedded electrodes, show promising capabilities to classify different cells based on their biophysical traits which can be utilized as a valuable tool for testing responses to physical and chemical stimuli. / MS
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/89947 |
| Date | 19 December 2017 |
| Creators | Ghassemi, Parham |
| Contributors | Electrical Engineering, Agah, Masoud, Zhu, Yizheng, Zhou, Wei |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf, application/x-zip-compressed |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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