Date of Graduation

5-2015

Document Type

Thesis

Degree Name

Bachelor of Science in Biomedical Engineering

Degree Level

Undergraduate

Department

Biomedical Engineering

Advisor/Mentor

Muldoon, Timothy J.

Abstract

We have demonstrated a method for conducting a leukocyte count in whole blood using a microfluidics chip and epi-fluorescence setup. Leukocyte counts provide physicians with a wealth of information about a patient’s medical condition and as such are routinely completed for many hospital visits. Miniaturization of this diagnostic tool may enable physicians to provide healthcare in resource-limited settings, where patients would otherwise not receive this test. The microfluidics chip was fabricated in polydimethylsiloxane (PDMS) using soft-film lithography. Following further processing and cleaning, the PDMS mold is exposed to UV-ozone for surface activation, and then sealed with a glass coverslip to create an enclosed chip. The epi-fluorescence microscope was constructed using a blue LED light source, excitation and emission filters, dichroic mirror, and objective lens. Prior to imaging leukocytes in whole blood, the optimal linear flow velocity in the microfluidics channel had to be determined to achieve minimal motion blur and sufficient signal-to-noise ratio. This was done by conducting a series of flow rate experiments in which fluorescent microspheres were seeded in phosphate-buffered saline (PBS) and pumped at various volumetric pump rates while simultaneously imaged with the epi-illuminating fluorescence microscop. These images were analyzed using ImageJ to determine average linear velocity of bead flow as it passed the image sensor. Values from this experiment were used to pump leukocytes at an optimal rate for image acquisition. Minimal pre-processing of the sample was completed with an anticoagulation agent, which prevents clogging within the channel, and proflavine, a fluorophore used to stain the nuclei of the leukocytes for imaging. The processed blood sample was then pumped into the chip and imaged simultaneously. Image data was gathered and processed to separate between populations of leukocytes based on nuclear morphology. In this particular system, a 3-part differential can be completed to distinguish between monocytes, lymphocytes, and granulocytes.

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