High-throughput microfluidic line scan imaging for cytological characterization

Joshua A. Hutcheson; Amy J. Powless; Aneeka A. Majid; Adair Claycomb; Ingrid Fritsch; Kartik Balachandran; Timothy J. Muldoon

doi:10.1117/12.2079946

5 March 2015 High-throughput microfluidic line scan imaging for cytological characterization

Joshua A. Hutcheson, Amy J. Powless, Aneeka A. Majid, Adair Claycomb, Ingrid Fritsch, Kartik Balachandran, Timothy J. Muldoon

Author Affiliations +

Proceedings Volume 9320, Microfluidics, BioMEMS, and Medical Microsystems XIII; 93200Y (2015) https://doi.org/10.1117/12.2079946
Event: SPIE BiOS, 2015, San Francisco, California, United States

Abstract

Imaging cells in a microfluidic chamber with an area scan camera is difficult due to motion blur and data loss during frame readout causing discontinuity of data acquisition as cells move at relatively high speeds through the chamber. We have developed a method to continuously acquire high-resolution images of cells in motion through a microfluidics chamber using a high-speed line scan camera. The sensor acquires images in a line-by-line fashion in order to continuously image moving objects without motion blur. The optical setup comprises an epi-illuminated microscope with a 40X oil immersion, 1.4 NA objective and a 150 mm tube lens focused on a microfluidic channel. Samples containing suspended cells fluorescently stained with 0.01% (w/v) proflavine in saline are introduced into the microfluidics chamber via a syringe pump; illumination is provided by a blue LED (455 nm). Images were taken of samples at the focal plane using an ELiiXA+ 8k/4k monochrome line-scan camera at a line rate of up to 40 kHz. The system’s line rate and fluid velocity are tightly controlled to reduce image distortion and are validated using fluorescent microspheres. Image acquisition was controlled via MATLAB’s Image Acquisition toolbox. Data sets comprise discrete images of every detectable cell which may be subsequently mined for morphological statistics and definable features by a custom texture analysis algorithm. This high-throughput screening method, comparable to cell counting by flow cytometry, provided efficient examination including counting, classification, and differentiation of saliva, blood, and cultured human cancer cells.

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Joshua A. Hutcheson, Amy J. Powless, Aneeka A. Majid, Adair Claycomb, Ingrid Fritsch, Kartik Balachandran, and Timothy J. Muldoon "High-throughput microfluidic line scan imaging for cytological characterization", Proc. SPIE 9320, Microfluidics, BioMEMS, and Medical Microsystems XIII, 93200Y (5 March 2015); https://doi.org/10.1117/12.2079946

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