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An optofluidic system with integrated microlens arrays for parallel imaging flow cytometry

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Abstract

In recent years, high-speed imaging has become increasingly effective for the rapid analysis of single cells in flowing environments. Single cell imaging methods typically incorporate a minimum magnification of 10× when extracting sizing and morphological information. Although information content may be significantly enhanced by increasing magnification, this is accompanied by a corresponding reduction in field of view, and thus a decrease in the number of cells assayed per unit time. Accordingly, the acquisition of high resolution data from wide field views remains an unsolved challenge. To address this issue, we present an optofluidic flow cytometer integrating a refractive, microlens array (MLA) for imaging cells at high linear velocities, whilst maximizing the number of cells per field of view. To achieve this, we adopt an elasto-inertial approach for cell focusing within an array of parallel microfluidic channels, each equipped with a microlens. We characterize the optical performance of the microlenses in terms of image formation, magnification and resolution using both ray-tracing simulations and experimental measurements. Results demonstrate that the optofluidic platform can efficiently count and magnify micron-sized objects up to 4 times. Finally, we demonstrate the capabilities of the platform as an imaging flow cyclometer, demonstrating the efficient discrimination of hB and Jurkat cells at throughputs up to 50 000 cells per second.

Graphical abstract: An optofluidic system with integrated microlens arrays for parallel imaging flow cytometry

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Publication details

The article was received on 11 Jun 2018, accepted on 15 Oct 2018 and first published on 22 Oct 2018


Article type: Paper
DOI: 10.1039/C8LC00593A
Citation: Lab Chip, 2018, Advance Article
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    An optofluidic system with integrated microlens arrays for parallel imaging flow cytometry

    G. Holzner, Y. Du, X. Cao, J. Choo, A. J. deMello and S. Stavrakis, Lab Chip, 2018, Advance Article , DOI: 10.1039/C8LC00593A

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