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Proceedings Paper

High-throughput time-stretch microscopy with morphological and chemical specificity
Author(s): Cheng Lei; Masashi Ugawa; Taisuke Nozawa; Takuro Ideguchi; Dino Di Carlo; Sadao Ota; Yasuyuki Ozeki; Keisuke Goda
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Paper Abstract

Particle analysis is an effective method in analytical chemistry for sizing and counting microparticles such as emulsions, colloids, and biological cells. However, conventional methods for particle analysis, which fall into two extreme categories, have severe limitations. Sieving and Coulter counting are capable of analyzing particles with high throughput, but due to their lack of detailed information such as morphological and chemical characteristics, they can only provide statistical results with low specificity. On the other hand, CCD or CMOS image sensors can be used to analyze individual microparticles with high content, but due to their slow charge download, the frame rate (hence, the throughput) is significantly limited. Here by integrating a time-stretch optical microscope with a three-color fluorescent analyzer on top of an inertial-focusing microfluidic device, we demonstrate an optofluidic particle analyzer with a sub-micrometer spatial resolution down to 780 nm and a high throughput of 10,000 particles/s. In addition to its morphological specificity, the particle analyzer provides chemical specificity to identify chemical expressions of particles via fluorescence detection. Our results indicate that we can identify different species of microparticles with high specificity without sacrificing throughput. Our method holds promise for high-precision statistical particle analysis in chemical industry and pharmaceutics.

Paper Details

Date Published: 7 March 2016
PDF: 6 pages
Proc. SPIE 9720, High-Speed Biomedical Imaging and Spectroscopy: Toward Big Data Instrumentation and Management, 97200X (7 March 2016); doi: 10.1117/12.2212670
Show Author Affiliations
Cheng Lei, The Univ. of Tokyo (Japan)
Tsinghua Univ. (China)
Masashi Ugawa, The Univ. of Tokyo (Japan)
Taisuke Nozawa, The Univ. of Tokyo (Japan)
Takuro Ideguchi, The Univ. of Tokyo (Japan)
Dino Di Carlo, Univ. of California, Los Angeles (United States)
Sadao Ota, The Univ. of Tokyo (Japan)
Yasuyuki Ozeki, The Univ. of Tokyo (Japan)
Keisuke Goda, The Univ. of Tokyo (Japan)
Univ. of California, Los Angeles (United States)
Japan Science and Technology Agency (Japan)


Published in SPIE Proceedings Vol. 9720:
High-Speed Biomedical Imaging and Spectroscopy: Toward Big Data Instrumentation and Management
Kevin K. Tsia; Keisuke Goda, Editor(s)

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