Abstract

We propose a line-field quantitative phase-imaging flow cytometer for analyzing large populations of label-free cells. Hydrodynamical focusing brings cells into the focus plane of an optical system while diluting the cell suspension, resulting in decreased throughput rate. To overcome the trade-off between throughput rate and in-focus imaging, our cytometer involves digitally extending the depth-of-focus on loosely hydrodynamically focusing cell suspensions. The cells outside the depth-of-focus range in the 70-µm diameter of the core flow were automatically digitally refocused after image acquisition. We verified that refocusing was successful with our cytometer through statistical analysis of image quality before and after digital refocusing.

© 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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References

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2019 (2)

Y. Ozaki, H. Yamada, H. Kikuchi, A. Hirotsu, T. Murakami, T. Matsumoto, T. Kawabata, Y. Hiramatsu, K. Kamiya, T. Yamauchi, K. Goto, Y. Ueda, S. Okazaki, M. Kitagawa, H. Takeuchi, and H. Konno, “Label-free classification of cells based on supervised machine learning of subcellular structures,” PLoS One 14(1), e0211347 (2019).
[Crossref]

Y. Li, A. Mahjoubfar, C. L. Chen, K. R. Niazi, L. Pei, and B. Jalali, “Deep Cytometry: Deep learning with Real-time Inference in Cell Sorting and Flow Cytometry,” Sci. Rep. 9(1), 1–12 (2019).
[Crossref]

2018 (5)

H. S. Park, S. Ceballos, W. J. Eldridge, and A. Wax, “Digital refocusing in quantitative phase imaging for flowing red blood cells,” APL Photonics 3(11), 110802 (2018).
[Crossref]

H. Mikami, J. Harmon, H. Kobayashi, S. Hamad, Y. Wang, O. Iwata, K. Suzuki, T. Ito, Y. Aisaka, N. Kutsuna, K. Nagasawa, H. Watarai, Y. Ozeki, and K. Goda, “Ultrafast confocal fluorescence microscopy beyond the fluorescence lifetime limit,” Optica 5(2), 117 (2018).
[Crossref]

N. Nitta, T. Sugimura, A. Isozaki, H. Mikami, K. Hiraki, S. Sakuma, T. Iino, F. Arai, T. Endo, Y. Fujiwaki, H. Fukuzawa, M. Hase, T. Hayakawa, K. Hiramatsu, Y. Hoshino, M. Inaba, T. Ito, H. Karakawa, Y. Kasai, K. Koizumi, S. Lee, C. Lei, M. Li, T. Maeno, S. Matsusaka, D. Murakami, A. Nakagawa, Y. Oguchi, M. Oikawa, T. Ota, K. Shiba, H. Shintaku, Y. Shirasaki, K. Suga, Y. Suzuki, N. Suzuki, Y. Tanaka, H. Tezuka, C. Toyokawa, Y. Yalikun, M. Yamada, M. Yamagishi, T. Yamano, A. Yasumoto, Y. Yatomi, M. Yazawa, D. Di Carlo, Y. Hosokawa, S. Uemura, Y. Ozeki, and K. Goda, “Intelligent image-activated cell sorting,” Cell 175(1), 266–276.e13 (2018).
[Crossref]

G. Dardikman, Y. N. Nygate, I. Barnea, N. A. Turko, G. Singh, B. Javidi, and N. T. Shaked, “Integral refractive index imaging of flowing cell nuclei using quantitative phase microscopy combined with fluorescence microscopy,” Biomed. Opt. Express 9(3), 1177–1189 (2018).
[Crossref]

D. Dannhauser, D. Rossi, P. Memmolo, A. Finizio, P. Ferraro, P. A. Netti, and F. Causa, “Biophysical investigation of living monocytes in flow by collaborative coherent imaging techniques,” Biomed. Opt. Express 9(11), 5194–5204 (2018).
[Crossref]

2017 (6)

A. S. Rane, J. Rutkauskaite, A. deMello, and S. Stavrakis, “High-throughput multi-parametric imaging flow cytometry,” Chem 3(4), 588–602 (2017).
[Crossref]

D. Jin, Y. Sung, N. Lue, Y.-H. Kim, P. T. C. So, and Z. Yaqoob, “Large population cell characterization using quantitative phase cytometer,” Cytometry, Part A 91(5), 450–459 (2017).
[Crossref]

B. Guo, C. Lei, H. Kobayashi, T. Ito, Y. Yalikun, Y. Jiang, Y. Tanaka, Y. Ozeki, and K. Goda, “High-throughput, label-free, single-cell, microalgal lipid screening by machine-learning-equipped optofluidic time-stretch quantitative phase microscopy,” Cytometry, Part A 91(5), 494–502 (2017).
[Crossref]

Y. Zhang, H. Wang, Y. Wu, M. Tamamitsu, and A. Ozcan, “Edge sparsity criterion for robust holographic autofocusing,” Opt. Lett. 42(19), 3824–3827 (2017).
[Crossref]

S. K. Mohammed, L. Bouamama, D. Bahloul, and P. Picart, “Quality assessment of refocus criteria for particle imaging in digital off-axis holography,” Appl. Opt. 56(13), F158–F166 (2017).
[Crossref]

F. Merola, P. Memmolo, L. Miccio, R. Savoia, M. Mugnano, A. Fontana, G. D’Ippolito, A. Sardo, A. Iolascon, A. Gambale, and P. Ferraro, “Tomographic flow cytometry by digital holography,” Light: Sci. Appl. 6(4), e16241 (2017).
[Crossref]

2016 (4)

S. Torino, M. Iodice, I. Rendina, G. Coppola, and E. Schonbrun, “A microfluidic approach for inducing cell rotation by means of hydrodynamic forces,” Sensors 16(8), 1326 (2016).
[Crossref]

T. Blasi, H. Hennig, H. D. Summers, F. J. Theis, J. Cerveira, J. O. Patterson, D. Davies, A. Filby, A. E. Carpenter, and P. Rees, “Label-free cell cycle analysis for high-throughput imaging flow cytometry,” Nat. Commun. 7(1), 10256 (2016).
[Crossref]

C. L. Chen, A. Mahjoubfar, L.-C. Tai, I. K. Blaby, A. Huang, K. R. Niazi, and B. Jalali, “Deep learning in label-free cell classification,” Sci. Rep. 6(1), 21471 (2016).
[Crossref]

Y. Han, Y. Gu, A. Zhang, and Y.-H. Lo, “Review: Imaging technologies for flow cytometry,” Lab Chip 16(24), 4639–4647 (2016).
[Crossref]

2015 (3)

V. Bianco, M. Paturzo, V. Marchesano, I. Gallotta, E. D. Schiavi, and P. Ferraro, “Optofluidic holographic microscopy with custom field of view (FoV) using a linear array detector,” Lab Chip 15(9), 2117–2124 (2015).
[Crossref]

P. Memmolo, L. Miccio, M. Paturzo, G. D. Caprio, G. Coppola, P. A. Netti, and P. Ferraro, “Recent advances in holographic 3D particle tracking,” Adv. Opt. Photonics 7(4), 713–755 (2015).
[Crossref]

M. T. Rinehart, H. S. Park, and A. Wax, “Influence of defocus on quantitative analysis of microscopic objects and individual cells with digital holography,” Biomed. Opt. Express 6(6), 2067–2075 (2015).
[Crossref]

2014 (3)

Y.-D. Zhang, S. Wang, G. Ji, and Z. Dong, “An improved quality guided phase unwrapping method and its applications to MRI,” Prog. Electromagn. Res. 145, 273–286 (2014).
[Crossref]

Y. Sung, N. Lue, B. Hamza, J. Martel, D. Irimia, R. R. Dasari, W. Choi, Z. Yaqoob, and P. So, “Three-dimensional holographic refractive-index measurement of continuously flowing cells in a microfluidic channel,” Phys. Rev. Appl. 1(1), 014002 (2014).
[Crossref]

H. Iwai, T. Yamauchi, M. Miwa, and Y. Yamashita, “Doppler-spectrally encoded imaging of translational objects,” Opt. Commun. 319, 159–169 (2014).
[Crossref]

2013 (2)

K. Lee, K. Kim, J. Jung, J. Han Heo, S. Cho, L. Sangyun, G. Y. Chang, Y. Ju Jo, H. Park, and Y. Park, “Quantitative Phase Imaging Techniques for the Study of Cell Pathophysiology: From Principles to Applications,” Sensors 13(4), 4170–4191 (2013).
[Crossref]

A. Mahjoubfar, C. Chen, K. R. Niazi, S. Rabizadeh, and B. Jalali, “Label-free high-throughput cell screening in flow,” Biomed. Opt. Express 4(9), 1618–1625 (2013).
[Crossref]

2012 (2)

K. Goda, A. Ayazi, D. R. Gossett, J. Sadasivam, C. K. Lonappan, E. Sollier, A. M. Fard, S. C. Hur, J. Adam, C. Murray, C. Wang, N. Brackbill, D. D. Carlo, and B. Jalali, “High-throughput single-microparticle imaging flow analyzer,” Proc. Natl. Acad. Sci. 109(29), 11630–11635 (2012).
[Crossref]

N. Sugiyama, Y. Asai, T. Yamauchi, T. Kataoka, T. Ikeda, H. Iwai, T. Sakurai, and Y. Mizuguchi, “Label-free characterization of living human induced pluripotent stem cells by subcellular topographic imaging technique using full-field quantitative phase microscopy coupled with interference reflection microscopy,” Biomed. Opt. Express 3(9), 2175–2183 (2012).
[Crossref]

2011 (1)

2008 (3)

2007 (1)

2006 (1)

2004 (1)

2001 (1)

A. Givan, “Chapter 2 Principles of flow cytometry: An overview,” Methods Cell Biol. 63, 19–50 (2001).
[Crossref]

1991 (1)

J. F. Keij, A. van Rotterdam, A. C. Groenewegen, W. Stokdijk, and J. W. Visser, “Coincidence in high-speed flow cytometry: models and measurements,” Cytometry 12(5), 398–404 (1991).
[Crossref]

1977 (1)

G. W. Zack, W. E. Rogers, and S. A. Latt, “Automatic measurement of sister chromatid exchange frequency,” J. Histochem. Cytochem. 25(7), 741–753 (1977).
[Crossref]

Adam, J.

K. Goda, A. Ayazi, D. R. Gossett, J. Sadasivam, C. K. Lonappan, E. Sollier, A. M. Fard, S. C. Hur, J. Adam, C. Murray, C. Wang, N. Brackbill, D. D. Carlo, and B. Jalali, “High-throughput single-microparticle imaging flow analyzer,” Proc. Natl. Acad. Sci. 109(29), 11630–11635 (2012).
[Crossref]

Aisaka, Y.

Arai, F.

N. Nitta, T. Sugimura, A. Isozaki, H. Mikami, K. Hiraki, S. Sakuma, T. Iino, F. Arai, T. Endo, Y. Fujiwaki, H. Fukuzawa, M. Hase, T. Hayakawa, K. Hiramatsu, Y. Hoshino, M. Inaba, T. Ito, H. Karakawa, Y. Kasai, K. Koizumi, S. Lee, C. Lei, M. Li, T. Maeno, S. Matsusaka, D. Murakami, A. Nakagawa, Y. Oguchi, M. Oikawa, T. Ota, K. Shiba, H. Shintaku, Y. Shirasaki, K. Suga, Y. Suzuki, N. Suzuki, Y. Tanaka, H. Tezuka, C. Toyokawa, Y. Yalikun, M. Yamada, M. Yamagishi, T. Yamano, A. Yasumoto, Y. Yatomi, M. Yazawa, D. Di Carlo, Y. Hosokawa, S. Uemura, Y. Ozeki, and K. Goda, “Intelligent image-activated cell sorting,” Cell 175(1), 266–276.e13 (2018).
[Crossref]

Asai, Y.

Ayazi, A.

K. Goda, A. Ayazi, D. R. Gossett, J. Sadasivam, C. K. Lonappan, E. Sollier, A. M. Fard, S. C. Hur, J. Adam, C. Murray, C. Wang, N. Brackbill, D. D. Carlo, and B. Jalali, “High-throughput single-microparticle imaging flow analyzer,” Proc. Natl. Acad. Sci. 109(29), 11630–11635 (2012).
[Crossref]

Badizadegan, K.

Bahloul, D.

Barnea, I.

Bianco, V.

V. Bianco, M. Paturzo, V. Marchesano, I. Gallotta, E. D. Schiavi, and P. Ferraro, “Optofluidic holographic microscopy with custom field of view (FoV) using a linear array detector,” Lab Chip 15(9), 2117–2124 (2015).
[Crossref]

Blaby, I. K.

C. L. Chen, A. Mahjoubfar, L.-C. Tai, I. K. Blaby, A. Huang, K. R. Niazi, and B. Jalali, “Deep learning in label-free cell classification,” Sci. Rep. 6(1), 21471 (2016).
[Crossref]

Blasi, T.

T. Blasi, H. Hennig, H. D. Summers, F. J. Theis, J. Cerveira, J. O. Patterson, D. Davies, A. Filby, A. E. Carpenter, and P. Rees, “Label-free cell cycle analysis for high-throughput imaging flow cytometry,” Nat. Commun. 7(1), 10256 (2016).
[Crossref]

Bouamama, L.

Brackbill, N.

K. Goda, A. Ayazi, D. R. Gossett, J. Sadasivam, C. K. Lonappan, E. Sollier, A. M. Fard, S. C. Hur, J. Adam, C. Murray, C. Wang, N. Brackbill, D. D. Carlo, and B. Jalali, “High-throughput single-microparticle imaging flow analyzer,” Proc. Natl. Acad. Sci. 109(29), 11630–11635 (2012).
[Crossref]

Callens, N.

Caprio, G. D.

P. Memmolo, L. Miccio, M. Paturzo, G. D. Caprio, G. Coppola, P. A. Netti, and P. Ferraro, “Recent advances in holographic 3D particle tracking,” Adv. Opt. Photonics 7(4), 713–755 (2015).
[Crossref]

Carlo, D. D.

K. Goda, A. Ayazi, D. R. Gossett, J. Sadasivam, C. K. Lonappan, E. Sollier, A. M. Fard, S. C. Hur, J. Adam, C. Murray, C. Wang, N. Brackbill, D. D. Carlo, and B. Jalali, “High-throughput single-microparticle imaging flow analyzer,” Proc. Natl. Acad. Sci. 109(29), 11630–11635 (2012).
[Crossref]

Carpenter, A. E.

T. Blasi, H. Hennig, H. D. Summers, F. J. Theis, J. Cerveira, J. O. Patterson, D. Davies, A. Filby, A. E. Carpenter, and P. Rees, “Label-free cell cycle analysis for high-throughput imaging flow cytometry,” Nat. Commun. 7(1), 10256 (2016).
[Crossref]

Causa, F.

Ceballos, S.

H. S. Park, S. Ceballos, W. J. Eldridge, and A. Wax, “Digital refocusing in quantitative phase imaging for flowing red blood cells,” APL Photonics 3(11), 110802 (2018).
[Crossref]

Cereghetti, G.

G. Holzner, B. Mateescu, D. van Leeuwen, G. Cereghetti, R. Dechant, A. deMello, and S. Stavrakis, “Ultra high-throughput multiparametric imaging flow cytometry: Towards diffraction-limited sub-cellular detection,” bioRxiv 695361 (2019).

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Supplementary Material (1)

NameDescription
» Visualization 1       Dynamic sheath-flow condition

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Figures (6)

Fig. 1.
Fig. 1. Schematic of interferometer set-up. A1, A2; acousto-optic modulators (AOMs), CL1, CL2; cylindrical lenses, O1; objective lens 20×, NA0.45 having correction collar, O2; objective lens 20×, NA0.50, T; tube lens f = 250 mm, FC; flow-cell, inner square 250 µm × 250 µm, P1; object plane in focus, P2; Fourier plane, P3; image plane, P: linear-array sensor having 1 pixel × 2,048 pixels whose square size Δp is 7 µm × 7 µm.
Fig. 2.
Fig. 2. Photograph of microfluidic channel and interferograms. (a) Line-illumination of sample light across microfluidic channel with illumination light, (b) line-shaped interferogram across microfluidic channel, (c) 2D interferogram built up by successive 10,000 scan lines in 125 msec, and (d) cropped image of single cell in interferogram.
Fig. 3.
Fig. 3. (a) Schematic of acquired image of a sample. (b) Ellipsoidal quadratic phase in Eq. (5). (c) The minimum search of GRA in the refocus distance range of –66.5 to +66.5 µm. (d) Original (defocus) hologram of a bead. (e) Automatically digitally refocused hologram of the bead. In each panel, the left sides are amplitude images, and the right sides are phase images. The yellow profiles are the cross-sections on the white lines.
Fig. 4.
Fig. 4. (a) Ellipsoidal quadratic phase in Eq. (5). (b) The minimum search of GRA in the refocus distance range of –66.5 to +66.5 µm. (c) Original (defocus) hologram of a single cell. (d) Automatically digitally refocused hologram of the single cell. In each panel, the left side is an amplitude image, and the right side is a phase image. The yellow profiles are the cross-sections on the white lines.
Fig. 5.
Fig. 5. Lateral and longitudinal distributions of cells in the microfluidic channel. (a) Lateral (x-z plane) distribution of positions across the microfluidic channel, and horizontal and vertical projections of the distribution in bar-graphs. (b) Probability (bars) and its cumulative probability (red curve) of the inverse of dy. Upper horizontal axis represents the distances (1,000 dy) between any two successive cells in the y-direction. Lower horizontal axis represents the spatial frequency of cells in the y-direction.
Fig. 6.
Fig. 6. Changes in the ratio of projection areas and standard deviations of cell images before and after digital refocusing.

Equations (6)

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n t = V n s = V ( C A c ) ,
d c = d t [ q c / ( q c + q s h ) ] 1 / 2 ,
u n = ( I 4 n + 1 I 4 n + 3 ) + i ( I 4 n + 2 I 4 n + 4 )
F [ o ( x , y , d ) ] = O ( u , v , d ) = O ( u , v , 0 ) e x p ( i φ ) ,
φ = π λ n d ( u 2 + v 2 ) ,
F u = M Δ p , F v = b a F u