• Photonics Research
  • Vol. 12, Issue 8, 1627 (2024)
Rubing Li1,†, Yueyun Weng1,2,11,†, Shubin Wei1, Siyuan Lin1..., Jin Huang1, Congkuan Song3, Hui Shen4, Jinxuan Hou5, Yu Xu6, Liye Mei1,7, Du Wang1,12, Yujie Zou8, Tailang Yin8, Fuling Zhou4, Qing Geng3, Sheng Liu1,2 and Cheng Lei1,9,10,*|Show fewer author(s)
Author Affiliations
  • 1Institute of Technological Sciences, Wuhan University, Wuhan 430072, China
  • 2School of Power and Mechanical Engineering, Wuhan University, Wuhan 430072, China
  • 3Department of Thoracic Surgery, Renmin Hospital, Wuhan University, Wuhan 430060, China
  • 4Department of Hematology, Zhongnan Hospital, Wuhan University, Wuhan 430071, China
  • 5Department of Thyroid and Breast Surgery, Zhongnan Hospital, Wuhan University, Wuhan 430071, China
  • 6Department of Radiation and Medical Oncology, Zhongnan Hospital, Wuhan University, Wuhan 430071, China
  • 7School of Computer Science, Hubei University of Technology, Wuhan 430068, China
  • 8Reproductive Medical Center, Renmin Hospital, Wuhan University, Wuhan 430060, China
  • 9Suzhou Institute of Wuhan University, Suzhou 215000, China
  • 10Shenzhen Institute of Wuhan University, Shenzhen 518057, China
  • 11e-mail: wengyueyun@whu.edu.cn
  • 12e-mail: wangdu@whu.edu.cn
  • show less
    DOI: 10.1364/PRJ.523653 Cite this Article Set citation alerts
    Rubing Li, Yueyun Weng, Shubin Wei, Siyuan Lin, Jin Huang, Congkuan Song, Hui Shen, Jinxuan Hou, Yu Xu, Liye Mei, Du Wang, Yujie Zou, Tailang Yin, Fuling Zhou, Qing Geng, Sheng Liu, Cheng Lei, "Fourier-domain-compressed optical time-stretch quantitative phase imaging flow cytometry," Photonics Res. 12, 1627 (2024) Copy Citation Text show less
    References

    [1] P. Y. Liu, L. K. Chin, W. Ser. Cell refractive index for cell biology and disease diagnosis: past, present and future. Lab Chip, 16, 634-644(2016).

    [2] Y. Su, D. Chen, D. Yuan. Multi-omics resolves a sharp disease-state shift between mild and moderate COVID-19. Cell, 183, 1479-1495(2020).

    [3] N. Toepfner, C. Herold, O. Otto. Detection of human disease conditions by single-cell morpho-rheological phenotyping of blood. eLife, 7, e29213(2018).

    [4] Y. Weng, H. Shen, L. Mei. Typing of acute leukemia by intelligent optical time-stretch imaging flow cytometry on a chip. Lab Chip, 23, 1703-1712(2023).

    [5] A. Thakur, G. Qiu, C. Xu. Label-free sensing of exosomal MCT1 and CD147 for tracking metabolic reprogramming and malignant progression in glioma. Sci. Adv., 6, eaaz6119(2020).

    [6] Z. Deng, S. Wu, Y. Wang. Circulating tumor cell isolation for cancer diagnosis and prognosis. eBioMedicine, 83, 104237(2022).

    [7] F. Li, Y. Du, G. Pi. Long-term real-time tracking live stem cells/cancer cells in vitro/in vivo through highly biocompatible photoluminescent poly(citrate-siloxane) nanoparticles. Mater. Sci. Eng. C, 93, 380-389(2018).

    [8] X. Guan, F. Ma, C. Li. The prognostic and therapeutic implications of circulating tumor cell phenotype detection based on epithelial–mesenchymal transition markers in the first-line chemotherapy of HER2-negative metastatic breast cancer. Cancer Commun., 39, 1-10(2019).

    [9] A. Sharma, P. W. Burridge, W. L. McKeithan. High-throughput screening of tyrosine kinase inhibitor cardiotoxicity with human induced pluripotent stem cells. Sci. Transl. Med., 9, eaaf2584(2017).

    [10] C. E. Mills, K. Subramanian, M. Hafner. Multiplexed and reproducible high content screening of live and fixed cells using Dye Drop. Nat. Commun., 13, 6918(2022).

    [11] H. Zhang, L. L. Y. Chan, W. Rice. Novel high-throughput cell-based hybridoma screening methodology using the Celigo Image Cytometer. J. Immunol. Methods, 447, 23-30(2017).

    [12] P. Lang, K. Yeow, A. Nichols. Cellular imaging in drug discovery. Nat. Rev. Drug Discov., 5, 343-356(2006).

    [13] Y. Yao, L. He, L. Mei. Cell damage evaluation by intelligent imaging flow cytometry. Cytom. Part A, 103, 646-654(2023).

    [14] F. Wei, S. Wang, X. Gou. A review for cell-based screening methods in drug discovery. Biophys. Rep., 7, 504-516(2021).

    [15] B. Guo, C. Lei, H. Kobayashi. High-throughput, label-free, single-cell, microalgal lipid screening by machine-learning-equipped optofluidic time-stretch quantitative phase microscopy. Cytom. Part A, 91, 494-502(2017).

    [16] A. K. S. Lau, T. T. W. Wong, K. K. Y. Ho. Interferometric time-stretch microscopy for ultrafast quantitative cellular and tissue imaging at 1 μm. J. Biomed. Opt., 19, 076001(2014).

    [17] K. Goda, A. Fard, O. Malik. High-throughput optical coherence tomography at 800 nm. Opt. Express, 20, 19612-19617(2012).

    [18] Y. Zhou, A. Yasumoto, C. Lei. Intelligent classification of platelet aggregates by agonist type. eLife, 9, e52938(2020).

    [19] Y. K. Park, C. Depeursinge, G. Popescu. Quantitative phase imaging in biomedicine. Nat. Photonics, 12, 578-589(2018).

    [20] E. Cuche, F. Bevilacqua, C. Depeursinge. Digital holography for quantitative phase-contrast imaging. Opt. Lett., 24, 291-293(1999).

    [21] S. Aknoun, M. Yonnet, Z. Djabari. Quantitative phase microscopy for non-invasive live cell population monitoring. Sci. Rep., 11, 4409(2021).

    [22] L. Kastl, M. Isbach, D. Dirksen. Quantitative phase imaging for cell culture quality control. Cytom. Part A, 91, 470-481(2017).

    [23] W. J. Eldridge, A. Meiri, A. Sheinfeld. Fast wide-field photothermal and quantitative phase cell imaging with optical lock-in detection. Biomed. Opt. Express, 5, 2517-2525(2014).

    [24] C. L. Chen, A. Mahjoubfar, L. C. Tai. Deep learning in label-free cell classification. Sci. Rep., 6, 21471(2016).

    [25] B. Guo, C. Lei, Y. Wu. Optofluidic time-stretch quantitative phase microscopy. Methods, 136, 116-125(2018).

    [26] Y. Wu, Y. Zhou, C. J. Huang. Intelligent frequency-shifted optofluidic time-stretch quantitative phase imaging. Opt. Express, 28, 519-532(2020).

    [27] H. Yan, Y. Wu, Y. Zhou. Virtual optofluidic time-stretch quantitative phase imaging. APL Photonics, 5, 046103(2020).

    [28] Y. Weng, G. Wu, R. Li. Multiparameter investigation of diamond plates with optical time-stretch quantitative phase imaging. Cryst. Growth Des., 23, 388-394(2022).

    [29] B. T. Bosworth, J. R. Stroud, D. N. Tran. High-speed flow microscopy using compressed sensing with ultrafast laser pulses. Opt. Express, 23, 10521-10532(2015).

    [30] Q. Guo, H. Chen, Y. Wang. High-speed compressive microscopy of flowing cells using sinusoidal illumination patterns. IEEE Photonics J., 9, 3900111(2016).

    [31] R. Li, Y. Weng, S. Lin. All-optical Fourier-domain-compressed time-stretch imaging with low-pass filtering. ACS Photonics, 10, 2399-2406(2023).

    [32] Q. Guo, Y. Wang, H. Chen. Principles and applications of high-speed single-pixel imaging technology. Front. Inf. Technol. Electron. Eng., 18, 1261-1267(2017).

    [33] S. Lin, R. Li, Y. Weng. Optical time-stretch imaging flow cytometry in the compressed domain. J. Biophotonics, 16, e202300096(2023).

    [34] C. Szegedy, V. Vanhoucke, S. Ioffe. Rethinking the inception architecture for computer vision. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2818-2826(2016).

    [35] R. Schielein, S. Schröpfer, M. Kiunke. Quantitative evaluation of CT images by means of Shannon entropy. 11th European Conference on Non-Destructive Testing, 2-4(2014).

    [36] B. Arun, U. Akar, A. M. Gutierrez-Barrera. The PARP inhibitor AZD2281 (olaparib) induces autophagy/mitophagy in BRCA1 and BRCA2 mutant breast cancer cells. Int. J. Oncol., 47, 262-268(2015).

    [37] V. D. M. Laurens, G. Hinton. Visualizing data using t-SNE. J. Mach. Learn. Res., 9, 2579-2605(2008).

    Rubing Li, Yueyun Weng, Shubin Wei, Siyuan Lin, Jin Huang, Congkuan Song, Hui Shen, Jinxuan Hou, Yu Xu, Liye Mei, Du Wang, Yujie Zou, Tailang Yin, Fuling Zhou, Qing Geng, Sheng Liu, Cheng Lei, "Fourier-domain-compressed optical time-stretch quantitative phase imaging flow cytometry," Photonics Res. 12, 1627 (2024)
    Download Citation