Literature DB >> 32700785

Label-free discrimination and selection of cancer cells from blood during flow using holography-induced dielectrophoresis.

Matan Dudaie1, Noga Nissim1, Itay Barnea1, Tobias Gerling2, Claus Duschl2, Michael Kirschbaum2, Natan T Shaked1.   

Abstract

We present a method for label-free imaging and sorting of cancer cells in blood, which is based on a dielectrophoretic microfluidic chip and label-free interferometric phase microscopy. The chip used for imaging has been embedded with dielectrophoretic electrodes, and therefore it can be used to sort the cells based on the decisions obtained during the cell flow by the label-free quantitative imaging method. Hence, we obtained a real-time, automatic, label-free imaging flow cytometry with the ability to sort the cells during flow. To validate our model, we combined into the label-free imaging interferometer a fluorescence imaging channel that indicated the correctness of the label-free sorting. We have achieved above 98% classification success and 69% sorting accuracy at flow rates of 4 to 7 μL hr-1 . In the future, this method is expected to help in label-free sorting of circulating tumor cells in blood following an initial state-of-the-art cell enrichment.
© 2020 Wiley-VCH GmbH.

Entities:  

Keywords:  cell sorting; circulating tumor cell; dielectrophoresis; imaging flow cytometry; lab on a chip; quantitative phase microscopy

Mesh:

Year:  2020        PMID: 32700785     DOI: 10.1002/jbio.202000151

Source DB:  PubMed          Journal:  J Biophotonics        ISSN: 1864-063X            Impact factor:   3.207


  4 in total

1.  Erythrocyte volumetric measurements in imaging flow cytometry using simultaneous three-wavelength digital holographic microscopy.

Authors:  Nir A Turko; Natan T Shaked
Journal:  Biomed Opt Express       Date:  2020-10-22       Impact factor: 3.732

2.  BCNet: A Novel Network for Blood Cell Classification.

Authors:  Ziquan Zhu; Siyuan Lu; Shui-Hua Wang; Juan Manuel Górriz; Yu-Dong Zhang
Journal:  Front Cell Dev Biol       Date:  2022-01-03

3.  Cancer-Cell Deep-Learning Classification by Integrating Quantitative-Phase Spatial and Temporal Fluctuations.

Authors:  Shani Ben Baruch; Noa Rotman-Nativ; Alon Baram; Hayit Greenspan; Natan T Shaked
Journal:  Cells       Date:  2021-11-29       Impact factor: 6.600

4.  Sperm Inspection for In Vitro Fertilization via Self-Assembled Microdroplet Formation and Quantitative Phase Microscopy.

Authors:  Yuval Atzitz; Matan Dudaie; Itay Barnea; Natan T Shaked
Journal:  Cells       Date:  2021-11-26       Impact factor: 6.600

  4 in total

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