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Nanotechnol. Precis. Eng. 5, 045002 (2022); https://doi.org/10.1063/10.0015301 5, 045002
© 2022 Author(s).
Demands and technical developments
of clinical flow cytometry with emphasis
in quantitative, spectral, and imaging
capabilities
Cite as: Nanotechnol. Precis. Eng. 5, 045002 (2022); https://doi.org/10.1063/10.0015301
Submitted: 22 October 2022 • Accepted: 10 November 2022 • Published Online: 29 November 2022
Ting Zhang, Mengge Gao, Xiao Chen, et al.
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Nanotechnology and
Precision Engineering REVIEW scitation.org/journal/npe
Demands and technical developments of clinical
flow cytometry with emphasis in quantitative,
spectral, and imaging capabilities
Cite as: Nano. Prec. Eng. 5, 045002 (2022); doi: 10.1063/10.0015301
Submitted: 22 October 2022 •Accepted: 10 November 2022 •
Published Online: 29 November 2022
Ting Zhang,1,2Mengge Gao,3Xiao Chen,1,2Chiyuan Gao,1,2Shilun Feng,4Deyong Chen,1,2,5Junbo Wang,1,2,5,a)
Xiaosu Zhao,3,a) and Jian Chen1,2,5, a)
AFFILIATIONS
1State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences,
Beijing 100190, People’s Republic of China
2School of Future Technology, University of Chinese Academy of Sciences, Beijing 100049, People’s Republic of China
3Peking University People’s Hospital, Peking University Institute of Hematology, National Clinical Research Center for
Hematologic Disease, Beijing Key Laboratory of Hematopoietic Stem Cell Transplantation,
Beijing 100044, People’s Republic of China
4State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology,
Chinese Academy of Sciences, Shanghai 200050, People’s Republic of China
5School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences,
Beijing 100049, People’s Republic of China
a)Authors to whom correspondence should be addressed: jbwang@mail.ie.ac.cn;Zhao.xiaosu@outlook.com;
and chenjian@mail.ie.ac.cn.Tel.: +86-10-58887256
ABSTRACT
As the gold-standard method for single-cell analysis, flow cytometry enables high-throughput and multiple-parameter characterization
of individual biological cells. This review highlights the demands for clinical flow cytometry in laboratory hematology (e.g., diagnoses of
minimal residual disease and various types of leukemia), summarizes state-of-the-art clinical flow cytometers (e.g., FACSLyricTM by Becton
Dickinson, DxFLEX by Beckman Coulter), then considers innovative technical improvements in flow cytometry (including quantitative, spec-
tral, and imaging approaches) to address the limitations of clinical flow cytometry in hematology diagnosis. Finally, driven by these clinical
demands, future developments in clinical flow cytometry are suggested.
©2022 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license
(http://creativecommons.org/licenses/by/4.0/). https://doi.org/10.1063/10.0015301
KEYWORDS
Clinical demand, Clinical flow cytometry, Quantitative flow cytometry, Spectral flow cytometry, Imaging flow cytometry
I. INTRODUCTION
Flow cytometry (FCy) is a precision technique in which sin-
gle cells labeled with fluorescent probes travel rapidly through
multiple laser beams, and the corresponding light scatterings and
fluorescence emissions are captured by optical detectors. As the
gold-standard technique for single-cell analysis, FCy enables high-
throughput and multiple-parameter characterization of individual
biological cells, which then allows cells to be separated and sorted
into subpopulations.
Historically, the first flow cytometer (FCr) was the ICP 11
(ICP stands for impulse cytophotometer) developed in 1968 by
Partec, in which light absorption was used for optical characteriza-
tion. In 1971, Bio/Physics Systems developed the Cytofluorograph
FCr, which measured forward light scattering and two fluorescence
emissions. In 1974, Becton Dickinson commercialized the FACS II
Nano. Prec. Eng. 5, 045002 (2022); doi: 10.1063/10.0015301 5, 045002-1
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FIG. 1. Framework of key points
of present review, including clinical
demands, state-of-the-art technical
capabilities, and challenges and future
directions.
FCr, which integrated single-cell optical measurements and physical
sorting based on droplet deflection.
Since the 1980s, FCr manufacturers have competed over how
many parameters can be measured simultaneously. Specifically, in
the 1980s, the EPICS C FCr of Coulter Electronics and the FACScan
FCr of Becton Dickinson were capable of three-color analysis; then
in the 1990s, simultaneous measurements of seven fluorescent mark-
ers were achieved by the PAS-III FCr of Partec; and in the 2000s,
the LSR II FCr of Becton Dickinson could sample 14 parameters of
single cells. Currently, the best FCrs can measure ca. 50 parameters
simultaneously by using ca. 10 lasers (e.g., the FACSymphony A5
FCr of BD Biosciences).
In this review, the demands for clinical FCy in laboratory hema-
tology [e.g., for diagnosing minimal residual disease (MRD) and
various types of leukemia] are introduced in detail, followed by
details about state-of-the-art instruments for clinical FCy (e.g., the
FACSLyricTM FCr of Becton Dickinson and the DxFLEX FCr of
Beckman Coulter) to meet these clinical demands. Then, innova-
tive technical improvements in FCy including quantitative, spectral,
and imaging approaches are included to address the limitations of
clinical FCy in hematology diagnosis. Finally, driven by these clin-
ical demands, future developments in clinical FCy are suggested.
In Fig. 1, the key points including clinical demands, state-of-the-
art technical capabilities, and challenges and future directions are
summarized as a framework.
II. CLINICAL DEMANDS
The demands for clinical FCy are mainly for diagnosing
acute myeloid leukemia (AML), mixed phenotype acute leukemia
(MPAL), acute lymphoblastic leukemia (ALL), chronic lympho-
cytic leukemia (CLL), and MRD, for which clinical FCy with three
lasers and ca. 10 colors is generally used to characterize the expres-
sion status of the surface or intracellular antigens of hematopoietic
cells, leveraging a combination of multiple antibodies with various
fluorescence markers (see Table I).1–3
In the clinical classification of AML, the antibodies CD34,
CD117, HLA-DR, and CD45 are “skeleton” antibodies for clini-
cal FCy. Other myeloid markers such as cytoplasmic myeloper-
oxidase (cyMPO), CD13, CD33, and CD38 distinguish nor-
mal and abnormal hematopoietic cells, playing key roles in
myelodysplastic syndrome-transformed AML. In addition, myeloid
markers (CD11b, CD15, CD64, and CD65), monocytic markers
(CD14, CD36, CD64, CD4, CD38, and CD11c), megakaryocytic
markers (CD41, CD61, and CD36), and erythroid markers (CD235a,
CD71, and CD36) are included for precise diagnosis of AML.
In MPAL, the expressions of cyMPO, CD3, and CD19 play key
roles in determining the differentiation characteristics of myeloid
and T/B-lineage leukemia cells, respectively. Among myeloid molec-
ular markers, cyMPO is positive or two or more monocytic markers
(CD14, CD11C, CD36, CD64, lysozyme) are positive, indicating
the existence of myeloid phenotype leukemia cells. For B-lineage of
MPAL, the diagnosis meets the requirements of strong CD19 with at
least one B-lineage molecular marker (CD79a, cell surface or cyto-
plasm CD22, CD10) strongly expressed, or weak CD19 with at least
two B-lineage molecular markers strongly expressed. T-lineage of
MPAL is diagnosed by high expressions of CD3 in the cytoplasm
or cell surface.
As for other types of leukemia, marker combinations of CD19,
CD79a, and CD22 are used to diagnose B-lineage ALL, while CD3,
CD2, CD7, and CD1a are used to classify T-lineage ALL based on
FCy. When CLL is diagnosed, typical immunophenotypes of FCy
include CD19+, CD5+, CD23+, CD200+, CD10-, FMC7-, CD43+,
and weak expressions (dim) of CD20 and CD79b.
MRD refers to the residual tumor cells that cannot be
detected by morphology and other traditional methods after achiev-
ing the hematological complete remission of hematologic malig-
nancies. FCy detects MRD by analyzing the expression patterns
of a series of cell-surface or intracellular antigens to identify
the immunophenotypes that appear only in leukemia cells and
either do not exist or have a very low proportion in normal
bone marrow cells, i.e., leukemia-associated immunophenotypes
(LAIPs).
The antigens selected for the detection of MRD are of three
main types. First, the antigens used for gate setting are a series of
highly sensitive antigens that can preliminarily delineate all cells
in a certain series, such as cytoplasmic CD3 (cyCD3) or CD7 of
T-lineage, CD19 of B-lineage, CD117 of myeloid, and CD38 and
CD138 of plasma cells. Second, there are those antigens that iden-
tify early differentiation of the corresponding series, recognizing the
series of primitive and naive cell populations and subtypes, such as
CD45, CD10, CD34 and nuclear TdT (nTdT) of B-lineage, CD3,
Nano. Prec. Eng. 5, 045002 (2022); doi: 10.1063/10.0015301 5, 045002-2
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TABLE I. Summary of demands for clinical flow cytometry (FCy).
Disease Markers Sub-diseases Sub-markers
Acute myeloid leukemia (AML) CD34, CD117, HLA-DR, CD45
Hematopoietic cyMPO, CD13, CD33, CD38
Myeloid CD11b, CD15, CD64, CD65
Monocytic CD14, CD36, CD64, CD4,
CD38, CD11c
Megakaryocytic CD41, CD61, CD36
Erythroid CD235a, CD71, CD36
Mixed phenotype acute leukemia (MPAL) cyMPO, CD3, CD19
Myeloid cyMPO, CD14, CD11C, CD36,
CD64, lysozyme
T-lineage cyCD3 and mCD3
B-lineage CD19, CD79a, CD22, CD10
Acute lymphoblastic leukemia (ALL) T-lineage CD3, CD2, CD7, CD1a
B-lineage CD19, CD79a, CD22
Chronic lymphocytic leukemia (CLL) CD19, CD5, CD23, CD200, CD10, FMC7, CD43, CD20, CD79b
Minimal residual disease (MRD) cyCD3, CD7, CD19, CD117, CD38, CD138 Myeloid CD34, CD117, HLA-DR, CD38
T lineage CD3, CD34, nTdT, CD99
B lineage CD45, CD10, CD34, nTdT
CD34, nTdT, CD99 of T-lineage, and CD34, CD117, HLA-DR, and
CD38 of myeloid. Third, there are leukemia-related abnormal anti-
gens can distinguish leukemia cells from the corresponding series of
normal immature cells, referring mainly to the antigens involved in
LAIPs.
III. CLINICAL FLOW CYTOMETERS
A. FACSLyricTM
FACSLyricTM by BD Biosciences is a state-of-the-art clinical
FCr that can quantify 12 colors based on three lasers of blue, red,
TABLE II. Summary of key performance details of commercially available clinical, spectral, and imaging flow cytometers (FCrs).
Type Instrument Manufacturer Optical setup Key performance details
Clinical
FACSLyricTM BD Three lasers with beam dimensions of Throughput of 35 000 events per second and sensitivities
Biosciences 9 μm×63 μm in ellipse and 12 channels of <85 MESF for FITC and <20 MESF for PE
DxFLEX Beckman Three lasers with beam dimensions of Throughput of 30 000 events per second and sensitivities
Coulter 5 μm×80 μm in ellipse and 13 channels of <30 MESF for FITC and <10 MESF for PE
XF-1600 Sysmex Three lasers and 10 channels Throughput of 50 000 events per second and sensitivities
of <100 MESF for FITC, <50 MESF
for PE, and <100 MESF for APC
NovoCyte Agilent Three lasers and 11 channels Throughput of 35 000 events per second
Spectral
ID7000 Sony Seven lasers and 186 PMTs Wavelengths of 360–920 nm with 44 colors
Northern Cytek Three lasers and arrays of APD based on Wavelengths of 420–829 nm and throughput
Lights coarse wavelength division multiplexing of 35 000 events per second
Symphony BD Five lasers and 48 PMTs Wavelengths of 365–880 nm, throughput of 40 000
A5 SE Biosciences events, per second and sensitivities of <80 MESF
for FITC, 20 MESF for PE, and <70 MESF for APC
Thermo Thermo Nine lasers and 60 PMTs Throughput of >100 000 events per second and
Big Foot Scientific sensitivities of <100 MESF for FITC, PE, and APC
Imaging ImageStream Six lasers and 12 channels Throughput of 5000 events per second
X Mk II Amnis
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and violet with a beam spot of 9 μm×63 μm in an ellipse. The
flow cell is made of stainless steel with a low coefficient of ther-
mal expansion and is aligned with the measurement quartz cuvette
with an internal cross section of 430 μm×180 μm. This instrument
runs at a throughput of 35 000 events per second with sensitivities of
<85 MESF (molecules of equivalent soluble fluorochrome) for fluo-
rescein isothiocyanat (FITC) and <20 MESF for phycoerythrin (PE)
(see Table II).
B. DxFLEX
DxFLEX by Beckman Coulter is a state-of-the-art clinical FCr
that can quantify 13 colors based on three lasers of blue, red, and
violet with a beam spot of 5 μm×80 μm in an ellipse. The alignment-
free integrated-optics quartz flow cell has an internal cross section of
420 μm×180 μm, and this instrument runs at a throughput of 30 000
events per second with sensitivities of <30 MESF for FITC and <10
MESF for PE (see Table II).
C. Others
XF-1600 by Sysmex is a state-of-the-art clinical FCr that can
quantify 10 colors based on three lasers; this instrument runs at a
throughput of 50000 events per second with sensitivities of <100
MESF for FITC, <50 MESF for PE, and <100 MESF for allophyco-
cyanine (APC) (see Table II). NovoCyte by Agilent is a state-of-the-
art clinical FCr than can quantify 11 colors based on three lasers, and
this instrument runs at a throughput of 35 000 events per second (see
Table II).
IV. CUTTING-EDGE DEVELOPMENTS
Although clinical FCy has been developed for decades, it still
has several key technical limitations, i.e., (i) its results are usu-
ally qualitative rather than quantitative, (ii) it suffers from spectral
overlaps, and (iii) it cannot capture cell and nuclear morphological
information simultaneously. To address these issues, cutting-edge
developments in clinical FCy are focused on quantitative FCy,
spectral FCy, and imaging FCy, which are described in detail as
follows.
A. Quantitative flow cytometry
In conventional FCy, the results can only be characterized
with features such as dim/intermediate/bright, negative/positive, or
arbitrary units of fluorescence intensities. However, in quantita-
tive FCy, the fluorescent intensities of labeled cell samples can be
translated into molecules of antibody binding per cell (ABC), for
which calibration curves relating fluorescence intensities to stan-
dardized ABC values are obtained by flushing calibration mate-
rials with well-defined molecular numbers of fluorochromes into
the FCr.4–8
As shown in Fig. 2, the dimensions of the laser beam spots
in the FCr are ca. 10 μm×50 μm in an ellipse. Because the opti-
cal intensities in the detection region are not distributed evenly,
in quantitative FCy, the fluorescent distributions of the calibration
materials should be comparable with those of the labeled bio-
logical cells. As shown in Fig. 2(a), calibration microbeads with
surface modifications are the gold-standard calibration material for
quantifying the ABC of biological cells, allowing the expressions
of specific surface antigens to be measured quantitatively.9–14
FIG. 2. Key technical developments
in quantitative FCy: (a) calibration
microbeads for quantitative analysis
of specific membrane proteins; (b)
constriction microchannels for quanti-
tative analysis of specific intracellular
proteins; (c) droplet microfluidics for
quantitative analysis of both membrane
and intracellular proteins.
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Leveraging this approach, white blood cells and especially lympho-
cytes are classified into subgroups quantitatively rather than qualita-
tively, thereby providing key insights in diagnosing various types of
leukemia.15–17
Because the fluorescent distributions of surface-coated cali-
bration microbeads deviate significantly from those of biological
cells with intracellular labeling, calibration microbeads are not com-
monly used to estimate ABC values quantitatively at the intracellular
level. Instead, Fig. 2(b) shows quantitative FCy based on constriction
microchannels in which a detection region with dimensions of ca.
2.5 μm×10 μm×10 μm is constructed by microfabrication. When
single cells with intracellular staining are forced to deform through
this optical field, stained fluorescent molecules occupy the detection
region evenly, with the corresponding fluorescent intensities cap-
tured. Fluorescent solutions flushed through this detection region
can function directly as the calibration material because of the detec-
tion volume being equivalent to the deformed cells, thus translating
fluorescent intensities of intracellularly stained single cells into ABC
values.
Quantitative FCy based on constriction microchannels was
used first to quantify the levels of single-cell intracellular proteins of
β-actins in tumor cell lines of Hep G2, A549, MCF 10A, and HeLa.18
Also, it has been used to quantify multiple-type intracellular proteins
of single cells including β-actin, α-tubulin, and β-tubulin (SACC-83,
CAL 27, A549, Hep G2, PC3), β-actin, biotin, and RhoA (HGE, CAL
27, WSU-HN6, MCF 7, MCF 10A), and Ras, c-Myc, and p53 (CAL
27, WSU-HN6, patient samples).19
For secreted cytokines, in droplet FCy, single cells are co-
encapsulated with microbeads to capture secreted proteins for
quantitative fluorescent detection. Based on this approach, vari-
ous secreted proteins at the single-cell level have been measured
quantitatively.20–22 However, within the droplet, there is an uneven
distribution of fluorescent intensities (e.g., bright microbeads),
leading to compromised accuracies of quantitative measurements.
To estimate quantitatively the expressions of single-cell pro-
teins distributed arbitrarily within biological cells, quantitative FCy
based on droplet microfluidics was developed recently [see Fig. 2(c)].
In this approach, single cells tagged by antibodies labeled with
fluorescent probes are firstly encapsulated within droplets; the anti-
bodies are stripped from the biological cells, and thus fluorescent
probes distributed evenly in the droplets. The individual droplets
then travel through and fully occupy the detection region of the
FCr, where the optical dimensions are confined by microfabri-
cated windows. Fluorescent solutions flushed through this detec-
tion region can function as the calibration material because of the
detection volume being equivalent to the droplets, thus translat-
ing fluorescent intensities of droplets into ABC values of single
cells.Quantitative FCy based on droplet microfluidics was used first
to quantify the expressions of one-type proteins, such as ConA of
A549, β-actin of A549, and HeLa.23 Furthermore, the same plat-
form was used to quantitatively estimate multiple-type proteins of
single cells, such as β-actin, α-tubulin, and β-tubulin of Hep G2
and CAL 27.24
B. Spectral flow cytometry
Unlike conventional clinical FCy, in which a single detector is
used to detect fluorescence emission in a narrow range for a single
fluorophore, in spectral FCy, the emission spectra of fluorescence
molecules bound with single cells are achieved with a set of detectors
across predefined wavelength ranges, and thus the fluorescent spec-
tra of different fluorescence molecules can be measured with spectral
signatures and used as references in multicolor FCy.
As pioneers of spectral FCy, in 2004, Robinson et al. reported
spectral FCy in which a grating was used to disperse light and a
photomultiplier tube (PMT) array was used for light detection [see
Fig. 3(a)].25,26 In 2011, Sony licensed the spectral technology patent
from the Robinson Group and pursued the commercial develop-
ment of a spectral FCr in which an array of prisms was used
to disperse light across the multi-anode PMT [see Fig. 3(b) and
Table II].27
Meanwhile, Nolan et al. reported a spectral FCr containing
spectroscopy-grade CCD-type detectors rather than multi-anode
PMTs; this provided higher quantum efficiencies and more detec-
tor elements in a high-density physical arrangement, which enabled
higher spectral resolutions [see Fig. 3(c)].28–31 To address the lim-
itation of relatively low readout speeds of CCDs in comparison to
PMTs, a spectral FCr with a CCD operating in the manner of time-
delayed integration for improved duty cycles and sensitivities was
recently reported [see Fig. 3(d)].32
Regarding the development of instruments for spectral FCy, the
first commercial one was released by Sony Biotechnology (SP6800)
in 2012: the key optical components were three lasers (405 nm,
488 nm, and 638 nm), 10 consecutive prisms, and a 32-channel
PMT; the corresponding key performance details were wavelengths
of 420–800 nm, an acquisition rate of 20 000 events per second,
and sensitivities of 120 MESF for FITC and 70 MESF for PE. The
newest Sony ID7000 analyzer is configured with up to seven lasers
and 186 detectors, enabling the characterization of 44 colors with
wavelengths of 360–920 nm (see Table II).
Other cutting-edge instruments include Cytek Northern Lights,
BD Symphony A5 SE, and Thermo Big Foot (see Table II). Specif-
ically, Cytek Northern Lights features arrays of avalanche pho-
todiodes based on coarse wavelength division multiplexing, and
other key parameters include an optical configuration of three
lasers, measurement wavelengths of 420–829 nm, and an acquisi-
tion rate of 35 000 events per second. BD Symphony A5 SE has
five lasers and 48 high-sensitivity GaAs PMTs, producing wave-
lengths of 365–880 nm, sensitivities of <80 MESF for FITC,
20 MESF for PE, and <70 MESF for APC, and an acquisition rate
of 40 000 events per second. Thermo Big Foot has up to nine
lasers and 60 PMTs, producing a sensitivity of <100 MESF for
FITC, PE, and APC and an acquisition rate of >100000 events per
second.
Regarding leveraging spectral FCy to address clinical
demands, a variety of lymphocyte immunophenotyping has been
reported.33–38 Specifically, in 2020, research groups affiliated with
Cytek Biosciences reported deep immunophenotyping of major
cell subsets for human peripheral blood based on 40-color spectral
FCy.33,39 In addition, the spectral FCy of Cytek was also used to
develop (i) a 43-color panel for characterizing conventional and
unconventional T cells, B cells, NK cells, monocytes, dendritic cells,
and innate lymphoid cells,34 (ii) a 21-marker 18-color panel for
deep phenotyping of human peripheral monocytes,37 and (iii) a
33-color panel for phenotyping of murine organ-specific immune
cells.38
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FIG. 3. Key technical developments in spectral FCy: (a) grating and photomultiplier tube (PMT) array;26 (b) prism array and PMT array;27 (c) grating and CCD;28 (d) CCD
with a time-delayed integration.32 Figures reprinted with permissions from (a) John Wiley and Sons, Copyright 2011; (b) John Wiley and Sons, Copyright 2015; (c) John
Wiley and Sons, Copyright 2006; (d) American Chemical Society, Copyright 2019.
C. Imaging flow cytometry
Unlike conventional FCy, whose results can only character-
ize the intensities of fluorescence signals without morphological
information, imaging FCy combining conventional FCy and imag-
ing capabilities provides quantitative images of every single cell,
thereby making the morphometric features of single cells available
for further studies.40,41
As the first commercially available imaging FCr, the
ImageStream system (Amnis USA) can obtain at most 12 images
per cell with spectral decomposition. A CCD camera combined
with time delay and integration is used to obtain images of the fast-
moving cells at low exposure times, thereby enabling a throughput
of 300 cells per second [see Fig. 4(a) and Table II].42–44
To improve the image capture rates, in 2020, Mikami et al.
reported a virtual-freezing fluorescence imaging FCr based on
optomechanical imaging to overcome the compromise among
throughput, sensitivity, and spatial resolution. A light-beam scan-
ner matching the entire field of view and a polygon scanner with
a special rotation angle synchronizing the timings of the image
sensor’s exposure and the excitation beam’s illumination and local-
ization were used to enable 1000 times longer exposure time, leading
to a higher throughput of more than 10 000 cells per second [see
Fig. 4(b)].45
To address fundamentally the issue of long exposure times of
cameras, an imaging method named time-stretch was reported, in
which PMTs are used to obtain the images of moving events that
are then used in imaging FCy.46 Specifically, in 2012, Goda et al.
reported an imaging FCr based on the time-stretch technique, in
which a PMT was used to image every event and then the spatial
spots were mapped to the different specific wavelengths of the broad-
band pulse laser; bright-field images of single cells were obtained at
a high throughput of 100 000 cells per second [see Fig. 4(c)].47
Although powerful, in time-stretch imaging, the mapping of
spatial spots to different specific wavelengths of the laser leads to
the wavelength information being lost during the digital reconstruc-
tion of images, and thus only bright-field images can be obtained.
Instead, the technique known as fluorescence imaging using radio-
frequency-tagged emissions was developed to achieve both bright-
field and fluorescence imaging with PMTs at an extremely high
speed.48 Specifically, in 2022, Schraivogel et al. developed an inte-
grated multicolor fluorescence imaging FCr in which the images
were captured by separated PMTs in different fluorescence channels:
the laser was separated into laser spots modulated at unique radio
frequencies to excite modulated fluorescent and scattered lights of
travelling events, and then the signal amplitudes were used to recon-
stitute 2D images in different channels; one bright-field image and
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© Author(s) 2022
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FIG. 4. Key technical developments in imaging FCy: (a) ImageStream with time delay and integration technique;44 (b) virtual-freezing fluorescence imaging FCy;45 (c) bright-
field imaging FCy based on time-stretch technique;47 (d) multicolor fluorescence imaging FCy using radio-frequency-tagged emission.49 Figures reprinted with permissions
from (a) Luminex Corporation; (b) Springer Nature, Copyright 2020; (c) Proceedings of the National Academy of Sciences, Copyright 2012; (d) The American Association
for the Advancement of Science, Copyright 2022.
four fluorescence images were captured at a throughput of 15 000
cells per second [see Fig. 4(d)].49
V. FUTURE DIRECTIONS
Regarding future directions, technical developments in clinical
FCy should be driven by clinical demands, which are divided here
into leukemia diagnosis and detection of MRD.
In leukemia diagnosis, quantitative rather than qualitative
gating is needed. Currently, with the help of calibration microbeads,
quantitative FCy can estimate the expressions of membrane
antigens, but quantitative numbers of cytoplasmic and nuclear
expressions of cell markers are still not available. Therefore, quan-
titative FCy capable of measuring both membrane and intracellular
biomarkers for single cells is demanded for leukemia
classification.
Regarding the detection of MRD, current clinical FCy suffers
from a key limitation of false negatives due to varied expressions of
antigens after treatments. With the contributions of spectral FCy,
the measurement resolutions can be increased dramatically, but the
detrimental issue of optical overlap remains. To a certain extent,
imaging FCy can address the issue of false negatives by collecting cell
images simultaneously, but current imaging FCy still cannot cap-
ture cell images with high magnification (e.g., ca. 100) for medical
examination because of the issue of losing focus. Therefore, imaging
FCy in which cell positions are fine-tuned for proper imaging is also
demanded.
ACKNOWLEDGMENTS
The authors acknowledge the financial support of the National
Natural Science Foundation of China (Grant Nos. 61922079,
61825107, and 62121003), the Chinese Academy of Sciences
(Grant Nos. GJJSTD20210004 and Y201927), and the National
Key Research and Development Program of China (Grant No.
2021YFC2500300).
AUTHOR DECLARATIONS
Conflict of Interest
The authors have no conflicts to disclose.
Author Contributions
T.Z. and M.G. contributed equally to this work as joint first authors.
DATA AVAILABILITY
Data sharing is not applicable to this article as no new data were
created or analyzed in this study.
Nano. Prec. Eng. 5, 045002 (2022); doi: 10.1063/10.0015301 5, 045002-7
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Ting Zhang received a B.S. degree in
Electronic Science and Technology from
North China Electric Power University,
Beijing, China in 2018. She is cur-
rently pursuing a Ph.D. degree with the
Aerospace Information Research Institute,
Chinese Academy of Sciences, Beijing,
China and with the University of Chinese
Academy of Sciences, Beijing, China. Her
research interests include microfluidics
and single-cell analysis.
Mengge Gao is currently pursuing an M.D.
degree with Peking University People’s
Hospital, Peking University Institute of
Hematology, National Clinical Research
Center for Hematologic Disease, Bei-
jing Key Laboratory of Hematopoietic
Stem Cell Transplantation, Beijing, China.
Her research interests include screening
and verification of new biological early-
warning markers for acute graft-versus-
host disease and molecular diagnosis of
hematological malignancies.
Xiao Chen received a B.S. degree in Mea-
surement and Control Technology and
Instruments from Tsinghua University,
Beijing, China in 2020. He is currently pur-
suing a Ph.D. degree with the Aerospace
Information Research Institute, Chinese
Academy of Sciences, Beijing, China and
with the University of Chinese Academy
of Sciences, Beijing, China. His research
interests include microfluidics and single-
cell analysis.
Chiyuan Gao received a B.S. degree in
Measurement and Control Technology
and Instruments from Tsinghua Univer-
sity, Beijing, China in 2020. He is cur-
rently pursuing a Ph.D. degree with the
Aerospace Information Research Institute,
Chinese Academy of Sciences, Beijing,
China and with the University of Chinese
Academy of Sciences, Beijing, China. His
research interests include microfluidics
and single-cell analysis.
Shilun Feng received a B.S. degree (China)
in Pharmaceutics in 2013, an M.S. degree
(Norway) in Bio-MEMS in 2015, and a
Ph.D. degree from Macquarie University,
Australia in 2018. He is currently an Asso-
ciate Professor in the State Key Labora-
tory of Transducer Technology, Shang-
hai Institute of Microsystem and Infor-
mation Technology, Chinese Academy of
Sciences, Shanghai, China. His research
interests include biomedical microfluidics,
microfabrication, on-chip imaging, 3D
printing, POCT, and wearable devices.
Nano. Prec. Eng. 5, 045002 (2022); doi: 10.1063/10.0015301 5, 045002-9
© Author(s) 2022
Nanotechnology and
Precision Engineering REVIEW scitation.org/journal/npe
Deyong Chen received a B.S. degree from
Tsinghua University, Beijing, China in
1989, an M.S. degree from the Institute of
Semiconductors, Chinese Academy of Sci-
ences, Beijing, China in 1992, and a Ph.D.
degree from the Institute of Electron-
ics, Chinese Academy of Sciences, Beijing,
China in 2002. He is currently a Full
Professor at the Aerospace Information
Research Institute, Chinese Academy of
Sciences, Beijing, China. His research
interests include microelectromechanical
systems and micro sensors.
Junbo Wang received B.S. and M.S.
degrees in Material Sciences from Jilin
University of Technology, Jilin, China
in 1995 and 1998 and a Ph.D. degree
in Material Processing Engineering from
Tsinghua University, Beijing, China in
2002. He is currently a Full Professor
and the Director of the State Key Labora-
tory of Transducer Technology, Aerospace
Information Research Institute, Chinese
Academy of Sciences, Beijing, China.
His research interests include microelec-
tromechanical systems, micro sensors, and
microfluidics.
Xiaosu Zhao received an M.S. degree in
Clinical Medicine from Peking University,
Beijing, China in 2003, a Ph.D. degree
from Hong Kong University in 2006, and
an M.D. degree from Peking University
in 2009. She is currently a Professor at
the Peking University People’s Hospital,
Peking University Institute of Hematol-
ogy, National Clinical Research Center for
Hematologic Disease, Beijing Key Labora-
tory of Hematopoietic Stem Cell Trans-
plantation, Beijing, China. Her research
interests include basic research into the
diagnosis and treatment of comorbidities
after hematopoietic stem cell transplanta-
tion and molecular diagnosis of malignant
hematological diseases.
Jian Chen received a Ph.D. degree in
Biomedical Engineering from the Univer-
sity of Toronto, ON, Canada in 2011.
He is currently a Professor at the State
Key Laboratory of Transducer Tech-
nology, Aerospace Information Research
Institute, Chinese Academy of Sciences,
Beijing, China. His research interests
include microfluidics, single-cell analysis,
and local micro environment rebuilding.
Nano. Prec. Eng. 5, 045002 (2022); doi: 10.1063/10.0015301 5, 045002-10
© Author(s) 2022
