Intelligent whole-blood imaging flow cytometry for simple, rapid, and cost-effective drug-susceptibility testing of leukemia

Kobayashi, Hirofumi; Lei, Cheng; Wu, Yi; Huang, Chun-Jung; Yasumoto, Atsushi; Jona, Masahiro; Li, Wenxuan; Wu, Yunzhao; Yalikun, Yaxiaer; Jiang, Yiyue; Guo, Baoping; Sun, Chia‐Wei; Tanaka, Yo; Yamada, Makoto; Yatomi, Yutaka; Goda, Keisuke

doi:10.1039/c8lc01370e

Cited by 56 publications

(43 citation statements)

References 41 publications

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“…Currently, the world's fastest imaging flow cytometry is realised by microfluidics-based optofluidic time-stretch (OTS) microscopy [21][22][23], which achieves continuous image acquisition at an ultrahigh rate of 10 million to 1 billion fps. Even though the theoretical limit of OTS microscopy allows a maximum flow velocity of 60 m/s [23,24], images were captured at a flow velocity of about 10 m/s [9,25] due to the limitation of presently available microfluidic technology. By employing a horizontal connection, it contributes to reduced pressure drop to increase flow velocity and further utilise the potential of imaging flow cytometry.…”

Section: Resultsmentioning

confidence: 99%

Horizontal connection method for glass microfluidic devices

Yalikun

Ota

et al. 2020

Micro & Nano Letters

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In a conventional glass microfluidic system, the vertical connection is the most frequently used for connections between a microfluidic device and its peripheral equipment. However, it leads to a significant pressure drop at the inlet of a microfluidic device, decreases the flow velocity, and can introduce few samples than expected. To overcome these problems, a horizontal connection method for glass microfluidic devices, which have advantages such as keeping pressure/flow velocity, compatible with small space, reduced sample loss and convenience for modularisation is reported. These advantages are important for high-speed analysis on precious samples such as single-cell flow cytometry. In this work, they proposed a horizontal connection method which showed compatibility with high pressure (at least 0.6 MPa) at inlet without leakage, small loss of injected samples (<0.11%), and 22% faster flow velocity along the direction of applied pressure than that of vertical connection.

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Section: Resultsmentioning

confidence: 99%

Horizontal connection method for glass microfluidic devices

Yalikun

Ota

et al. 2020

Micro & Nano Letters

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“…To demonstrate image capturing by OTS microscopy, K562, a human chronic myelogenous leukemia cell line was used. K562 cells were purchased from the Japanese Collection of Research Bioresources Cell Bank (JCRB).…”

Section: Methodsmentioning

confidence: 99%

“…A previous study reported a maximum throughput of 1 million cells/s at a flow velocity of 10 m/s using a glass‐PDMS‐glass hybrid microfluidic device. In order to demonstrate the capability of our developed OTS microscopy, it is important to show that the images obtained at an ultra‐high‐flow velocity have the same quality as those obtained at a lower flow velocity.…”

Section: Methodsmentioning

confidence: 99%

“…Currently, the world's fastest imaging flow cytometry is realized by microfluidics‐based OTS microscopy , which achieves continuous image acquisition at an ultra‐high rate of 10 million to 1 billion frames per second. Meanwhile, image capturing at a flow velocity of about 10 m/s is presently available , even though the theoretical limit of OTS microscopy allows a maximum flow velocity of 60 m/s .…”

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Effects of Flow‐Induced Microfluidic Chip Wall Deformation on Imaging Flow Cytometry

et al. 2019

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Imaging flow cytometry is a powerful tool by virtue of its capability for high‐throughput cell analysis. The advent of high‐speed optical imaging methods on a microfluidic platform has significantly improved cell throughput and brought many degrees of freedom to instrumentation and applications over the last decade, but it also poses a predicament on microfluidic chips. Specifically, as the throughput increases, the flow speed also increases (currently reaching 10 m/s): consequently, the increased hydrodynamic pressure on the microfluidic chip deforms the wall of the microchannel and produces detrimental effects lead to defocused and blur image. Here, we present a comprehensive study of the effects of flow‐induced microfluidic chip wall deformation on imaging flow cytometry. We fabricated three types of microfluidic chips with the same geometry and different degrees of stiffness made of polydimethylsiloxane (PDMS) and glass to investigate material influence on image quality. First, we found the maximum deformation of a PDMS microchannel was >60 μm at a pressure of 0.6 MPa, while no appreciable deformation was identified in a glass microchannel at the same pressure. Second, we found the deviation of lag time that indicating velocity difference of migrating microbeads due to the deformation of the microchannel was 29.3 ms in a PDMS microchannel and 14.9 ms in a glass microchannel. Third, the glass microchannel focused cells into a slightly narrower stream in the X‐Y plane and a significantly narrower stream in the Z‐axis direction (focusing percentages were increased 30%, 32%, and 5.7% in the glass channel at flow velocities of 0.5, 1.5, and 3 m/s, respectively), and the glass microchannel showed stabler equilibrium positions of focused cells regardless of flow velocity. Finally, we achieved the world's fastest imaging flow cytometry by combining a glass microfluidic device with an optofluidic time‐stretch microscopy imaging technique at a flow velocity of 25 m/s. © 2019 International Society for Advancement of Cytometry

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“…One of the most promising approaches is to employ machine learning and artificial intelligence to metabolize these unprecedent amount of data. Although traditional machine learning offers advanced data processing capabilities, the advent of its most important component, the deep learning, made possible to analyze massive unstructured data such as images, drug-target interactions and computational biology [16][17][18][19]. These AI-based techniques employ algorithms that learn without direct programming overcoming the limitation of human recognition boosting human knowledge in various fields.…”

Section: Introductionmentioning

confidence: 99%

The Synergy between Organ-on-a-Chip and Artificial Intelligence for the Study of NAFLD: From Basic Science to Clinical Research

2021

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Non-alcoholic fatty liver affects about 25% of global adult population. On the long-term, it is associated with extra-hepatic compliances, multiorgan failure, and death. Various invasive and non-invasive methods are employed for its diagnosis such as liver biopsies, CT scan, MRI, and numerous scoring systems. However, the lack of accuracy and reproducibility represents one of the biggest limitations of evaluating the effectiveness of drug candidates in clinical trials. Organ-on-chips (OOC) are emerging as a cost-effective tool to reproduce in vitro the main NAFLD’s pathogenic features for drug screening purposes. Those platforms have reached a high degree of complexity that generate an unprecedented amount of both structured and unstructured data that outpaced our capacity to analyze the results. The addition of artificial intelligence (AI) layer for data analysis and interpretation enables those platforms to reach their full potential. Furthermore, the use of them do not require any ethic and legal regulation. In this review, we discuss the synergy between OOC and AI as one of the most promising ways to unveil potential therapeutic targets as well as the complex mechanism(s) underlying NAFLD.

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Intelligent whole-blood imaging flow cytometry for simple, rapid, and cost-effective drug-susceptibility testing of leukemia

Abstract: The drug susceptibility of leukemia cells in whole blood is evaluated by using extreme-throughput imaging flow cytometry with deep learning.

Cited by 56 publications

References 41 publications

Horizontal connection method for glass microfluidic devices

Horizontal connection method for glass microfluidic devices

Effects of Flow‐Induced Microfluidic Chip Wall Deformation on Imaging Flow Cytometry

The Synergy between Organ-on-a-Chip and Artificial Intelligence for the Study of NAFLD: From Basic Science to Clinical Research

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