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Flow Cytometry

Flow Cytometry

The development of flow cytometry techniques began in 1934 with initial attempts by Andrew Moldavan, a bacteriologist who counted the cells in a flowing capillary system. Moldavan pumped cells through a capillary tube focused under a microscope for visualization. The invention of photometry allowed the measurement of differentially-stained cells, and Louis Kamentsky developed the first multiparameter flow cytometer in 1965 to identify and count the cancer cells in cervical tissue specimens.
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Discrimination of Seven Immune Cell Subsets by Two-fluorochrome Flow Cytometry

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Refining the white blood cell differential: the first flow cytometry routine application.

Mikael Roussel¹, Cyrille Benard, Beatrice Ly-Sunnaram

¹Hematology laboratory, University Hospital Pontchaillou, Rennes, France.

Cytometry. Part a : the Journal of the International Society for Analytical Cytology

|May 28, 2010

Summary

Automated white blood cell (WBC) differential analysis using flow cytometry streamlines laboratory workflows. This method offers comparable diagnostic quality and turnaround times to manual slide reviews, reducing the need for expert personnel.

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Characterization of Human Monocyte Subsets by Whole Blood Flow Cytometry Analysis

Characterization of Human Monocyte Subsets by Whole Blood Flow Cytometry Analysis

Published on: October 17, 2018

Area of Science:

Hematology
Clinical Pathology
Immunophenotyping

Background:

Automated Complete Blood Count analysis often requires manual microscopic review for white blood cell (WBC) differentials.
This manual review is time-consuming and necessitates experienced laboratory personnel.
Flow cytometry with monoclonal antibodies offers a potential automated solution for extended WBC differentials.

Purpose of the Study:

To evaluate the integration and efficiency of a flow cytometry-based workflow for WBC differential analysis in a routine hematology laboratory setting.
To compare the diagnostic quality, turnaround time, and labor requirements of flow cytometry versus traditional manual slide review.
To assess the performance of automated data management software in validating flow cytometric results.

Main Methods:

A workflow combining robotic sample preparation, antibody labeling, flow cytometry, and data management software was implemented.
This automated workflow was compared against the standard manual microscopic review of blood films.
Analytic thresholds were determined and validated on 1,973 patient samples.

Main Results:

The flow cytometry data management software automatically validated 52% of samples with high accuracy.
An additional 33% of samples were validated by an operator, while only 15% required manual microscopic review.
The overall turnaround time was comparable to the traditional manual review process.

Conclusions:

Flow cytometry, when integrated into a WBC differential workflow, significantly enhances efficiency in routine hematology laboratories.
This automated approach reduces the reliance on manual slide reviews and expert personnel.
The study demonstrates the practical utility and diagnostic capability of flow cytometry for routine WBC differential analysis.