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Related Concept Videos

Flow Cytometry01:23

Flow Cytometry

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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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Flow Cytometry to Estimate Leukemia Stem Cells in Primary Acute Myeloid Leukemia and in Patient-derived-xenografts, at Diagnosis and Follow Up
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The routine leukocyte differential flow cytometry HematoFlow™ method: A new flagging system for automatic validation.

Kaoutar Allou1, Jean-Philippe Vial1, Marie C Béné2

  • 1University Hospital of Bordeaux, Haut Lévêque Hospital, Pessac, France.

Cytometry. Part B, Clinical Cytometry
|April 25, 2015
PubMed
Summary

The HematoFlow™ system, a novel flow cytometry method, enables automated validation of over 50% of complete blood cell counts and white blood cell differentials. This reduces technician workload and improves accuracy in diagnosing hematological diseases.

Keywords:
flow cytometryhematologyimmunophenotypingmultiparameter analysisperipheral blood

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Characterization of Human Monocyte Subsets by Whole Blood Flow Cytometry Analysis
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Area of Science:

  • Hematology
  • Flow Cytometry
  • Clinical Diagnostics

Background:

  • Complete blood cell counts and white blood cell differentials are crucial for diagnosing hematological diseases.
  • Current automated methods require manual review for flagged results, impacting efficiency.
  • Microscopic blood smear review, the reference method, has limitations in sensitivity and reproducibility.

Purpose of the Study:

  • To evaluate the HematoFlow™ system, a flow cytometry method, for routine differential analysis.
  • To develop and validate a novel flag system for automated differential validation.
  • To assess the impact of the HematoFlow™ system on laboratory workload and diagnostic accuracy.

Main Methods:

  • Utilized a retrospective analysis of 6,462 blood samples and a prospective study of 15,335 cases.
  • Employed a flow cytometry system with six markers in five colors and an automated gating strategy.
  • Developed an original flag system based on bivariate histograms to detect immature granulocytes, blast cells, and aberrant cell localizations.

Main Results:

  • The HematoFlow™ system reliably detected 17 leukocyte subpopulations.
  • Over 50% of results were automatically validated in both retrospective and prospective studies, with no false negatives.
  • The new flag system improved automated validation rates and aided in smear review interpretation and disease confirmation.

Conclusions:

  • The HematoFlow™ system and its associated flag system significantly reduce technician workload by enabling high rates of automated differential validation.
  • This flow cytometry approach enhances diagnostic accuracy and efficiency in routine hematological analysis.
  • The implementation of this technology is essential for advancing routine differential analysis and improving laboratory workflow.