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Chapter 14 - Future Applications of Flow Cytometry and Related Techniques

Published online by Cambridge University Press:  30 January 2025

By
Marie-Christine Béné ,
Anna Porwit  and
Francis Lacombe
Edited by
Anna Porwit  and
Marie Christine Béné
Anna Porwit
Affiliation:
Lunds Universitet, Sweden
Marie Christine Béné
Affiliation:
Université de Nantes, France
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Summary

Although the fundamental idea of having cells focalised to be ’seen’ one by one by a detection system remains unchanged, flow cytometry technologies evolve. This chapter provides an overview of recent progress in this evolution. From a technical point of view, cameras can provide images of each of these cells together with their fluorescent properties, or the whole spectrum of emitted light can be collected. Markers coupled to heavy metals allow to detect each cell immunophenotype by mass spectrometry. On the analysis side, artificial intelligence and machine learning are developing for unsupervised analysis, saving time before a much better supervision of small populations.

Keywords

flow cytometryimmunophenotypingimagingcyTOFspectral flowdata representationdimension reductionclusteringartificial intelligencemeasureable/minimal residual disease in AML
Type
Chapter
Information
Multiparameter Flow Cytometry in the Diagnosis of Hematologic Malignancies , pp. 219 - 232
Publisher: Cambridge University Press
Print publication year: 2025

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