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memo - Magazine of European Medical Oncology

, Volume 7, Issue 4, pp 219–226 | Cite as

Towards automation of flow cytometric analysis for quality-assured follow-up assessment to guide curative therapy for acute lymphoblastic leukaemia in children

  • Michael Reiter
  • Jana Hoffmann
  • Florian Kleber
  • Angela Schumich
  • Gerald Peter
  • Florian Kromp
  • Martin Kampel
  • Michael Dworzak
special report
  • 117 Downloads

Abstract

Minimal residual disease (MRD) is of high prognostic value in risk stratification in childhood acute lymphoblastic leukaemia. Flow cytometry (FCM) was shown to yield reliable results in MRD measurement. However, the interpretation of FCM data relies largely on operator skills and experience. While sample preparation, antibody panels, staining procedures and flow cytometric acquisition can be standardized, easily controlled and be made available worldwide, the availability of experienced operators represents the current bottleneck to a growing number of laboratories to the benefit of an increasing number of patients with leukaemia. Currently, international paediatric studies—throughout Europe, South America, to Australia—aim at stratifying the treatment according to the FCM-MRD methodology. The measurements are still operator-dependent leading to substantial costs regarding training and quality control. This article introduces a new European Union-funded project (AutoFLOW) aiming at the standardization and automation of FCM-MRD analysis by machine-learning technology.

Keywords

Acute lymphoblastic leukaemia Flow cytometry Minimal residual disease Gaussian mixture model Kernel density estimation 

Notes

Acknowledgements

The AutoFLOW project is funded by Marie Curie Industry Academia Partnerships & Pathways (FP7-Marie Curie–PEOPLE-2013-IAPP) under the grant no. 610872. The authors would like to thank Nuno Andrade and Melanie Gau for their valuable contributions to the pro­ject. Furthermore, the authors would like to thank the R community.

Conflict of interest

Michael Reiter, Jana Hoffmann, Florian Kleber, Angela Schumich, Gerald Peter, Florian Kromp, Martin Kampel and Michael Dworzak declare that there is no conflict of interest.

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Copyright information

© Springer-Verlag Wien 2014

Authors and Affiliations

  • Michael Reiter
    • 1
    • 2
  • Jana Hoffmann
    • 2
    • 3
  • Florian Kleber
    • 1
    • 2
  • Angela Schumich
    • 2
    • 4
  • Gerald Peter
    • 4
  • Florian Kromp
    • 2
    • 4
  • Martin Kampel
    • 1
  • Michael Dworzak
    • 2
    • 4
  1. 1.Institute of Computer Aided AutomationVienna University of TechnologyViennaAustria
  2. 2.Labdia LabordiagnostikViennaAustria
  3. 3.Department of Pediatric Oncology/HematologyCharité—University Medical CenterBerlinGermany
  4. 4.Department of Pediatrics, St. Anna Children’s Hospital and Children’s Cancer Research InstituteMedical University of ViennaViennaAustria

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