Deep learning identifies Acute Promyelocytic Leukemia in bone marrow smears.

Journal: BMC cancer
PMID: 35193533

Abstract

BACKGROUND: Acute promyelocytic leukemia (APL) is considered a hematologic emergency due to high risk of bleeding and fatal hemorrhages being a major cause of death. Despite lower death rates reported from clinical trials, patient registry data suggest an early death rate of 20%, especially for elderly and frail patients. Therefore, reliable diagnosis is required as treatment with differentiation-inducing agents leads to cure in the majority of patients. However, diagnosis commonly relies on cytomorphology and genetic confirmation of the pathognomonic t(15;17). Yet, the latter is more time consuming and in some regions unavailable.

Authors

  • Jan-Niklas Eckardt
    Department of Internal Medicine I, University Hospital Carl Gustav Carus, Dresden, Germany. jan-niklas.eckardt@uniklinikum-dresden.de.
  • Tim Schmittmann
    Institute of Circuits and Systems, Technical University Dresden, Dresden, Germany.
  • Sebastian Riechert
    Institute of Circuits and Systems, Technical University Dresden, Dresden, Germany.
  • Michael Kramer
    Department of Internal Medicine I, University Hospital Carl Gustav Carus, Dresden, Germany.
  • Anas Shekh Sulaiman
    Department of Internal Medicine I, University Hospital Carl Gustav Carus, Dresden, Germany.
  • Katja Sockel
    Department of Internal Medicine I, University Hospital Carl Gustav Carus, Dresden, Germany.
  • Frank Kroschinsky
    Department of Internal Medicine I, University Hospital Carl Gustav Carus, Dresden, Germany.
  • Johannes Schetelig
    Department of Internal Medicine I, University Hospital Carl Gustav Carus, Dresden, Germany.
  • Lisa Wagenführ
    Department of Internal Medicine I, University Hospital Carl Gustav Carus, 01307, Dresden, Saxony, Germany.
  • Ulrich Schuler
    Department of Internal Medicine I, University Hospital Carl Gustav Carus, Dresden, Germany.
  • Uwe Platzbecker
    Medical Clinic and Polyclinic I, University Hospital, Technical University Dresden, Dresden, Germany.
  • Christian Thiede
    Department of Internal Medicine I, University Hospital Carl Gustav Carus, Dresden, Germany.
  • Friedrich Stölzel
    Department of Internal Medicine I, University Hospital Carl Gustav Carus, 01307, Dresden, Saxony, Germany.
  • Christoph Röllig
    Department of Internal Medicine I, University Hospital Carl Gustav Carus, Dresden, Germany.
  • Martin Bornhäuser
    Department of Internal Medicine I, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.
  • Karsten Wendt
    Institute of Circuits and Systems, Technical University Dresden, Dresden, Germany.
  • Jan Moritz Middeke
    Department of Internal Medicine I, University Hospital Carl Gustav Carus, Dresden, Germany.

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