Deep Learning Neural Network-Guided Detection of Asbestos Bodies in Bronchoalveolar Lavage Samples.

Journal: Acta cytologica
PMID: 37725908

Abstract

INTRODUCTION: Asbestos is a global occupational health hazard, and exposure to it by inhalation predisposes to interstitial as well as malignant pulmonary morbidity. Over time, asbestos fibers embedded in lung tissue can become coated with iron-rich proteins and mucopolysaccharides, after which they are called asbestos bodies (ABs) and can be detected in light microscopy (LM). Bronchoalveolar lavage, a cytological sample from the lower airways, is one of the methods for diagnosing lung asbestosis and related morbidity. Search for ABs in these samples is generally laborious and time-consuming. We describe a novel diagnostic method, which implements deep learning neural network technology for the detection of ABs in bronchoalveolar lavage samples (BALs).

Authors

  • Antti J Hakkarainen
    Forensic Medicine, University of Helsinki, Helsinki, Finland.
  • Reija Randen-Brady
    Pathology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
  • Henrik Wolff
    Pathology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
  • Mikko I Mäyränpää
    Pathology, University of Helsinki and Helsinki University Hospital, FI-00290, Helsinki, Finland.
  • Antti Sajantila
    Forensic Medicine, University of Helsinki, Helsinki, Finland.

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