Evaluation of minor labial salivary gland focus score in Sjögren's disease using deep learning: a tool for more efficient diagnosis and future tissue biomarker discovery.

Journal: Journal of autoimmunity
PMID: 40262321

Abstract

BACKGROUND: Sjögren's Disease (SjD) is histopathologically characterized by focal sialadenitis in minor labial salivary gland biopsies (mLSGB), which is evaluated by utilizing the focus score (FS). Focus score ≥1 identification is a critical step of the diagnostic approach and SjD classification. Nonetheless, during mLSGB analysis, FS reporting is neglected in a staggering 17 %, and a degree of inter-observer variability is introduced, even among specialized university centers. As the unmet need for reliable FS reporting is displayed, leveraging artificial intelligence in mLSGB evaluation shows encouraging potential and mandates to be investigated.

Authors

  • Konstantinos N Panagiotopoulos
    Department of Pathophysiology and Joint Rheumatology, Medical School, National and Kapodistrian University of Athens, Greece.
  • Nikos Tsiknakis
    Computational BioMedicine Laboratory, Foundation for Research and Technology Hellas, Greece; Department of Oncology, Pathology, Karolinska Institute, Sweden.
  • Dimitrios I Zaridis
    Biomedical Research Institute, Foundation for Research and Technology Hellas, Greece; Biomedical Engineering Laboratory, School of Electrical & Computer Engineering, National Technical University of Athens, Greece; Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, University of Ioannina, Greece.
  • Clio P Mavragani
    Department of Physiology, Medical School, National and Kapodistrian University of Athens, Greece.
  • Athanasios G Tzioufas
    Department of Pathophysiology and Joint Rheumatology, Medical School, National and Kapodistrian University of Athens, Greece; Biomedical Research Foundation of the Academy of Athens, Greece; Research Institute for Systemic Autoimmune Diseases, Greece.
  • Dimitrios I Fotiadis
    Biomedical Research Institute, Foundation for Research and Technology Hellas, Greece; Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, University of Ioannina, Greece.
  • Andreas V Goules
    Department of Pathophysiology and Joint Rheumatology, Medical School, National and Kapodistrian University of Athens, Greece; Research Institute for Systemic Autoimmune Diseases, Greece. Electronic address: agoules@med.uoa.gr.

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