Stratum corneum nanotexture feature detection using deep learning and spatial analysis: a noninvasive tool for skin barrier assessment.

Journal: GigaScience
PMID: 39657103

Abstract

BACKGROUND: Corneocyte surface nanoscale topography (nanotexture) has recently emerged as a potential biomarker for inflammatory skin diseases, such as atopic dermatitis (AD). This assessment method involves quantifying circular nano-size objects (CNOs) in corneocyte nanotexture images, enabling noninvasive analysis via stratum corneum (SC) tape stripping. Current approaches for identifying CNOs rely on computer vision techniques with specific geometric criteria, resulting in inaccuracies due to the susceptibility of nano-imaging techniques to environmental noise and structural occlusion on the corneocyte.

Authors

  • Jen-Hung Wang
    Department of Medical Research, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien, Taiwan.
  • Jorge Pereda
    Department of Health Technology, Technical University of Denmark, Kongens Lyngby 2800, Denmark.
  • Ching-Wen Du
    Department of Health Technology, Technical University of Denmark, Kongens Lyngby 2800, Denmark.
  • Chia-Yu Chu
    Department of Dermatology, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei 100225, Taiwan.
  • Maria Oberländer Christensen
    Department of Dermatology, Bispebjerg and Frederiksberg Hospital (BFH), University Hospitals of Copenhagen, Copenhagen 2400, Denmark.
  • Sanja Kezic
    Department of Public and Occupational Health, Amsterdam Public Health Research Institute, Amsterdam University Medical Center, Amsterdam 1105, The Netherlands.
  • Ivone Jakasa
    Laboratory for Analytical Chemistry, Department of Chemistry and Biochemistry, Faculty of Food Technology and Biotechnology, University of Zagreb, Zagreb 10000, Croatia.
  • Jacob P Thyssen
    Department of Dermatology, Bispebjerg Hospital, University of Copenhagen, Copenhagen, Denmark.
  • Sreeja Satheesh
    Institute of Solid State Physics, Leibniz University Hannover, Hannover 30167, Germany.
  • Edwin En-Te Hwu
    Department of Health Technology, Technical University of Denmark, Kongens Lyngby 2800, Denmark.

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