Validation of digital microscopy in the histopathological diagnoses of oral diseases

Virchows Arch. 2018 Sep;473(3):321-327. doi: 10.1007/s00428-018-2382-5. Epub 2018 Jun 1.

Abstract

Whole slide imaging (WSI) systems are being increasingly used in educational and professional settings, highlighting the value of digital microscopy and favouring its acceptance for use in primary diagnosis. There has been a reluctance to introduce diagnostic applications due to a lack of validation and regulation of these devices. This study aims to provide information regarding the performance of WSI and to validate it for use in the diagnosis of oral diseases, using the intraobserver variability as the primary form of analysis. Seventy (n = 70) H&E-stained glass slides of oral biopsies were scanned using the Aperio Digital Pathology System at a magnification of × 20. Two experienced oral pathologists blindly analysed all H&E-stained sections with a conventional light microscope (CLM) and, after 3-month washout, with WSI. Clinical information was provided along with the cases in both analyses. The intraobserver agreement between CLM and WSI was 97% (κ = 0.9) for both pathologists. The majority of preferred diagnoses were by CLM. Both pathologists had the same discordances in different cases. Challenging cases and cases with insufficient quantity of tissue for analyses were considered the main reasons for disagreement rather than the diagnostic methods. Median time taken to make a diagnosis was higher only in CLM for one pathologist. Time outliers occurred in discordant cases and in other difficult cases. This study provides evidence of a high performance of WSI for diagnostic purposes in clinical practice, routine pathology and primary diagnosis in the field of oral pathology.

Keywords: Digital pathology; Intraobserver agreement; Validation; Whole slide imaging.

Publication types

  • Validation Study

MeSH terms

  • Cross-Sectional Studies
  • Humans
  • Microscopy / methods*
  • Mouth Diseases / diagnostic imaging*
  • Mouth Diseases / pathology
  • Observer Variation
  • Retrospective Studies