title: Automated virtual microscopy of gastric biopsies.
abstract: BACKGROUND
  Automated virtual microscopy of specimens from gastrointestinal biopsies is based on cytometric parameters of digitized histological sections. To our knowledge, cytometric parameters of gastritis and of adenocarcinoma have yet to be fully characterized. Our objective was to classify gastritis and adenocarcinoma based on cytometric parameters. We hypothesized that automated virtual microscopy using this novel classification can reliably diagnose gastritis and adenocarcinoma.
  
  
  METHODS
  Routinely processed hematoxylin-and-eosin-stained histological sections from specimens that showed normal mucosa (14 cases), gastritis (35 cases), and adenocarcinoma (30 cases) diagnosed by conventional optical microscopy were scanned and digitized at high resolution. Thirty-eight cytometric parameters based on density and morphometry were applied to glands and superficial epithelium. Twelve cytometric parameters based on cytologic detail were applied to individual cells.
  
  
  RESULTS
  Statistically significant differences in cytometric parameters for normal mucosa, gastritis, and adenocarcinoma were found. The most discriminatory parameter was the ratio of the total number of cells to the number of interstitial cells. These differences correctly classified adenocarcinoma at 100% accuracy and overall correctness was 86%.
  
  
  CONCLUSIONS
  We describe a novel method of analyzing gastric mucosal histology based on cytometric parameters. Automated virtual microscopy can be used to classify gastric mucosa as normal, gastritis, or adenocarcinoma with reasonable accuracy. Further research is necessary to determine whether automated virtual microscopy can subclassify gastric mucosal histology in greater detail.
authors.affiliation: 2nd Department of Internal Medicine, Semmelweis University, Budapest, Hungary.
authors.forename: Levente
authors.initials: L
authors.lastname: Ficsor
authors.forename: Viktor
authors.initials: V
authors.lastname: Varga
authors.forename: Lajos
authors.initials: L
authors.lastname: Berczi
authors.forename: Pal
authors.initials: P
authors.lastname: Miheller
authors.forename: Attila
authors.initials: A
authors.lastname: Tagscherer
authors.forename: Mark Li-cheng
authors.initials: ML
authors.lastname: Wu
authors.forename: Zsolt
authors.initials: Z
authors.lastname: Tulassay
authors.forename: Bela
authors.initials: B
authors.lastname: Molnar
mesh_terms: D000230:Adenocarcinoma / Q000145:classification / Q000175:diagnosis* / Q000473:pathology; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001706:Biopsy; D003937:Diagnosis, Differential; D005260:Female; D005753:Gastric Mucosa / Q000648:ultrastructure*; D005756:Gastritis / Q000145:classification / Q000175:diagnosis* / Q000473:pathology; D006801:Humans; D019044:Image Cytometry / Q000379:methods*; D008297:Male; D008853:Microscopy / Q000379:methods*; D008875:Middle Aged; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D013274:Stomach Neoplasms / Q000145:classification / Q000175:diagnosis* / Q000473:pathology; D014584:User-Computer Interface