title: Computer-assisted differential diagnosis of malignant mesothelioma based on syntactic structure analysis.
abstract: BACKGROUND
  Malignant mesothelioma, a mesoderm-derived tumor, is related to asbestos exposure and remains a diagnostic challenge because none of the genetic or immunohistochemical markers have yet been proven to be specific. To assist in the identification of mesothelioma and to differentiate it from other common lesions at the same location, we have tested the performance of syntactic structure analysis (SSA) in an automated classification procedure.
  
  
  METHODS
  Light-microscopic images of tissue sections of malignant mesothelioma, hyperplastic mesothelium, and adenocarcinoma were analyzed using parameters selected from the Voronoi diagram, Gabriel's graph, and the minimum spanning tree which were classified with a K-nearest-neighbor algorithm.
  
  
  RESULTS
  Results showed that mesotheliomas were diagnosed correctly in 74% of the cases; 76% of the adenocarcinomas were correctly graded, and 88% of the mesotheliomas were correctly typed. The performance of the parameters was dependent on the obtained classification (i.e., tumor-tumor versus tumor-benign).
  
  
  CONCLUSIONS
  Our results suggest that SSA is valuable in the differential classification of mesothelioma and that it supplements a visually appraised diagnosis. The recognition scores may be increased by a combination of SSA with, for example, cellular or nuclear parameters, measured at higher magnifications to form a solid base for fully automated expert systems.
authors.affiliation: Center for Electron Microscopy, University of Antwerp, Wilrijk, Belgium. bweyn@uia.ua.ac.be
authors.forename: B
authors.initials: B
authors.lastname: Weyn
authors.forename: G
authors.initials: G
authors.lastname: van de Wouwer
authors.forename: S
authors.initials: S
authors.lastname: Kumar-Singh
authors.forename: A
authors.initials: A
authors.lastname: van Daele
authors.forename: P
authors.initials: P
authors.lastname: Scheunders
authors.forename: E
authors.initials: E
authors.lastname: van Marck
authors.forename: W
authors.initials: W
authors.lastname: Jacob
mesh_terms: D000230:Adenocarcinoma / Q000145:classification / Q000473:pathology*; D000704:Analysis of Variance; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D003937:Diagnosis, Differential; D004848:Epithelium / Q000473:pathology; D017709:Fractals; D006801:Humans; D006965:Hyperplasia / Q000145:classification / Q000473:pathology; D007091:Image Processing, Computer-Assisted; D008175:Lung Neoplasms / Q000145:classification / Q000473:pathology*; D008654:Mesothelioma / Q000145:classification / Q000473:pathology*; D015999:Multivariate Analysis