Integrated decision support system/image archive for histological typing of breast cancer using a relation oriented inference system

P J Van Diest, J A Beliën, P E Zanstra, W W Wilhelm, J P Baak

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5 Citations (Scopus)

Abstract

Histological typing of invasive breast cancer according to the World Health Organisation criteria is prognostically relevant, because some histological subtypes have a markedly better prognosis. However, reproducibility of histological typing is not high because of the absence of strict typing criteria, variations in the application of the typing criteria and the usually limited illustration of the relevant criteria. The aim of this study was to develop an expert system based on highly structured histological typing criteria, integrated with high-quality microscope images to illustrate the typing criteria. This system should be useful as a decision support system in the diagnosis of breast cancers and should increase the reproducibility of histological typing. Criteria for typing were extracted from textbooks and, based on experience, these criteria were structured and implemented in the Relation Oriented Inference System (ROIS), in which information can be structured by defining relations. Illustrative black and white images were digitized and integrated into the shell. The performance of the resulting decision support system was evaluated by a group of six pathologists using a set of slides covering the spectrum of the most frequently occurring histological types of invasive breast cancer. The pathologists first assessed histological type according to standard morphological procedures. The cases were then reassessed with the decision support system available for consultation. The use of the decision support system appeared to influence the previously assessed histological type in about half of the cases. Using the decision support system, histological typing was more uniform and more in accord with a 'gold standard' set by two experts.(ABSTRACT TRUNCATED AT 250 WORDS)

Original languageEnglish
Pages (from-to)253-9
Number of pages7
JournalHistopathology
Volume25
Issue number3
Publication statusPublished - Sept 1994

Keywords

  • Artificial Intelligence
  • Breast Neoplasms
  • Decision Support Techniques
  • Diagnosis, Computer-Assisted
  • Humans
  • Journal Article
  • Management Information Systems
  • Research Support, Non-U.S. Gov't

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