title: Differential diagnosis of follicular tumor by expert systems based on a set of quantitative features of thyrocyte nuclei and aggregates.
abstract: OBJECTIVE
  To develop expert systems for classification of follicular thyroid tumor at a preoperative stage.
  
  
  METHODS
  Fine needle aspiration biopsy of the thyroid gland with a histologic conclusion of follicular cancer and follicular adenoma were the object of the morphometric study. General sample size was 4500 nuclei and 3000 aggregates.
  
  
  RESULTS
  Quantitative regularities of pathologic changes in thyrocyte nuclei and aggregates in follicular cancer and follicular adenoma were revealed. Threshold values and weighting coefficients of quantitative features of thyrocyte nuclei and aggregates characterizing cancer made the basis of the two expert systems. Expert systems included standard 2-D S-matrix containing threshold values of nuclei and aggregates in cancer and their weighting coefficients as well as 1-D scientific X-matrix designed for filling with quantitative features of the studied object. The diagnosis was verified by the value of a diagnostic index by means of comparing feature values in the corresponding elements of S- and X-matrices. After that, a diagnostic index was calculated taking into account the features' weighting coefficient.
  
  
  CONCLUSIONS
  The developed expert systems based on a set of quantitative features of thyrocyte nuclei and aggregates will allow assessing the malignant potential of a follicular thyroid tumor at a preoperative stage.
authors.affiliation: Laboratory for Electron Paramagnetic Resonance Dosimetry and Cytology, Belarusian State Medical University, Minsk, Belarus. kirillov@bsmu.by
authors.forename: Vladimir
authors.initials: V
authors.lastname: Kirillov
authors.forename: Olga
authors.initials: O
authors.lastname: Emeliyanova
mesh_terms: D018263:Adenocarcinoma, Follicular / Q000473:pathology*; D001706:Biopsy; D002449:Cell Aggregation; D002467:Cell Nucleus / Q000473:pathology; D003937:Diagnosis, Differential; D005103:Expert Systems; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007620:Karyometry / Q000379:methods*; D008954:Models, Biological; D013961:Thyroid Gland / Q000473:pathology; D013964:Thyroid Neoplasms / Q000473:pathology*