title: Computer-based association of the texture of expressed estrogen receptor nuclei with histologic grade using immunohistochemically-stained breast carcinomas.
abstract: OBJECTIVE
  To investigate the potential correlation between estrogen receptor (ER) texture and histologic grade in breast carcinomas.
  
  
  METHODS
  Clinical material comprised 96 biopsies of infiltrative ductal carcinomas that were hematoxylin-eosin (H-E) and immunohistochemically (IHC) stained. H-E-stained specimens were used for tumor grading, and IHC-stained specimens were analyzed for ER-status estimation. Spearman's correlation test was used to estimate the relation between histologic grade and both the physician's ER-status assessment and a computer system's ER-status evaluation. Moreover, a pattern recognition system was developed that takes as input textural features extracted from ER-expressed nuclei and outputs the grade of the tumor. The system was evaluated using an external cross-validation procedure in order to assess its generalization to new cases.
  
  
  RESULTS
  Spearman's correlation revealed that the histologic grading was inversely related to both the physician's ER-status assessment and to the computer system's ER-status evaluation. The pattern recognition system was able to predict histologic grade with 95.2% accuracy. Important textural nuclear features were proven--the skewness, the angular second moment and the sum of entropy.
  
  
  CONCLUSIONS
  ER-expressed nuclei texture was found to contain important information related to histologic grade.
authors.affiliation: Medical Image Processing and Analysis Group, Laboratory of Medical Physics, School of Medicine, University of Patras, Athens, Greece. skostopoulos@upatras.gr
authors.forename: Spiros
authors.initials: S
authors.lastname: Kostopoulos
authors.forename: Dimitris
authors.initials: D
authors.lastname: Glotsos
authors.forename: Dionisis
authors.initials: D
authors.lastname: Cavouras
authors.forename: Antonis
authors.initials: A
authors.lastname: Daskalakis
authors.forename: Ioannis
authors.initials: I
authors.lastname: Kalatzis
authors.forename: Pantelis
authors.initials: P
authors.lastname: Georgiadis
authors.forename: Panagiotis
authors.initials: P
authors.lastname: Bougioukos
authors.forename: Panagiota
authors.initials: P
authors.lastname: Ravazoula
authors.forename: George
authors.initials: G
authors.lastname: Nikiforidis
mesh_terms: D000465:Algorithms; D001706:Biopsy; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000378:metabolism / Q000473:pathology*; D018270:Carcinoma, Ductal, Breast / Q000175:diagnosis* / Q000378:metabolism / Q000473:pathology*; D002467:Cell Nucleus / Q000378:metabolism*; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007150:Immunohistochemistry; D016015:Logistic Models; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated; D011960:Receptors, Estrogen / Q000032:analysis / Q000378:metabolism*; D015203:Reproducibility of Results; D018709:Statistics, Nonparametric
chemical_list: D011960:Receptors, Estrogen