title: A class discovery and class prediction approach to histopathological classification of mammographic screen detected columnar cell lesions of the breast.
abstract: OBJECTIVE
  Columnar cell lesions (CCLs) of the breast have been increasingly recognised in biopsies taken to investigate mammographic screen detected microcalcification. The aim of this study was to identify distinct CCL subtypes by systematic analysis of histopathology.
  
  
  METHODS
  Hierarchical cluster analysis was performed based on the profile of histopathological features in 102 screen detected CCLs. Features assessed included nuclear morphology, acinar dilatation, epithelial cell hyperplasia, cell crowding, apical snout formation and intraluminal secretion. The stability of this classification was tested in an independent cohort of 32 cases.
  
  
  RESULTS
  The histopathology of screen detected CCLs was extremely variable. Hierarchical cluster analysis identified two subclasses: Class 1 (34/102, 33%) characterised by absence of nuclear atypia and less pronounced hyperplasia; and Class 2 (68/102, 67%) that were generally more atypical. Ki-67 scores were significantly lower for Class 1 CCLs (p < 0.001). In the independent cohort of 32 cases, Class 1 cases were clearly distinguished from Class 2, indicating that these were stable phenotypes amongst screen detected CCLs.
  
  
  CONCLUSIONS
  The histopathological features of CCLs diagnosed at screening are extremely heterogeneous. Using a systematic approach, we have devised a broad classification system that delineates a category of less atypical CCLs that could form a basis for future studies.
authors.affiliation: Department of Tissue Pathology, Institute of Clinical Pathology and Medical Research, Sydney West Area Health Service, New South Wales, Australia. nirmala.path@swahs.health.nsw.gov.au
authors.forename: Nirmala
authors.initials: N
authors.lastname: Pathmanathan
authors.forename: Elizabeth L
authors.initials: EL
authors.lastname: Salisbury
authors.forename: Pamela J
authors.initials: PJ
authors.lastname: Provan
authors.forename: A Michael
authors.initials: AM
authors.lastname: Bilous
authors.forename: Karen
authors.initials: K
authors.lastname: Byth
authors.forename: Jane S
authors.initials: JS
authors.lastname: Milliken
authors.forename: Christine L
authors.initials: CL
authors.lastname: Clarke
authors.forename: Rosemary L
authors.initials: RL
authors.lastname: Balleine
mesh_terms: D014408:Biomarkers, Tumor / Q000378:metabolism; D001706:Biopsy; D001940:Breast / Q000378:metabolism / Q000473:pathology*; D001943:Breast Neoplasms / Q000145:classification / Q000378:metabolism / Q000473:pathology*; D002114:Calcinosis / Q000378:metabolism / Q000473:pathology; D002467:Cell Nucleus / Q000473:pathology; D016000:Cluster Analysis; D004847:Epithelial Cells / Q000378:metabolism / Q000473:pathology*; D005260:Female; D006801:Humans; D006965:Hyperplasia; D019394:Ki-67 Antigen / Q000378:metabolism; D008327:Mammography; D011230:Precancerous Conditions / Q000145:classification / Q000378:metabolism / Q000473:pathology*
chemical_list: D014408:Biomarkers, Tumor; D019394:Ki-67 Antigen