title: Semi-automatic identification of punching areas for tissue microarray building: the tubular breast cancer pilot study.
abstract: BACKGROUND
  Tissue MicroArray technology aims to perform immunohistochemical staining on hundreds of different tissue samples simultaneously. It allows faster analysis, considerably reducing costs incurred in staining. A time consuming phase of the methodology is the selection of tissue areas within paraffin blocks: no utilities have been developed for the identification of areas to be punched from the donor block and assembled in the recipient block.
  
  
  RESULTS
  The presented work supports, in the specific case of a primary subtype of breast cancer (tubular breast cancer), the semi-automatic discrimination and localization between normal and pathological regions within the tissues. The diagnosis is performed by analysing specific morphological features of the sample such as the absence of a double layer of cells around the lumen and the decay of a regular glands-and-lobules structure. These features are analysed using an algorithm which performs the extraction of morphological parameters from images and compares them to experimentally validated threshold values. Results are satisfactory since in most of the cases the automatic diagnosis matches the response of the pathologists. In particular, on a total of 1296 sub-images showing normal and pathological areas of breast specimens, algorithm accuracy, sensitivity and specificity are respectively 89%, 84% and 94%.
  
  
  CONCLUSIONS
  The proposed work is a first attempt to demonstrate that automation in the Tissue MicroArray field is feasible and it can represent an important tool for scientists to cope with this high-throughput technique.
authors.affiliation: Institute for Biomedical Technologies of the National Research Council, Segrate, Milan, Italy. federica.viti@dist.unige.it
authors.forename: Federica
authors.initials: F
authors.lastname: Viti
authors.forename: Ivan
authors.initials: I
authors.lastname: Merelli
authors.forename: Mieke
authors.initials: M
authors.lastname: Timmermans
authors.forename: Michael
authors.initials: M
authors.lastname: den Bakker
authors.forename: Francesco
authors.initials: F
authors.lastname: Beltrame
authors.forename: Peter
authors.initials: P
authors.lastname: Riegman
authors.forename: Luciano
authors.initials: L
authors.lastname: Milanesi
mesh_terms: D000230:Adenocarcinoma / Q000473:pathology*; D001943:Breast Neoplasms / Q000473:pathology*; D005260:Female; D006801:Humans; D010865:Pilot Projects; D046888:Tissue Array Analysis / Q000379:methods*