title: Fully automated microvessel counting and hot spot selection by image processing of whole tumour sections in invasive breast cancer.
abstract: BACKGROUND
  Manual counting of microvessels is subjective and may lead to unacceptable interobserver variability, which may explain conflicting results.
  
  
  OBJECTIVE
  To develop and test an automated method for microvessel counting and objective selection of the hot spot, based on image processing of whole sections, and to compare this with manual selection of a hot spot and counting of microvessels.
  
  
  METHODS
  Microvessels were stained by CD31 immunohistochemistry in 10 cases of invasive breast cancer. The number of microvessels was counted manually in a subjectively selected hot spot, and also in the same complete tumour sections by interactive and automated image processing methods. An algorithm identified the hot spots from microvessel maps of the whole tumour section.
  
  
  RESULTS
  No significant difference in manual microvessel counts was found between two observers within the same hot spot, and counts were significantly correlated. However, when the hot spot was reselected, significantly different results were found between repeated counts by the same observer. Counting all microvessels manually within the entire tumour section resulted in significantly different hot spots than manual counts in selected hot spots by the same observer. Within the entire tumour section no significant differences were found between the hot spots of the manual and automated methods using an automated microscope. The hot spot was found using an eight connective path search algorithm, was located at or near the border of the tumour, and (depending on the size of the hot spot) did not always contain the field with the largest number of microvessels.
  
  
  CONCLUSIONS
  The automated counting of microvessels is preferable to the manual method because of the reduction in measurement time when the complete tumour is scanned, the greater accuracy and objectivity of hot spot selection, and the possibility of visual inspection and relocation of each measurement field afterwards.
authors.affiliation: Department of Pathology, Academic Hospital Vrije Universiteit, Amsterdam, The Netherlands. jam.belien@azvu.nl
authors.forename: J A
authors.initials: JA
authors.lastname: Beliën
authors.forename: S
authors.initials: S
authors.lastname: Somi
authors.forename: J S
authors.initials: JS
authors.lastname: de Jong
authors.forename: P J
authors.initials: PJ
authors.lastname: van Diest
authors.forename: J P
authors.initials: JP
authors.lastname: Baak
mesh_terms: D001943:Breast Neoplasms / Q000098:blood supply* / Q000473:pathology; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D007091:Image Processing, Computer-Assisted; D008833:Microcirculation; D009361:Neoplasm Invasiveness; D015588:Observer Variation; D019408:Platelet Endothelial Cell Adhesion Molecule-1 / Q000032:analysis; D011379:Prognosis; D015203:Reproducibility of Results
chemical_list: D019408:Platelet Endothelial Cell Adhesion Molecule-1