Fully automated microvessel counting and hot spot selection by image processing of whole tumour sections in invasive breast cancer

• Published in: Journal of clinical pathology Vol. 52; no. 3; pp. 184 - 192
• Main Authors: Beliën, J A, Somi, S, de Jong, J S, van Diest, P J, Baak, J P
• Format: Journal Article
• Language: English
• Published: London BMJ Publishing Group Ltd and Association of Clinical Pathologists 01.03.1999; BMJ
• Subjects: Biological and medical sciences; Breast Neoplasms - blood supply; Breast Neoplasms - pathology; Female; Humans; Image Interpretation, Computer-Assisted; Image Processing, Computer-Assisted; Investigative techniques, diagnostic techniques (general aspects); Medical sciences; Microcirculation; Miscellaneous. Technology; Neoplasm Invasiveness; Observer Variation; Pathology. Cytology. Biochemistry. Spectrometry. Miscellaneous investigative techniques; Platelet Endothelial Cell Adhesion Molecule-1 - analysis; Prognosis; Reproducibility of Results; Performance evaluation; Human; Immunohistochemistry; Carcinoma; Hot spot; Malignant tumor; Invasion; Pathology; Mammary gland diseases; Angiogenesis; Microcirculation; Image analysis; Manual processing; Blood vessel; Mammary gland; Technique; Automatic analysis; Comparative study; Quantitative analysis
• ISSN: 0021-9746; 1472-4146
• DOI: 10.1136/jcp.52.3.184

BACKGROUND: Manual counting of microvessels is subjective and may lead to unacceptable interobserver variability, which may explain conflicting results. AIMS: 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.