Microvessel Density Image Analysis Essay

Assessment of tissue vascularization using immunohistochemical techniques for microvessel detection has been limited by difficulties in generating reproducible quantitative data. The distinction of individual blood vessels and the selection of microscopic fields to be analyzed remain two factors of subjectivity. In this study, we used imaging analysis software and a high-resolution slide scanner for measurement of CD31-immunostained endothelial area (EA) in whole sections of human neuroblastoma xenograft and murine mammary adenocarcinoma tumors. Imaging analysis software provided objective criteria for analysis of sections of different tumors. The use of the criteria on images of entire tumor section acquired with the slide scanner constituted a rapid method to quantify tumor vascularization. Compared with previously described methods, the “hot spot” and the “random fields” methods, EA measurements obtained with our “whole section scanning” method were more reproducible with 8.6% interobserver disagreement for the “whole section scanning” method vs 42.2% and 39.0% interobserver disagreement for the “hot spot” method and the “random fields,” respectively. Microvessel density was also measured with the whole section scanning method and provided additional data on the distribution and the size of the blood vessels. Therefore, this method constitutes a time efficient and reproducible method for quantification of tumor vascularization.


In some studies of breast cancer, quantitation of immunohistochemically highlighted microvessel ‘hot spots’ has been shown to be a powerful prognostic tool. However, the antibody used, the number and size of the ‘hot spots’ assessed, and the stratification of patients into high and low vascular groups vary between studies. Furthermore, little is known about the relationship between microvessel density and other vascular parameters. These uncertainties and the laborious nature of the technique make it unsuitable for diagnostic practice. Both manual and computerized image analysis techniques were used in this study to examine the relationship between microvessel density and the vascular parameters in different sized microscopic fields in a pilot series of 30 invasive breast carcinomas. Automated pixel analysis of immunohistochemical staining, Chalkley point counting, and observer subjective vascular grading were also assessed as more rapid methods of measuring tumour vascularity. A Chalkley count was also performed on a further 211 invasive breast carcinomas. Significant correlations were observed between manual microvessel density and luminal perimeter (r=0·6, P=0·0004), luminal area (r=0·56, P=0·002), and microvessel number (r=0·57, P=0·0009) by computerized analysis. There were also significant correlations between the microscopic hot spots of 0·155 mm2 and 0.848 mm2 for microvessel number (r=0·81, P>0·00005), luminal perimeter (r=0·78, P<0·00005), and luminal area (r=0·65, P=0·0001). In addition, a significant correlation was observed between microvessel density and both subjective vascular grade (P=0·002) and Chalkley count (P=0·0001). A significant reduction in overall survival was observed between patients stratified by Chalkley count in both a univariate (P=0·02) and a multivariate (P=0·05) analysis in the 211 invasive breast carcinomas. These findings show that Chalkley counting is a rapid method of quantifying tumour angiogenesis and gives independent prognostic information which might be useful in diagnostic practice.

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