The study objective was to determine whether tumor vascularity correlates with patient survival, to compare newer semiautomated methods of angiogenesis assessment to older methods, and to determine if advanced image analysis methods can offer useful patient outcome data in serous ovarian cancer. Using the specific endothelial marker CD34, microvessel determinations were quantified in 132 serous ovarian tumors by manual counting at final magnifications of x 200 and x 400 in the most highly vascular areas. Computer-assisted image analysis microvessel counts, endothelial area estimates, and minimum spanning tree (MST) analysis of capillary architecture, which involves assessment of intercapillary distances, were correlated with traditional manual techniques.Manual, semiautomated, and advanced image analysis methods were found to be highly reproducible and express strong correlation with one another. Univariate cyclooxygenase analysis revealed angiogenesis parameters to be highly significant predictors for overall survival (OS) and disease-free survival. Multivariate cyclooxygenase analysis revealed maximum MST (P = 0.009), length MST (P = 0.005), 1 nearest neighbor (P <or= 0.01) and mean microvessel density (x 400) (P = 0.0001) to be significant predictors for OS, and mean endothelial area (P <or= 0.01) and stage (P = 0.001) significant predictors for disease-free survival. Despite showing prognostic significance on univariate analysis, most clinicopathologic parameters did not retain independent significance on multivariate analysis. Microvessel determination is an independent prognostic indicator for survival in patients with serous ovarian carcinoma. Computer-assisted image analysis is a highly reproducible method of assessment capable of accurately evaluating tumor vascularity. Minimum spanning tree analysis of capillary architecture was found to be the strongest prognosticator for OS, suggesting this to be a promising marker.