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Evaluation of automated estimation of epithelial volume and its prognostic value in ovarian tumors.

The paper describes an improved segmentation method to measure the percentages of epithelium and stroma in ovarian (tumor) tissue with automated image analysis and evaluates its prognostic value. In the image processing method, a blue-yellow image pair is recorded from standard paraffin sections and stained with pararosanilin Feulgen and naphthol yellow. The blue image is used for automated determination of the total tissue area and the yellow image for the epithelial area. Results are obtained with 114 ovarian tumors of the common epithelial types (14 borderline tumors and 100 invasive carcinomas with varying degrees of differentiation). The fraction of epithelium in the total tissue shows a strong correlation with the epithelial percentage resulting from interactive morphometry (r = 0.991) for 15 tumors of varying histological grades. The prognostic value is evaluated on the 100 invasive carcinomas. Survival analysis implies that the epithelial percentage is of prognostic importance (Mantel-Cox 7.4, p = 0.0064). Multivariate analysis shows that the estimated fraction of epithelium is the strongest factor and that the FIGO stage has additional prognostic value (Mantel-Cox 12.5, p = 0.0004). It can be concluded that epithelial volume, as automatically estimated by image processing, seems useful in predicting the prognosis of patients with ovarian cancers.