CONTROL OF LOW-RESOLUTION SCANNING OF OVARIAN TUMOR STROMAL COMPARTMENT

Abstract

The active search for markers of prognostic impact and therapeutic response is of crucial importance in oncology. The amount of stroma is a potential indicator with a significant impact on tumor growth. To solve the problems linked to tumor heterogeneity and, hence, of quantization at the microscopic level, we developed an image-analysis strategy dedicated to estimating the proportion of tumor connective tissue in whole histological sections at low resolution. 2,700-dot-per-inch numerical images were acquired with a calibrated slide scanner and automatically analyzed. We performed a quality control in order to evaluate the efficiency of the proposed method of analysis at the selected resolution. The point-counting method and the interactive drawing of stroma limits on equivalent mosaic microscopic images were "the gold standards." The proportions of stroma estimated on microscopic images (magnification with a 4× objective corresponding to 16,200 dots per inch) and on slide scanner images (2,700 dots per inch) through point counting stereology or manual delineation were equivalent (p < 0.0001). The results obtained through automatic image processing of scanner images were also close to the gold standard (95% correlation, p < 0.0001). The proposed method makes it possible to estimate the stroma amount of ovarian carcinomas in whole histological sections with a simple, fast, and low-cost acquisition device.