Nicolas Elie, Alexandre Labiche, Jean-Jacques Michels, Paulette Herlin


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.

automatic image analysis; ovarian cancer; quality control; stroma; slide scanner

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DOI: 10.5566/ias.v24.p85-93

Image Analysis & Stereology
EISSN 1854-5165 (Electronic version)
ISSN 1580-3139 (Printed version)