Computer aided analysis of prostate histopathology images Gleason grading especially for Gleason score 7

Abstract

Clinically, prostate adenocarcinoma is diagnosed by recognizing certain morphology on histology. While the Gleason grading system has been shown to be the strongest prognostic factor for men with prostrate adenocarcinoma, there is a significant intra and interobserver variability between pathologists in assigning this grading system. In this study, we present a new method for prostate gland segmentation from which we then utilize to develop a computer aided Gleason grading. The novelty of our method is a region-based nuclei segmentation to get individual gland without using lumen as prior information. Because each gland region is surrounded by nuclei, individual gland can be segmented by using the structure features and Delaunay Triangulation. The precision, recal and F1 of this approach are 0.94±0.11, 0.60±0.23 and 0.70±0.19 respectively. Our method achieves a high accuracy for prostate gland segmentation with less computation time.

Fig. 1

Flow chart of our method

Fig. 2

Examples of four H&E stained images, but with quite different staining appearance for nuclei, cytoplasm, stroma and lumen. (a) and (b) shows a trend of gland infusion, many glands have touched other glands, while glands in (c) and (d) have merged together and it’s more difficult than (a) and (b) to separate each gland.

Fig. 3

(a) Stain vector contains gland and nuclei information; (b) Glandular region mask; (c) Nuclear region mask

Fig. 4

(a) Original Image; (b) Gland region mask, in which there are three gland regions in the images and are labeled by green arrows; (c) Distance transform of glandular region mask; (d) Local maximum points of distance transform image; (e) Grouping the nuclei that connect with local maximum points directly; (f) Contours of final (in red) image of gland segmentation, each black arrow indicates one gland.

Fig. 5

Each individual gland segmentation result of two representative example images. The manual annotation of each gland is shown in (a) and (c). Each segmented gland by using our approach is contoured in red or green line with its corresponding gland score on it as shown in (b) and (d).