Quantitative Assessment of Epithelial Proliferation in Rat Mammary Gland Using Artificial Intelligence Independent of Choice of Proliferation Marker

Abstract

Epithelial proliferation in the rat mammary gland is recommended in regulatory guidelines as an endpoint for assessment of the in vivo carcinogenic potential of insulin analogues. Epithelial proliferation is traditionally assessed by immunohistochemical staining of a proliferation marker, for example, 5-bromo-2′-deoxyuridine (BrdU) or Ki67, followed by labor-intensive manual counting of positive and negative cells. The aim of this study was to develop and validate an approach for image analysis based on artificial intelligence, which can be used for quantification of proliferation in rat mammary gland, independent of the choice of proliferation marker. Furthermore, the aim was to compare the markers BrdU, Ki67, and phosphorylated histone H3 (PHH3). A sequence of image analysis applications were developed, which allowed for quantification of proliferative activity in the mammary gland epithelium. These endpoints agreed well with manually counted labeling indices, with correlation coefficients in the range ≈0.92–0.93. In addition, all three proliferation markers were significantly correlated and could detect the variation in epithelial proliferation during the estrous cycle. In conclusion, image analysis can be used to quantify epithelial proliferation in the rat mammary gland and thereby replace time-consuming manual counting. Furthermore, BrdU, Ki67, and PHH3 can be used interchangeably to assess proliferation.