Quantitative assessment of mouse mammary gland morphology using automated digital image processing and TEB detection.

The assessment of rodent mammary gland morphology is largely used to study the molecular mechanisms driving breast development and to analyze the impact of various endocrine disruptors with putative pathological implications. In this work, we propose a methodology relying on fully automated digital image analysis methods including image processing and quantification of the whole ductal tree and of the terminal end buds (TEB) as well. It allows to accurately and objectively measure both growth parameters and fine morphological glandular structures. Mammary gland elongation was characterized by two parameters: the length and the epithelial area of the ductal tree. Ductal tree fine structures were characterized by: 1) branch end-point density, 2) branching density and 3) branch length distribution. The proposed methodology was compared to quantification methods classically used in the literature. This procedure can be transposed to several software and thus largely used by scientists studying rodent mammary gland morphology.