A device has been developed to assess breast health

Branching is characteristic not only of trees. This biological process takes place during animal development and allows organs to perform complex functions. Branched structures form in the lungs, kidneys, mammary glands, and other organs. It is important to note that in women’s mammary glands, branching occurs mainly years after birth — during puberty and pregnancy, when the milk ducts branch out in preparation for breastfeeding. Disruptions in this process are associated with breast cancer. However, studying branching can be complicated and labor-intensive.

A system developed at Cold Spring Harbor Laboratory, called MaGNet, may be used to study how hormonal changes and treatments affect the mammary glands, and even to detect early signs of breast cancer. The findings were published in the Journal of Mammary Gland Biology and Neoplasia.

Lewis, the study’s lead author, wondered whether a mathematical model previously used by the Navlakha team to study plants could be applied to the mammary gland. “It seemed like a natural extension of another branched structure,” he says.

Typically, researchers studying mammary glands in mice must cut thin slices of breast tissue, analyze them under a microscope, and manually count ducts and branches in each slice, reports the portal Scientific Russia. This process is “very labor-intensive and sometimes unreliable,” the scientist explains. “It is often impossible to get a full picture of the architecture of the mammary gland.”

MaGNet was created to precisely compare stained images of mammary tissue. Researchers simply trace the branches and then use software to map them as networks. The computer code then analyzes the networks and quantifies the data. “With this tool, we can measure the total length of the ductal tree, as well as the number of ducts, alveoli, and branching structures,” Lewis says. “It becomes very easy to rapidly visualize different networks and run tests.”

At this stage, MaGNet is used only in mice. However, the code can be adapted for any branching system. Ultimately, MaGNet may be used to study how specific conditions, such as infections, or life events like pregnancy and menopause, influence cancer risk. It may also help with early diagnosis. “We are always looking for warning signs that emerge before you can feel a lump or see something on a mammogram or ultrasound,” Lewis says. “Imagine an automated tool that could tell you that there is no tumor yet, but measurable changes are already present.”

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