fbpx

A method created in mice may help with the identification of cancer in thick breasts.

The results were published in American Journal of Pathology.

Researchers at Georgetown Lombardi Comprehensive Cancer Center improved breast tissue change detection, including early cancer symptoms, by using a two-pronged strategy to assessing breast density in mice.

As density may be connected to specific patterns of mammary gland growth, including symptoms of cancer development, the researchers are hopeful that this strategy will be applied to humans and improve breast imaging.

“Having a means to accurately assess mammary gland density in mice, just as is done clinically for women using mammograms, is an important research advance,” says Priscilla A. Furth, MD, professor of oncology and medicine at Georgetown Lombardi and corresponding author of the study. “This method has the benefit of being applicable across all ages of mice and mammary gland shapes, unlike some methods used in earlier studies.”

While an undergraduate in Furth’s lab, Brendan Rooney (C’20) created an inventive analytical computer software that enabled the classification of mammary gland tissue to one of two imaging evaluations.

Younger mouse glands were the subject of Rooney’s original research, and he discovered that a programme that reduced background ‘noise’ in those photos improved the ability to spot anomalies in the generally rounder, more lobular tissues. However, as people age and their risk of getting cancer rises, lobules get smaller and ridges are more noticeable, much to how dropping autumn leaves reveal tree branches.

The ducts that convey milk and other fluids are represented by the mammary ridges. The de-noising technique was shown to be less accurate at identifying ridges when used on the photos from the older mice. Since this imaging technique has mostly been utilised to identify blood vessel alterations in the retina of the eye, Rooney and the colleagues decided to employ it.

“The idea for the analytic program came from routine visual observations of tissue samples and the challenges inherent in observing differences in breast tissue with just a microscope. We found that visual human observations are important but having another read on abnormalities from optimal imaging programs added validity and rigor to our assessments,” says Rooney, the lead author of the study. “Not only does our program result in a high degree of diagnostic accuracy, it is freely available and easy to use.” Rooney notes that he could not have done this research without Furth’s mentorship, starting as early as his freshman year. “The support that I received from Dr. Furth enabled me to introduce an idea and execute the project from start to finish — it provided an unparalleled experience in hands-on learning,” he says.

Being a mentor has been an important part of Furth’s career at Georgetown Lombardi. “Georgetown University has a program for undergraduate students called RISE, or Research Intensive Senior Experience, that enables students to delve deeply into a research project over a year,” says Furth. “Brendan demonstrated exceptional drive and maturity to merit a first authorship as an undergraduate student developing his research direction.”

Rooney has started medical school with a potential view toward focusing in oncology now that the broad strokes of the research have been developed and proof of principle has been established.

Furth and Rooney concur that future studies will need to improve and streamline their mouse study methodology, including improved density measures that would allow the classification of samples into those with a higher and lower likelihood of developing cancer.
In addition to Furth and BL Rooney, the other authors from Georgetown include Brian P. Rooney, Vinona Muralidaran, and Weisheng Wang.

A method created in mice may help with the identification of cancer in thick breasts.

Leave a Reply

Your email address will not be published.

Scroll to top