Tech developed in mice could help detect cancer in high-density breasts – ScienceDaily

A two-pronged approach to imaging breast density in mice, developed by researchers at the Georgetown Lombardy Comprehensive Cancer Center, has led to better detection of changes in breast tissue, including the detection of early signs of cancer. The researchers hope that this approach will translate from mice and improve human breast imaging; It may also help diagnose disease as density can be linked to certain patterns of mammary gland growth, including signs of cancer development.

The results appeared on September 14, 2022 in American Journal of Pathology.

Priscilla A. Forth, MD, professor of oncology and medicine at Georgetown Lombardy and corresponding author of the study, says. “This method has the benefit of being applicable to all ages of mice and shapes of mammary glands, in contrast to some of the methods used in previous studies.”

An innovative analytical computer program, developed by Georgetown alum Brendan Rooney (C’20) while working as an undergraduate in Furth’s lab, allowed mammary gland tissue to be sorted into one of two imaging assessments. Rooney first looked at the glands of younger mice and found that software that removed background ‘noise’ in those images helped enhance detection of abnormalities in more rounded lobed tissue. But as aging occurs and the chances of cancer increase, the lobules dwindle and the bumps become more noticeable, just as fallen autumn leaves reveal tree branches. The edges of the breast represent the ducts that carry milk and other fluids. When the noise removal technique was applied to images from older mice, it was found to be less reliable in detecting edges. So Ronnie and the team turned to a different imaging software, which was used primarily to detect vascular changes in the retina.

“The idea for the analytical software came from routine visual observations of tissue samples and the challenges of noticing differences in breast tissue using only a microscope. We found that human visual observations are important but further reading of anomalies from optimized imaging software added the validity and accuracy of our assessments,” says Rooney, lead author to study. “Not only does our software 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 Forth’s guidance, starting in his freshman year. “The support I received from Dr. Forth enabled me to present the idea and implement the project from start to finish – it provided an unparalleled experience of hands-on learning,” he says.

Being a mentor was an important part of Forth’s career in Georgetown Lombardy. “Georgetown has an undergraduate program called RISE, or Research Intensive Senior Experience, which enables students to delve deeply into a research project over the course of a year,” says Forth. “Brendan demonstrated exceptional drive and maturity to merit first authorship as an undergraduate developing his own research direction.”

Now that the research has been outlined and the principle has been proven, Rooney is starting medical school with a focus on specializing in oncology. Forth and Rooney both believe that future studies will need to refine and simplify their research approach in mice, including better density measurements that could enable samples to be sorted into higher and lower odds of developing cancer.

In addition to Furth and B. L. Rooney, other authors from Georgetown University include Brian P. Rooney, Vinona Muralidaran, and Weisheng Wang.

This study was supported by NIH grant UH3CA213388 and the American Society of Investigative Pathology: Pathology Summer Research Opportunities Program.

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