Dr. Yu Receives NIH Grant to Advance Intraoperative Breast Tumor Margin Assessment

Headshot of Dr. Bing YuOct. 6, 2022

Bing Yu, PhD, associate professor in the Marquette-Medical College of Wisconsin Joint Department of Biomedical Engineering, has received a $1.54-million grant from the National Institutes of Health for the development of deep-learning enabled ultraviolet scanning microscopy for intraoperative assessment of breast tumor margins. Developed in collaboration with Tina Yen, MD, professor of surgical oncology, and Julie Jorns, MD, associate professor of pathology, this project is anticipated to have a direct impact on public health.

Women with positive margins after breast conserving surgery (BCS) are at two-times the risk of recurrence, and re-excision is recommended. The current re-excision rate for BCS in the U.S. is 14-18% and highly variable among surgeons. While several technologies for intraoperative assessment of breast tumor margins do exist, they are highly variable and often not employed.

More recently proposed solutions are either point- or high-resolution devices with very small fields-of-view that require excessive scanning time or wide-field devices with low spatial resolution and poor sensitivity. Because the size of BCS specimens varies significantly and positive margins may include multiple foci, an intraoperative device with both large margin coverage and microscopic resolution that can accurately and efficiently evaluate an entire surgical specimen is highly desirable.

The proposed research seeks to yield a technology that meets these criteria by using deep ultra-violet light for surface excitation of fresh specimens, parallel imaging of two margins, a low optical magnification for fast speed, and deep-learning and sparse sampling to rapidly search for pathological features of cancer cells. The imaging device will be distinctly relevant to public health in that it will significantly reduce the need for additional surgery for women who undergo BCS. In addition, the technology is expected to have applications relevant to other surgical and clinical settings.

This project will be executed in collaboration with co-principal investigator Dr. Dong Hye Ye, assistant professor of computer and electrical engineering at Marquette University, who specializes in machine learning and image processing. Co-investigators include Dr. Taly Gilat-Schmidt, professor in the Marquette-MCW Joint Department of Biomedical Engineering, Dr. Yen and Dr. Jorns.