New Baylor Study Will Train AI to Assist Breast Cancer Surgery

In Clinical Studies News by Barbara Jacoby

By: Samantha McGrail


Researchers at Baylor College of Medicine will enroll patients in a study, ATLAS AI, which will use a high-resolution imaging system to collect images of breast tumors in order to develop artificial intelligence (AI) that can help with breast cancer surgery, according to a recent press release.

ATLAS AI will leverage Perimeter Medical Imaging’s OTIS system, which delivers real-time, ultra-high resolution, sub-surface images of extracted tissues, Baylor researchers explained.

The majority of breast cancer patients will undergo lumpectomy surgery as part of their treatment, hoping to remove the tumor and conserve the breast.

Perimeter’s AI technology, ImgAssist, is designed to utilize a machine learning model to help surgeons identify if cancer is still present when performing a lumpectomy.

This will allow surgeons to immediately remove additional tissue from the patient with the intent to reduce the likelihood that the patient will require additional surgeries, researchers explained.

“One of the big problems in breast cancer surgery is that in about one in four women on whom we do a lumpectomy to remove cancer, we fail to get clear margins,” Alastair Thompson, MD, professor, section chief of breast surgery and Olga Keith Wiess chair of Surgery at Baylor College of Medicine, said in the press release.

“That in turn leads to a need for reoperation to avoid high recurrence rates. Hence the need for a good, effective and user-friendly tool to help us better identify if we have adequately removed the breast cancer from a woman’s breast, to get it right the first time.”

Thomas, also a surgical oncologist at the Dan L Duncan Comprehensive Cancer Center at Baylor Medical Center and co-director of the Lester and Sue Smith breast center at Baylor College of Medicine, explained that OTIS and ImgAssist are noninvasive for the patients and fit into the routine surgical process.

“Our AI technology has the potential to be a powerful tool for ‘real-time’ margin visualization and assessment that we believe will help physicians improve surgical outcomes for breast cancer patients,” said Andrew Berkeley, co-founder of Perimeter Medical Imaging.

“The patients who enroll in these clinical studies at Baylor are contributing to new technology that we hope will assist surgeons in the future so that they can reduce the likelihood of their patients needing additional surgeries.”

ATLAS AI was made possible by a $7.4 million grant from the Cancer Prevention and Research Institute of Texas (CPRIT) to further develop the AI algorithm for OTIS.

The grant will allow the company to use data collected at pathology labs at Baylor College of Medicine, the University of Texas MD Anderson Cancer Center, and UT Health San Antonio as part of the study.

The study will enroll nearly 400 patients at the beginning of next week.

Additionally, Perimeter will continue the ATLAS AI Project with a second randomized, multi-site study in nearly 600 patients to test the OTIS platform with ImgAssist AI against current standard of care.

Through the study, researchers intend to uncover whether the platform lowers the re-operation rate for breast conservation surgery, Baylor researchers said.

“This could be a huge improvement for patient care. It could help patients avoid a second surgery and the physical, emotional, and financial stress that accompany an additional procedure,” Thompson concluded.