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A healthy respect for software

OCM’s New Hope for Breast Cancer Patients

Nearly one in four women who have breast cancer and opt for a breast-saving lumpectomy will need a second surgery, according to a recent study. These repeat operations increase both the cost of medical treatment and the risk of complications.

Surgeons can freeze and examine surgically removed tissue during an operation to determine whether any cancer cells remain in the margin of tissue surrounding the excised tumor. But the accuracy of this approach is limited. And the results from a more thorough histopathological evaluation of the removed tissue are not available for several days.

What if surgeons had a more accurate way to find out—in real time in the operating room—whether the tumor margins were free of cancer cells?

Chao Zhou, assistant professor of bioengineering, and Sharon Xiaolei Huang, associate professor of computer science and engineering, are working to make that vision a reality. They have created a computer-aided diagnostic technique that combines cutting-edge imaging technology with advanced artificial intelligence to detect, in real-time, the difference between cancerous and benign cells.

“The idea is that one day, if this technique is used during surgery, it could complement the histopathology, potentially reducing the need for a second breast cancer surgery,” said Zhou.

Collaborators on the project include James G. Fujimoto of the Massachusetts Institute of Technology, James L. Connolly of Harvard Medical School, and Xianxu Zeng and Zhan Zhang of The Third Affiliated Hospital of Zhengzhou University in Henan, China.

In an article published in Medical Image Analysis, the researchers reported that their technique correctly identified benign versus cancerous cells more than 90 percent of the time. The article was titled “Integrated local binary pattern texture features for classification of breast tissue imaged by optical coherence microscopy.”

Sunhua Wan, a graduate student in Lehigh’s department of computer science and engineering, is the article’s lead author. Zhou and Huang are coauthors, along with Lehigh graduate students Ting Xu (computer science and engineering) and Tao Xu (electrical and computer engineering).

Read the full story at the Lehigh University News Center.