For patients with a brain tumor, the first step in treatment is often surgery to remove as much of the mass as possible. A tumor sample obtained and analyzed during surgery can help to precisely diagnose the tumor and define the margins between tumor and healthy brain tissue. However, such intraoperative pathology analysis takes time—the sample must be processed, stained, and analyzed by a pathologist while the surgeon and patient wait for the results. Now, a new study shows that a process combining an advanced imaging technology and artificial intelligence (AI) can accurately diagnose brain tumors in fewer than 3 minutes during surgery. The approach was also able to accurately distinguish tumor tissue from healthy tissue. The findings were published January 6 in Nature Medicine. “This technology is especially encouraging for patients with newly detected tumors and patients with [recurrent tumors] who are undergoing second or third surgeries,” said Daniel Orringer, M.D., of NYU Langone Health, who helped lead the study. This study, the research team wrote, opens the door to “provid[ing] unparalleled access to intraoperative tissue diagnosis at the bedside during surgery” while “reducing the risk of removing … normal tissue adjacent to a [tumor].” Kareem Zaghloul, M.D., Ph.D., a neurosurgeon in NIH’s Surgical Neurology Branch who was not involved in the research, said he is encouraged by the study’s results. “This technology could help inform how aggressive or conservative surgery needs to be,” Dr. Zaghloul said.