Researchers from the University of Washington have developed a smartphone application capable of screening for pancreatic cancer through taking a 'selfie.'
Currently, detecting pancreatic cancer is difficult due to the lack of symptoms, and non-invasive screening tools are unable to detect tumors before they spread. The BiliScreen app uses a smartphone camera, computer vision algorithms and artificial intelligence to detect increased levels of bilirubin, which identify a patient’s risk in developing pancreatic cancer, in the whites of a patient’s eye.
"The eyes are a really interesting gateway into the body—tears can tell you how much glucose you have, sclera can tell you how much bilirubin is in your blood," said senior author Shwetak Patel, the Washington Research Foundation Entrepreneurship Endowed Professor in Computer Science & Engineering and Electrical Engineering. "Our question was: Could we capture some of these changes that might lead to earlier detection with a selfie?"
The initial clinical trial of 70 participants showed the BiliScreen app was able to correctly pinpoint cases of concern with 89.7 percent accuracy, when compared to blood tests. The app’s high level of accuracy assists physicians in identifying which patients need further testing as well as unburdening patients with pancreatic cancer that need frequent bilirubin monitoring.
"The problem with pancreatic cancer is that by the time you're symptomatic, it's frequently too late," said lead author Alex Mariakakis, a doctoral student at the Paul G. Allen School of Computer Science & Engineering. "The hope is that if people can do this simple test once a month—in the privacy of their own homes—some might catch the disease early enough to undergo treatment that could save their lives."