The five-year survival rate of pancreatic cancer is one of the worst — 9 percent — in part because there are no obvious symptoms or non-invasive screening tools to catch a tumor before it spreads. One of the earliest symptoms of pancreatic cancer, as well as other diseases, is jaundice, a yellow discoloration of the skin and eyes caused by a buildup of bilirubin in the blood. The ability to detect signs of jaundice when bilirubin levels are minimally elevated — but before they're visible to the naked eye — could enable an entirely new screening program for at-risk individuals.
An app was developed that could allow people to easily screen for pancreatic cancer and other diseases by snapping a smartphone selfie. BiliScreen uses a smartphone camera, computer vision algorithms, and machine learning tools to detect increased bilirubin levels in a person's sclera, or the white part of the eye. In an initial clinical study of 70 people, the BiliScreen app — used in conjunction with a 3D-printed box that controls the eye's exposure to light — correctly identified cases of concern 89.7 percent of the time.
The blood test that doctors currently use to measure bilirubin levels — which is typically not administered to adults unless there is reason for concern — requires access to a healthcare professional, and is inconvenient for frequent screening. BiliScreen is designed to be an easy-to-use, non-invasive tool that could help determine whether someone ought to consult a doctor for further testing. Beyond diagnosis, BiliScreen could also potentially ease the burden on patients with pancreatic cancer who require frequent bilirubin monitoring.
In adults, the whites of the eyes are more sensitive than skin to changes in bilirubin levels, which also can be an early warning sign for hepatitis or the generally harmless Gilbert's syndrome. Unlike skin color, changes in the sclera are more consistent across all races and ethnicities. Yet, by the time people notice the yellowish discoloration in the sclera, bilirubin levels are already well past cause for concern.
BiliScreen uses a smartphone's built-in camera and flash to collect pictures of a person's eye as they snap a selfie. The team developed a computer vision system to automatically and effectively isolate the white parts of the eye, which is a valuable tool for medical diagnostics. The app then calculates the color information from the sclera — based on the wavelengths of light being reflected and absorbed — and correlates it with bilirubin levels using machine learning algorithms.
To account for different lighting conditions, the team tested BiliScreen with two different accessories: paper glasses printed with colored squares to help calibrate color, and the 3D-printed box that blocks out ambient lighting. Using the app with the box accessory led to slightly better results.
Next steps include testing the app on a wider range of people at risk for jaundice and underlying conditions, as well as continuing to make usability improvements — including removing the need for accessories like the box and glasses.