Computer-based image analysis promising for ROP
Computer algorithm fares well
The computer algorithm using manually segmented images agreed with the reference standard diagnosis 95% of the time, which was a better rate of agreement than all but one of the eight experts.
In addition, the researchers found that the computer algorithm could produce a quantitative output indicating the degree of tortuosity and dilation on a spectrum from mildest to most severe disease with multiple grades in between.
This more granular disease scale could help clinicians track disease progression, and help clinicians working by telemedicine to identify babies in need of ophthalmoscopy, said Dr. Campbell.
“We’re planning to make our algorithm freely available,” he added. “It could be an objective measure of disease in the same way you can go to the doctor and get a blood pressure measure.”
Dr. Campbell doesn’t expect the algorithm to take the place of clinical judgment. “It gives you one more piece of information in a way that’s more objective than your clinical exam is,” he pointed out.
The team also is working to put the algorithm in a smart phone application. Clinicians would use the phone’s camera to capture fundus images from a monitor screen and categorize them on a scale of severity.
Although the cell phone processor will be working with an image of an image, Dr. Campbell and his colleagues are hopeful that the resolution will be sufficient for an accurate analysis.
“Until we have the app working, we don’t know if you lose too much quality,” Dr. Campbell said. “There are a lot of exciting possibilities, and like anything we need to make sure they work in the real world.”