Earlier Detection of Diabetic Retinopathy with Smartphone AI

Pairing a smartphone to capture retinal images with artificial intelligence to interpret them may help overcome barriers to ophthalmic screening for the disease.

1:00 PM

Author | Shelley Zalewski

Yannis M. Paulus, M.D., the study's lead author

A novel pairing of two technologies may offer a solution for better screening for diabetic retinopathy, a condition that can lead to permanent vision loss if not caught early.

LISTEN UP: Add the new Michigan Medicine News Break to your Alexa-enabled device, or subscribe to our daily audio updates on iTunes, Google Play and Stitcher.

At the 2019 annual meeting of The Association for Research in Vision and Ophthalmology, researchers at the University of Michigan Kellogg Eye Center revealed that combining a smartphone-mounted device that takes high-quality retinal pictures with artificial intelligence software that reads them can determine in real  time whether a patient should be referred to an ophthalmologist for follow-up.

"The key to preventing DR-related vision loss is early detection through regular screening," says Yannis Paulus, M.D., a Kellogg vitreoretinal surgeon and the study's lead author. "We think the key to that is bringing portable, easy-to-administer, reliable retinal screening to primary care doctors' offices and health clinics."

Smartphone-based tool for rapid, portable screening

Michigan Medicine is one of a handful of institutions leading an effort to adapt smartphone technology to ophthalmic screening.

Paulus was part of a Kellogg team that developed a device that turns a smartphone into a functioning retinal camera.

SEE ALSO: Enhancing Eye Care with a Smartphone

In 2016, the project, CellScope Retina, was one of 12 funded by U-M's Translational Research and Commercialization for Life Sciences Innovation Hub, which accelerates ideas with a high potential for positively impacting human health.

The new study utilizes the latest generation of the device, now called RetinaScope.

"Traditional retinal cameras are expensive, large, immovable and require special training to operate, whereas RetinaScope is a smartphone-based platform that is cheap, handheld and easy to use with no required training," says Paulus, an assistant professor of ophthalmology and visual sciences and an assistant professor of biomedical engineering.

While smartphone platforms like RetinaScope can be used to deliver high-definition retinal images virtually anywhere, that's only part of the challenge.

"It can take two to seven days for an ophthalmologist to interpret the images," Paulus explains. "To make screening truly accessible, we need to provide on-the-spot feedback, taking the photo and interpreting it while the patient is there to schedule an eye appointment if necessary."

That's where another emerging technology called deep neural network software comes in.

"Deep neural network is an AI software platform that can enhance and review images and provide automated grading of lesions present in DR, indicating which lesions require referral to an ophthalmologist for follow-up," he says.

Paulus' team utilizes a proprietary software platform called EyeArt developed by the California-based company Eyenuk. "This is the first study to combine the imaging technology with automated real-time interpretation and compare it to gold standard dilated eye examination," Paulus says, "and the results are very encouraging."

Reducing obstacles to care

Data was collected from 69 adult patients with diabetes seen in the Kellogg Eye Center Retina Clinic, including previously recorded results of dilated slit-lamp fundus examinations by their treating clinicians.

After pupillary dilation, RetinaScope was used to image patient retinas and the images were analyzed with EyeArt software, which graded them as referral-warranted diabetic retinopathy (RWDR) or non-referral-warranted DR.

The same images were independently evaluated by two expert readers trained to recognize signs of diabetic retinopathy.

SEE ALSO: Telemedicine Could Improve Eye Exam Access for People with Diabetes

"We took the extra step of comparing both automated interpretation and human expert graders with slit lamp evaluation to overcome what we felt was a shortcoming of similar studies conducted elsewhere," says Michael Aaberg, a research assistant in the Paulus lab and study co-author.

"When human grading is used as the only check of AI-based grading, there's a risk that photos that fail to accurately capture the pathology of DR could be interpreted incorrectly by both," Aaberg says.

Sensitive enough

The study compared two measurements: if the screening was sensitive enough to find disease, and if it was specific enough to confirm when an individual does not have diabetic retinopathy.

"Sensitivity is the more crucial measurement in a screening test," explains Aaberg, "since the worst-case scenario is disease that progresses due to a missed diagnosis."  

Slit-lamp evaluation confirmed RWDR in 53 subjects (76.8 percent). Automated interpretation had a sensitivity of 86.8 percent (above the 80 percent recommended for an ophthalmic screening device) and specificity of 73.3 percent.

One of the human graders achieved a level of sensitivity that was higher by a statistically significant factor (96.2 percent), and both had lower specificity (40 percent and 46.7 percent).

"This is the first time AI used on a smartphone-based platform has been shown to be effective when compared to the gold standard of clinical evaluation," says Paulus.

Encouraged by both these findings and the soon-to-be-published results of a usability study in a primary care clinic, Paulus' lab continues to pursue hardware and software improvements (notably a version that does not require pupillary dilation), as well as FDA clearance.

"We're focused on overcoming patients' reluctance to seek DR screening by bringing it to them," Paulus says, "making it easy, immediate and available in a familiar clinical environment."


More Articles About: Health Tech Eye Disorders Kellogg Eye Center Health Care Delivery, Policy and Economics Diabetes Eye Care & Vision
Health Lab word mark overlaying blue cells
Health Lab

Explore a variety of healthcare news & stories by visiting the Health Lab home page for more articles.

Media Contact Public Relations

Department of Communication at Michigan Medicine

[email protected]

734-764-2220

Stay Informed

Want top health & research news weekly? Sign up for Health Lab’s newsletters today!

Subscribe
Featured News & Stories computer
Health Lab
Same patient. Different visit. Different race and ethnicity?
Data on the race and ethnicity of patients underpins efforts to reduce health care disparities, but a study shows inconsistent recording in emergency departments
Blurred image of health care professionals in blue scrubs pushing a gurney down a hallway
Health Lab
Primary care scarcity linked to more surgical emergencies, problems
Patients living in areas with the worst shortages of primary care providers are more likely to have emergency surgery, surgical complications and hospital readmissions.
Person's hand holding an aspirin tablet with a glass of water nearby
Health Lab
An aspirin a day? Some older adults who take it may be following outdated advice
Many people aged 50 to 80 who said they take aspirin multiple times a week may not need to do so and could be causing health risks, according to National Poll on Healthy Aging.
Illustration of girl with blue water line, depicting a figure drowning, as girl contemplates pill in hand
Health Lab
Antidepressant dispensing to adolescents and young adults surges during pandemic
Rate of antidepressant dispensing to young people rose faster after March 2020, especially among females
Scale pictured behind a hospital room curtain
Health Lab
Obesity care can make a big difference, but few get it, study suggests
Obesity care under a health care provider’s supervision, whether through nutrition counseling, medication, meal replacement or bariatric surgery, can help people with high BMI, but many don’t receive it.
Woman in pink shirt lifts kettleball in an outdoor exercise class
Health Lab
How to make cancer prevention more equitable
Expert explains six behavioral risk factors for cancer and why current programs don’t always meet the needs of people from racially and ethnically minoritized groups and other vulnerable populations.