Researchers develop new methods to diagnose glaucoma and detect disease progression

NewsGuard 100/100 Score

Two new research studies demonstrate that imaging technologies can help to diagnose and detect the progression of glaucoma, one of the leading causes of blindness in the U.S. When diagnosed early, vision loss from glaucoma can be slowed or prevented. The two studies are being presented at the 2018 Annual Meeting of the Association for Research in Vision and Ophthalmology (ARVO) in Honolulu, Hawaii, Sunday, April 29 – Thursday, May 3.

Diagnosing glaucoma with a new algorithm Scientists have developed an algorithm that automatically diagnoses glaucoma using fundus photography — color photos of the inside of the eye. The researchers used a training dataset of 1,364 photos of the inside of the eye with glaucoma appearances and 1,768 without glaucoma appearances. The testing dataset included non-near-sighted glaucoma patients, highly near-sighted glaucoma patients, non-highly near-sighted normative subjects and highly near-sighted normative subjects.

The researchers found that the algorithm was able to diagnose glaucoma from the photos as accurately as or better than those diagnosed by a medical doctor.

"Our study suggests that a leading edge, deep learning method of the residual network achieved an equivalent or superior diagnostic performance of glaucoma from a fundus photograph as compared to medical doctors -; even with a reasonably large training dataset and in highly myopic [near-sided] eyes," says first author Ryo Asaoka, MD, PhD, of the University of Tokyo.

This type of technology could lead to screening more patients at a faster rate, as well as help individuals identify the disease before significant vision loss.

Abstract title: Construction of a deep learning algorithm to automatically diagnose glaucoma using a fundus photograph
Presentation start/end time: Tuesday, May 1, 11:30 – 11:45am
Location: Ballroom A Abstract number: 3024

New measurement from eye imaging technology may detect glaucoma progression and predict worsening

Vision scientists have identified an eye measurement that may improve the detection of glaucoma progression and may predict the rates at which the disease worsens in patients.

Researchers observed 83 patients with glaucoma for at least two years, using a new technology called optical coherence tomography angiography (OCT-A), a noninvasive imaging technique that generates images of the volume flow rate of blood within seconds. OCT-A was used to obtain semi-annual measurements of the density of blood vessels in the macula and around the optic nerve head in patients. Results showed that patients with lower blood vessel densities saw a faster progression of retinal nerve fiber layer loss, an indicator of glaucoma.

"Assessment of optic nerve head and macular vessel density using OCT-A adds significant information to the evaluation of the risk of glaucoma progression and prediction of rates of disease worsening," says first author Sasan Moghimi, MD, of Shiley Eye Institute, University of California, San Diego. "These findings offer new insights about glaucoma management and support the role of OCT-A parameters as a factor to be considered in the assessment of the risk of progression in patients with primary open angle glaucoma."

Abstract title: Macular and Optic Nerve Head Vessel Density and Progressive Retinal Nerve Fiber Layer Loss in Glaucoma
Presentation start/end time:  Tuesday, May 1, 4 – 4:15pm
Location: Ballroom A Abstract number: 3498


The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of News Medical.
Post a new comment

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
AI model GPT-4 exceeds unspecialized doctors' ability to assess eye problems