Article

Edge Detection Might Help Determine Differences in Patients With Far-Advanced Glaucoma

There’s significant evidence that some patients with far-advanced glaucoma are able to perform more tasks than others. Yet, it’s difficult to distinguish these patients from each other. A new study proposes a way to find out.

Scientists have uncovered a new strategy for determining visual function in low-vision patients with advanced glaucoma.

In findings published this month in the journal Medicine, a team of investigators from South Korea argues that edge detection can be a meaningful test to gauge visual function in these patients.

Glaucoma is already a major public health problem, but with the world’s population living to older ages, the number of people worldwide with the eye condition is expected to hit 80 million this year. About 1 in 10 of those patients will be considered blind as a result of the disease.

Despite the severity of the problem, corresponding author Chan Kee Park, MD, PhD, of Seoul St. Mary’s Hospital and the Catholic University of Korea, notes that there still seems to be significant differences in quality of life among patients with advanced glaucoma who appear to have similar visual fields (VFs).

“Among patients with the same total VF defect test results, some patients are able to successfully complete daily activities, but some patients need help,” Park and colleagues wrote.

Nor can retinal structure evaluation adequately assess advanced cases, they noted, “due to the ‘floor effect’ of the retinal nerve fiber layer (RNFL) measuring.”

This inability of VF or retinal structure to predict quality of life led Park and others to seek out additional strategies for evaluating differences between patients with far-advanced glaucoma.

In search of a better option, Park and colleagues turned to research related to goldfish. A decade-old study found that goldfish were able to detect edges when evaluated using a pattern band that is similar to an optokinetic band. The investigators note that it’s not clear whether goldfish are able to detect high-frequency contrast sensitivity, so they hypothesized that some humans with difficulty discerning high-frequency contrast sensitivity might be able to detect edges using a pattern edge band.

The team recruited 44 patients, and after exclusions, 73 eyes were included in the study. The team looked for correlations between low-vision quality of life scores (LVQOL) and visual function parameters. When it came to far-off activities, both visual acuity and pattern edge band scores correlated with LVQOL. However, when it came to “near” activities, only visual acuity was a predictor of LVQOL.

The investigators then repeated the same test with the 22 patients who had a decimal visual acuity of 0.1 or less. Once again, they found visual acuity and pattern edge band correlated with LVQOL. However, this time when these patients were scored for distant activity, only pattern edge band, and not visual field status, correlated with LVQOL.

“This means that the evaluation of edge detection ability using the pattern edge band can be an assistant for assessing the visual function of patients with poor VA,” the authors wrote.

The study had some limitations. For one, the socioeconomic status of participants was not recorded, even though socioeconomic status might have an impact on quality of life. The authors also said additional study would be necessary to ensure that the results are replicable.

“Assessment of edge detection ability using the pattern edge band may be a promising additive parameter for visual function in low vision patients,” Park and colleagues conclude. “Furthermore, it might be expected to help in the evaluation of visual function improvement through neuroprotective treatment in advanced glaucoma.”

Reference

Jeon SJ, Jung Y, Jung CS, Park HYL, Park CK. Visual function evaluation for low vision patients with advanced glaucoma. Medicine. 2020;99:7(e19149).

Related Videos
Quint Petris
Mina Massaro-Giordano, MD
Quint and Petris
Quint Petris
Image of the UPMC eyeVan
Image of the UPMC eyeVan
Screenshot of Byron Lam, MD
Screenshot of Byron Lam, MD
Screenshot of Byron Lam, MD
Related Content
AJMC Managed Markets Network Logo
CH LogoCenter for Biosimilars Logo