Future Glaucoma Detection

New technologies and AI may soon better detect progression. Howard Larkin reports from the American Glaucoma Society 2022 annual meeting

Emerging diagnostic techniques should help detect and track glaucoma progression, reports Felipe A Medeiros MD, PhD.

Optical coherence tomography angiography (OCTA) is one promising technology. OCTA allows mapping of blood vessel density in the retina, which decreases as glaucoma progresses, Dr Medeiros explained.

In one study with a mean follow-up of 14 months, OCTA showed faster loss of macula vessel density in eyes with primary open-angle glaucoma than healthy eyes without evidence of change in conventional macular thickness measures.i

A second OCTA study found a relationship between the decline in macula vessel density and faster future visual field loss.ii

“The relationship was somewhat higher than you would see with the ganglion cell complex thinning but still not very strong at an R2 of 0.07,” Dr Medeiros noted.

While OCTA is a promising technology that may help clarify pathogenetic mechanisms in glaucoma, there is currently no clear evidence of additional benefit for detecting progression compared with conventional OCT studies, such as peripapillary retinal nerve fibre layer thickness.

AI DETECTION Applying artificial intelligence to imaging data may help detect glaucoma progression, Dr Medeiros said. Working with colleagues, he recently trained a deep learning algorithm to replicate the work of glaucoma specialists, who graded progression based on OCT scans. It replicated the work of glaucoma experts well, with a score of 0.935 in the area under the Receiver Operating Characteristic (ROC) curve.

“The combination of multiple sources of imaging with AI is likely to improve our detection of change in the near future,” said Dr Medeiros, adding there are still challenges related to how to train and validate these models.

Detection of apoptosing retinal cells (DARC) involves fluorescently marking phosphatidylserine—an early marker of apoptosis—and imaging it with confocal scanning laser ophthalmoscopy. AI is useful for interpreting these images as well. A baseline DARC was able to predict progression seen 18 months later on OCT with an accuracy of 0.88 for the area under the ROC curve.iii

“You see more apoptotic cells in the eye that was progressing,” Dr Medeiros said.

COUNTING GANGLION CELLS Adaptive optics OCT is another promising technology that may allow for detecting progressive loss of ganglion cells in glaucoma. AI can help automate the quantification of ganglion cell damage in this technology, Dr Medeiros said. This may eventually find a way into clinical practice. For the present, however, the technology may be more useful for research, such as in early-stage drug trials.

Lastly, Dr Medeiros considered head-mounted perimetry systems for detecting progression but noted that none has yet been validated in a longitudinal study.

“They may enable more frequent testing, which would be a very welcome addition. But they still need validation as tools for detection of progression.”

“The combination of multiple sources of imaging with AI is likely to improve our detection of change in the near future.”

i American Journal of Ophthalmology, 2017; 182: 107–117. ii JAMA Opthalmology. Online Feb 24, 2022. doi:10.1001/jamaophthalmol.2021.6433 iii Expert Review of Molecular Diagnostics, 2020 Jul 1; 20(7): 737–748.

Felipe A Medeiros MD, PhD is Joseph Wadsworth Distinguished Professor of Ophthalmology, professor of electrical and computer engineering, professor of biostatistics and bioinformatics, and vice-chair (technology) at Duke University, Durham, North Carolina, USA. felipe.medeiros@duke.edu