AI out performs humans in glaucoma screening

Artificial Intelligence (AI) utilizes the latest cutting technology to identify human diseases.

Screening for glaucoma remains challenging due to the myriad presentations of the condition. Presently, screening is regarded as economically and practically unfeasible.

However, studies are being performed to investigate the possibility of using AI to screen for glaucoma.

A study presented at the 129th annual meeting of the American Academy of Ophthalmology by Anthony Khwaja and his colleagues from the University of London, Institute of Ophthalmology and Moorefields Eye Hospital, has shown that AI can out-perform humans in screening for glaucoma.

The study used 6,304 fundus images gathered for a large, population-based cohort study (EPIC-Norfolk Eye Study) to compare the accuracy of their algorithm and a trained human grader to estimate a key measure of glaucoma, vertical cup-disc ratio. A glaucoma specialist examined the patients to confirm the diagnosis.

Results showed the algorithm correctly identified patients with glaucoma 88 to 90 percent of the time; human graders were correct 79 to 81 percent of the time. The algorithm did not differentiate between those who had glaucoma or might have glaucoma.

It remains to be seen how a single feature of glaucoma (the vertical C:D R) can be used to diagnose glaucoma patients. This feature is dependent on the ISNT rule and is often seen in only 50% of the population.

URIC ACID AND GLAUCOMA

Uric acid (UA) is a purine metabolite present intracellularly and in all body fluids. Usually high UA levels have been associated with gout and kidney stones.

However, UA has both pro-oxidant and antioxidant features in-vitro by production and scavenging of reactive oxygen species. 

The beneficial impacts of UA have been shown in certain neurodegenerative conditions, such as Parkinson's disease, Huntington's disease, Alzheimer's disease, and amyotrophic lateral sclerosis. However, the role of UA in the underlying mechanism of glaucoma is still unclear.

A meta-analysis was performed by Mohammadi et al, to identify case-control studies comparing the serum UA concentrations of the patients with glaucoma and controls. The mean ± standard division difference was used to assess the difference in serum UA concentrations between the glaucoma patients and controls.

The meta-analysis involved 6 studies involving 1,221 glaucoma patients and 1,342 in the control group.

The pooled analysis included all six studies, showing that serum UA level was higher in glaucoma patients than in other patients without glaucoma. In detail, the meta-analysis using a random effect model indicates that the mean UA level in glaucoma patients was 0.13 (I2 = 91.92%, 95% CI = −0.42 to 0.68) higher than the controls; however, it was not statistically significant.

Three out of six case-control studies within this meta-analysis found a significant inverse association. In comparison, three other studies have reported a positive association between high UA levels and glaucoma.

These findings provide evidence that glaucoma patients have a higher serum UA level compared to the controls, but this difference is not statistically significant. Prospective studies are needed to determine the possible association between increased UA and glaucoma pathogenesis.

REFERENCE:

Mohammadi M, Yarmohammadi A, Salehi-Abargouei A, Ghasemirad H, Shirvani M, Ghoshouni H. Uric acid and glaucoma: a systematic review and meta-analysis. Front Med (Lausanne). 2023 Jul 28;10:1159316. doi: 10.3389/fmed.2023.1159316. PMID: 37575992; PMCID: PMC10422028.

CLOSED EYE IOP AND EM MONITORING

Normally, intraocular pressure (IOP) exhibits a significant circadian rhythm, typically peaking in the early morning hours before the end of sleep (3–4 mmHg higher than daytime levels), with a trough occurring at the end of the day. This phenomenon is closely associated with changes in body position (supine posture increases episcleral venous pressure by 3–6 mmHg) and fluctuations in glucocorticoid levels.

Furthermore, frequent eye movements during sleep, such as those occurring during rapid eye movement (REM) sleep, can increase resistance to aqueous humor outflow. This is particularly concerning in patients with angle-closure glaucoma, where the risk of acute attacks is 3–5 times higher at night compared to during the day.

Smart contact lenses have emerged as a promising solution for continuous, noninvasive ocular signal monitoring instead of discrete measurements.

While Goldman Appalanation Tonography (GAT) is the ideal method, it requires topical anesthesia and fluorescein instillation before measurement, and the fluorescein concentration can influence accuracy. Furthermore, GAT-like instruments often require a slit lamp examination. Corneal thickness, stiffness, and tear film characteristics can also introduce measurement errors. 

Contact lenses are a practical solution to the problems of continuous monitoring. Gan and colleagues have proposed a stretchable self-decoupled BCL comprising electromagnetic capacitive IOP (CIOP) and neodymium-iron-boron (NdFeB)-MEM components. The design features an NdFeB/polydimethylsiloxane (PDMS) interlayer film that separates double-layered serpentine-geometry spiral copper (Cu) films.

This innovation involves a stretchable bimodal contact lens (BCL) amalgamating self-decoupled electromagnetic capacitive intraocular pressure (CIOP) and magnetic eye movement (MEM) monitoring components. This integrated system offers a non-invasive and comfortable solution for real-time eye health monitoring, providing accurate measurements and continuous tracking of eye status. 

In this way, both IOP and EM can be monitored continuously through closed lids.

REFERENCE:

Gan, X., Yao, G., Li, C. et al. Closed-eye intraocular pressure and eye movement monitoring via a stretchable bimodal contact lens. Microsyst Nanoeng 11, 83 (2025). https://doi.org/10.1038/s41378-025-00946-y