Pupillometric recordings to detect glaucoma

Area of Science:

• Ophthalmology
• Biomedical Engineering
• Signal Processing

Background:

• Glaucoma is a leading cause of irreversible vision loss.
• Early diagnosis of glaucoma is crucial for effective treatment and better prognosis.
• Current diagnostic methods can be invasive or require specialized equipment.

Purpose of the Study:

• To investigate the potential of hippus (steady-state pupil oscillations) for computerized glaucoma detection.
• To evaluate the efficacy of using eye-tracking technology to measure pupillary oscillations.
• To determine if entropy analysis of hippus can differentiate between glaucoma patients and healthy controls.

Main Methods:

• Pupillary data were collected using a commercial eye-tracker.
• A cohort of 40 glaucoma patients and 30 age-matched controls participated.
• De-noised pupillary signals were analyzed for entropy at two light intensities (34 and 100 cd m⁻²).

Main Results:

• Significant differences in sample entropy of hippus were observed between glaucoma and healthy eyes at 100 cd m⁻² (p < 0.05).
• The entropy values were 0.55 ± 0.017 for healthy eyes and 0.7 ± 0.034 for glaucoma eyes at 100 cd m⁻².
• Significant differences were also found at 34 cd m⁻², albeit to a lesser extent.

Conclusions:

• The entropy of pupillary oscillations (hippus) measured via eye-tracking is a significant differentiator between glaucoma and healthy eyes.
• This non-invasive method utilizes inexpensive, commercially available hardware.
• The findings suggest a potential for widespread deployment in computerized glaucoma screening programs.