Glaucoma is the leading cause of irreversible blindness worldwide, which is characterized by progressive loss of retinal ganglion cells (RGCs) and their optic nerve axons. Early diagnosis and treatment can effectively prevent the progression of the disease and avoid blindness. The damage of RGCs appears in the early stage of glaucoma, and the asymmetry of the eyes has also been observed clinically. CPLRAD may serve as an effective screening tool for glaucomatous optic neuropathy, since they can dynamically detect abnormal pupillary responses from a novel sequence of light stimuli and functionally-shaped stimuli. The current theoretical evidence of relative afferent pupillary defect/pupillary light reflex (RAPD/PLR) as a functional test for predicting nerve damage is insufficient, and pupil detection technology is not yet mature. Therefore, the investigators want to complete these tasks: 1) collect the clinical examination data and objectively measure the pupil dynamic parameters monocularly and/or binocularly as indicators from the retina and optic nerve in glaucoma patients 2) design RAPD/PLR detection technology and develop dynamic analysis system; 3) verify the feasibility of RAPD/PLR applied to early glaucoma screening through clinical trials. The pupil image dynamic analysis and iris recognition system will provide a simple, inexpensive and non-invasive screen tool, and is highly reliable and cost-effective.
To explore an effective diagnostic tool of glaucoma through the dynamic analysis of computerized pupillary light reflex assessment device (CPLRAD) pupillography based on iris recognition techniques and investigate its feasibility in glaucoma screening.