Future glaucoma diagnostics
Current research foreshadows future technologies for glaucoma diagnosis. Roibeard Ó hÉineacháin reports
The next 40 years are likely to see advances in the diagnosis of glaucoma using technologies that are now in their infancy, said Prof David F. Garway-Heath MD, FRCOphth, Moorfields Eye Hospital and Glaucoma UK Professor of Ophthalmology, University College London, London, England.
“The future is exciting, with advances in miniaturisation and mobile technology, advances in perimetry and imaging, machine learning to better interpret the data from these devices, and also in developing biomarkers to identify patients who have glaucoma or who are more susceptible to glaucoma,” Prof Garway-Heath told the 14th European Glaucoma Society Congress.
He noted that records going back 30 years show a consistent pattern of a portion of glaucoma cases being missed until they are at a late stage of disease, demonstrating the need for better case-finding technologies. The case-finding approaches now under investigation include innovations in both structural and functional measurements.
For example, perimetry is likely to improve because research has shown that modulating the size of stimuli used in perimetry devices can increase the specificity of the devices in identifying glaucoma and reduce the need for re-testing. One new means of measuring functional changes now being tested is the recording of patients’ gazing patterns, for which glaucoma patients have characteristic differences compared to those with healthy eyes.
There is also a new portable hand-held binocular OCT device that is now undergoing trials at Moorfields and other centres. The current advances in software processing for imaging devices are also likely to continue, enabling the visualisation of the optic nerve in exquisite detail. The coming decades are also likely to see more precision in the correlation between structural changes in the optic nerve and functional changes in glaucoma. In addition, there is now a camera attachment for mobile phones which allow imaging of the fundus.
“Combined with machine learning and artificial intelligence it may be possible to identify obvious glaucoma in individuals with simple imaging with mobile phones in the future,” Prof Garway-Heath said.
Other approaches include the use of biomarkers, that might enable the detection of glaucoma with a blood-test. Frans Grus MD and his associates in Mainz Germany have shown that it is possible to identify glaucoma patients based on their antibody profile with high sensitivity and specificity. Other biomarker strategies under development include new means of detecting mitochondrial dysfunction as a biomarker for glaucoma susceptibility, and metabolic imaging, with two-photon imaging with an ultrafast pulsing laser which can target particular molecules in the retina, Prof Garway-Heath said.