Future technologies for glaucoma diagnosis
The next 40 years is likely to see advances in the diagnosis of glaucoma using technologies that are now in their infancy
David Garway-Heath MD
The next 40 years is likely to see advances in the diagnosis of glaucoma using technologies that are now in their infancy, said Prof David F. Garway-Heath, UCL NIHR Biomedical Research Centre at Moorfields Eye Hospital and UCL Institute of Ophthalmology.
“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 with glaucoma or 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 cases being missed until they are at a late stage of disease, showing the need for better case-finding. New approaches under investigation in case-finding include the use of technology to measure functional changes through observation of patients’ gaze behaviour, and portable binocular OCT devices. Other approaches include the use of biomarkers, which might enable the detection of glaucoma with a blood-test.
In terms of diagnosis, advances are in progress in the stimuli used in perimetry devices, which may be more specific in identifying glaucoma. The coming decades are also likely to see more precision in the correlation between structural changes and functional changes in glaucoma. The current advances in software processing for imaging devices are also likely to continue, enabling clearer visualisation of changes in the optic nerve head.
Some of the new technologies now for the diagnosis and monitoring of glaucoma include metabolic imaging, with two-photon imaging with an ultrafast pulsing laser that can target particular molecules in the retina, new means of detecting mitochondrial dysfunction as a biomarker for glaucoma susceptibility and many new approaches to visual function testing, such as the use of virtual reality.