Abstract

Being the primary site of degeneration, the optic nerve has always been the focus of structural glaucoma assessment. The technical advancements, mainly of optical coherence tomography (OCT), now allow for a very precise quantification of the optic nerve head and peripapillary retina morphology. By far the most commonly used structural optic nerve parameter is the thickness of the parapapillary retinal nerve fiber, which has great clinical utility but also suffers from significant limitations, mainly in advanced glaucoma. Emerging novel imaging technologies, such as OCT angiography, polarization-sensitive or visible-light OCT and adaptive optics, offer new biomarkers that have the potential to significantly improve structural glaucoma diagnostics. Another great potential lies in the processing of the data already available. Artificial intelligence does not only help increase the reliability of current biomarkers but can also integrate data from various imaging modalities and other clinical measures to increase diagnostic accuracy. And it can, in a more efficient way, draw information from available datasets, such as an OCT scan, compared to the current concept of biomarkers, which only use a fraction of the whole dataset.

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