Through the eyes into the brain, using artificial intelligence

Abstract

Introduction: Detection of neurological conditions is of high importance in the current context of increasingly ageing populations. Imaging of the retina and the optic nerve head represents a unique opportunity to detect brain diseases, but requires specific human expertise. We review the current outcomes of artificial intelligence (AI) methods applied to retinal imaging for the detection of neurological and neuro-ophthalmic conditions. Method: Current and emerging concepts related to the detection of neurological conditions, using AI-based investigations of the retina in patients with brain disease were examined and summarised. Results: Papilloedema due to intracranial hypertension can be accurately identified with deep learning on standard retinal imaging at a human expert level. Emerging studies suggest that patients with Alzheimer’s disease can be discriminated from cognitively normal individuals, using AI applied to retinal images. Conclusion: Recent AI-based systems dedicated to scalable retinal imaging have opened new perspectives for the detection of brain conditions directly or indirectly affecting retinal structures. However, further validation and implementation studies are required to better understand their potential value in clinical practice. Keywords: Alzheimer’s disease, deep learning, dementia, optic neuropathy, papilloedema

Retinal Alterations Predict Early Prodromal Signs of Neurodegenerative Disease

“…In the future, as previously described for Parkinson's disease, appropriately trained AI will be able to give more information on the probability of developing neurodegenerative pathologies with the investigation of retinal images [255,270,271].…”

The eye as a window to the brain

“…This begs the question: what are the limits of our ability to peer into the eye to inform us of diseases elsewhere in the central nervous system? This question has more relevance today than ever, lending appreciation to the efforts of Sathianvichitr et al and the thrust of the team's work 1 published in this issue of the Annals.…”

“…As part of continuing efforts 7 to find new and useful application of funduscopic examination to diagnose central nervous system diseases, Sathianvichitr et al 1 have reviewed techniques of artificial intelligence (AI) and its application in the tricky world of early diagnosis of AD. Their study delves into the complex world of AD-a world already filled with hundreds of promising hypotheses and brilliant ideas, though without clear immediate application in early diagnosis so far.…”