Detection of Systemic Diseases From Ocular Images Using Artificial Intelligence: A Systematic Review

Abstract

Purpose: Despite the huge investment in health care, there is still a lack of precise and easily accessible screening systems. With proven associations to many systemic diseases, the eye could potentially provide a credible perspective as a novel screening tool. This systematic review aims to summarize the current applications of ocular image–based artificial intelligence on the detection of systemic diseases and suggest future trends for systemic disease screening. Methods: A systematic search was conducted on September 1, 2021, using 3 databases—PubMed, Google Scholar, and Web of Science library. Date restrictions were not imposed and search terms covering ocular images, systemic diseases, and artificial intelligence aspects were used. Results: Thirty-three papers were included in this systematic review. A spectrum of target diseases was observed, and this included but was not limited to cardio-cerebrovascular diseases, central nervous system diseases, renal dysfunctions, and hepatological diseases. Additionally, one- third of the papers included risk factor predictions for the respective systemic diseases. Conclusions: Ocular image – based artificial intelligence possesses potential diagnostic power to screen various systemic diseases and has also demonstrated the ability to detect Alzheimer and chronic kidney diseases at early stages. Further research is needed to validate these models for real-world implementation.

The Eye Is a Window to Systemic and Neuro-Ophthalmic Diseases

“…Lee et al 11 noted that DL helped identify a strong association between neurofibrillary tangles and development of dementia in patients with significant amyloid plaques from neuropathology specimens. Additional systemic disease associations are discussed further by Peng et al 12 in this special issue. It may be that AI will help elucidate similar findings from the ophthalmologic examination that might predict which patients are at future risk of cognitive impairment from Alzheimer disease.…”

Predicting cerebral small vessel disease through retinal scans and demographic data with Bayesian feature selection

“…6 With the development of examination methods such as fundus photography and optical coherence tomography (OCT), an increasing number of studies have shown that abnormal changes in the retina and fundus blood vessels can reflect systemic diseases and are applied to the diagnosis of systemic diseases. 7 The fundus image is obtained by imaging the patient's fundus with a fundus camera, capturing common structures such as the optic disc, macula, and blood vessels. Recently, structural analysis of these vessels in fundus images has been employed in diagnosing clinical diseases such as myocardial infarction, 8 stroke 9 and chronic kidney disease.…”

Evaluating imaging repeatability of fully self-service fundus photography within a community-based eye disease screening setting

“…Fundus imaging stands as a fundamental screening approach, providing insight into ocular conditions and systemic diseases [9]. The implementation of remote ophthalmic care and the development of artificial intelligence (AI)-assisted software greatly depend on digitalized fundus images [10][11][12].…”