Unlocking the power of the retina

The eyes are not just the window to the soul; they can also tell the story of your overall health. The retina — the innermost, back portion of the eye — is part of the central nervous system and the only place in the human body where veins, arteries, capillaries and nerves can be seen directly and non-invasively.

Your retina is a unique map to your health that reflects your individual biological signature

The retina is as singular and distinctive as the strands of our DNA, and it provides insight into the body's overall well-being. Recent cutting-edge studies have indicated that preliminary indicators of diabetes, hypertension, and a myriad of other health conditions can be detected using retinal imaging. With the aid of advanced machine learning, these images now reveal critical health information, offering personalized maps to health and wellness.

01. DIABETIC RETINOPATHY

Diabetic retinopathy is the leading cause of preventable blindness in American adults

The American Academy of Ophthalmology advises yearly checks for diabetic retinopathy; however, a significant number of individuals, particularly those facing barriers to healthcare access, fail to receive these screenings. Although retinal imaging can readily identify diabetic retinopathy, the condition frequently remains undetected in its initial phases.

1 in 3

individuals living with diabetes will develop diabetic retinopathy.1

40%

of people living with diabetes do not receive recommended screenings.2

50%

of eyes with proliferative diabetic retinopathy will be blind in 5 years if left untreated.3

02. LOOKING TOWARDS THE FUTURE

Peering into health beyond the eye using AI-enhanced ocular imaging

In addition to identifying ocular diseases such as diabetic retinopathy, glaucoma, and macular degeneration, AI-powered retinal scans can also detect a wide range of health conditions affecting various parts of the body.

Cardiovascular health

Algorithms can assess changes in retinal vessel caliber and branching patterns, which correlate with hypertension and cardiovascular risks.

Neurological conditions

AI can detect signs in the retina associated with major neurological conditions, such as nerve fiber layer thinning in Alzheimer's or microvascular alterations in Parkinson’s and Multiple Sclerosis.

Obesity

Retinal imaging can reveal signs of obesity-related eye changes, such as thickening of retinal vessels, offering a novel way to monitor metabolic health.

Inflammatory conditions

By identifying characteristic patterns of inflammation, AI can use retinal images to suggest the presence of systemic inflammatory conditions like rheumatoid arthritis.

Holistic wellness

AI retinal imaging can analyze the microvasculature and tissue health to provide a holistic view of wellness, detecting signs of general physiological stress, hormonal imbalances, or vitamin deficiencies.

Systemic diseases

AI retinal imaging can act as a barometer for systemic diseases like lupus or sickle cell anemia, which often manifest with specific retinal changes.

Infectious diseases

Certain infectious diseases can lead to unique retinal findings, which AI can identify, such as the cotton wool spots associated with HIV or the chorioretinitis found in congenital toxoplasmosis.

03. VISION OF EQUALITY

Bridging health disparities through AI-enhanced ocular screening

AI's entry into eye screening ushers in a new era of equitable healthcare access. By facilitating mass detection and analysis, it empowers healthcare systems to deliver uniform and improved outcomes, transforming the way we approach disease prevention and wellness.

Revolutionizing early detection
Enhancing diagnostic accuracy
Scaling up population health screening
Reducing healthcare disparities
Reducing cost burdens
Improving patient outcomes
Expanding access to care

Sources:
1. International Diabetes Federation: Diabetes Eye Health.
2. American Academy of Ophthalmology: Diabetic Retinopathy PPP 2019
3. Ferris F. Early photocoagulation in patients with either type I or type II diabetes. Trans Am Ophthalmol Soc. 1996;94:505-37.