AI-enabled eye scan delivers stroke and heart disease risk scores

AI-enabled eye scan delivers stroke and heart disease risk scores

AI-enabled eye scan

A team of UK researchers has developed an innovative fully automated artificial intelligence (AI) system, named QUARTZ (Quantitative Analysis of Retinal vessels Topology and size), designed to scan retinal images for vascular health. This technology aims to identify individuals at a higher risk of heart disease and stroke by analyzing retinal vasculature. The eyes have long been recognized as potential indicators of overall health, with certain diseases and conditions manifesting in ocular features.

AI-enabled eye scan

Retinal scans have been studied for their potential to reveal information about various health conditions, including cardiovascular changes related to diseases such as diabetes and coronary artery disease. The AI system QUARTZ was subjected to testing using more than 88,000 retinal images from two extensive population health studies. Each participant had seven to nine years of follow-up data, allowing researchers to assess the system’s predictive capabilities.

The study’s results indicated that when combined with factors like age, sex, smoking status, and medical history, the AI-driven system could provide 10-year risk scores for stroke and heart disease comparable to those generated by one of the most widely used diagnostic tools, the Framingham Risk Score (FRS). Unlike traditional FRS diagnostics, which require blood tests and blood pressure measurements, the automated eye-scanning technique offers the potential for widespread monitoring with ease if widely adopted.

AI-enabled eye scan

While the majority of retinal images analyzed in the study were captured by non-expert personnel, the researchers suggested that employing better imaging techniques by healthcare professionals could further enhance the results. However, the simplicity of less-complex retinal imaging also opens up the possibility of incorporating this technology into smartphone apps.

An accompanying commentary by two University of Dundee researchers not involved in the study discussed the clinical implications of this diagnostic tool. They emphasized the need for collaborative efforts among ophthalmologists, cardiologists, primary care physicians, and computer scientists to design studies determining the impact of using this information on clinical outcomes. Questions regarding whether the tools should be restricted to specific medical professionals, the necessary clinical follow-ups for high-risk patients, and the potential influx of patients seeking consultation based on smartphone app results need careful consideration.

AI-enabled eye scan

In conclusion, further collaborative research and discussions involving regulatory bodies, scientific societies, and healthcare systems are crucial for optimizing clinical workflows and facilitating the practical implementation of this technology in routine practice.

AI-enabled eye scan The new research was published in the British Journal of Ophthalmology.

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