Good news! Will we soon have affordable, easy, and regular health checkups based on retina scans? Will we have a smartphone app for that?
"A team of researchers in the UK has developed a fully automated artificial intelligence-enabled system that can scan retinal images for vascular health, helping identify those at high risk of heart disease and stroke.
The old adage "the eyes are windows to the soul" isn’t that far off when considering how much one can infer about a person’s general health by studying their eyes. Diseases such as rheumatoid arthritis and hyperthyroidism can be detected in the eyes, and recent innovations suggest neurodegenerative diseases like Alzheimer’s and Parkinson’s could be diagnosable through retinal scanning. ...
The AI system is dubbed QUARTZ ((QUantitative Analysis of Retinal vessels Topology and siZe) and a new study put the algorithm to the test on more than 88,000 retinal images from two large ongoing population health studies. ...
The results showed the AI-driven system (when incorporated with age, sex, smoking status and medical history) could deliver 10-year risk scores for stroke and heart disease equal to one of the most commonly used diagnostic tools called the Framingham Risk Score (FRS). Because FRS diagnostics require blood tests and blood pressure measurement, the ease of an automated eye-scanning technique reaching similar conclusions would mean more people could be better monitored if the technology was widely deployed. ..."
The old adage "the eyes are windows to the soul" isn’t that far off when considering how much one can infer about a person’s general health by studying their eyes. Diseases such as rheumatoid arthritis and hyperthyroidism can be detected in the eyes, and recent innovations suggest neurodegenerative diseases like Alzheimer’s and Parkinson’s could be diagnosable through retinal scanning. ...
The AI system is dubbed QUARTZ ((QUantitative Analysis of Retinal vessels Topology and siZe) and a new study put the algorithm to the test on more than 88,000 retinal images from two large ongoing population health studies. ...
The results showed the AI-driven system (when incorporated with age, sex, smoking status and medical history) could deliver 10-year risk scores for stroke and heart disease equal to one of the most commonly used diagnostic tools called the Framingham Risk Score (FRS). Because FRS diagnostics require blood tests and blood pressure measurement, the ease of an automated eye-scanning technique reaching similar conclusions would mean more people could be better monitored if the technology was widely deployed. ..."
From the abstract:
"Aims
We examine whether inclusion of artificial intelligence (AI)-enabled retinal vasculometry (RV) improves existing risk algorithms for incident stroke, myocardial infarction (MI) and circulatory mortality.
We examine whether inclusion of artificial intelligence (AI)-enabled retinal vasculometry (RV) improves existing risk algorithms for incident stroke, myocardial infarction (MI) and circulatory mortality.
Methods
AI-enabled retinal vessel image analysis processed images from 88 052 UK Biobank (UKB) participants (aged 40–69 years at image capture) and 7411 European Prospective Investigation into Cancer (EPIC)-Norfolk participants (aged 48–92). Retinal arteriolar and venular width, tortuosity and area were extracted. Prediction models were developed in UKB using multivariable Cox proportional hazards regression for circulatory mortality, incident stroke and MI, and externally validated in EPIC-Norfolk. Model performance was assessed using optimism adjusted calibration, C-statistics and R2 statistics. Performance of Framingham risk scores (FRS) for incident stroke and incident MI, with addition of RV to FRS, were compared with a simpler model based on RV, age, smoking status and medical history (antihypertensive/cholesterol lowering medication, diabetes, prevalent stroke/MI).
AI-enabled retinal vessel image analysis processed images from 88 052 UK Biobank (UKB) participants (aged 40–69 years at image capture) and 7411 European Prospective Investigation into Cancer (EPIC)-Norfolk participants (aged 48–92). Retinal arteriolar and venular width, tortuosity and area were extracted. Prediction models were developed in UKB using multivariable Cox proportional hazards regression for circulatory mortality, incident stroke and MI, and externally validated in EPIC-Norfolk. Model performance was assessed using optimism adjusted calibration, C-statistics and R2 statistics. Performance of Framingham risk scores (FRS) for incident stroke and incident MI, with addition of RV to FRS, were compared with a simpler model based on RV, age, smoking status and medical history (antihypertensive/cholesterol lowering medication, diabetes, prevalent stroke/MI).
Results
UKB prognostic models were developed on 65 144 participants (mean age 56.8; median follow-up 7.7 years) and validated in 5862 EPIC-Norfolk participants (67.6, 9.1 years, respectively). Prediction models for circulatory mortality in men and women had optimism adjusted C-statistics and R2 statistics between 0.75–0.77 and 0.33–0.44, respectively. For incident stroke and MI, addition of RV to FRS did not improve model performance in either cohort. However, the simpler RV model performed equally or better than FRS.
UKB prognostic models were developed on 65 144 participants (mean age 56.8; median follow-up 7.7 years) and validated in 5862 EPIC-Norfolk participants (67.6, 9.1 years, respectively). Prediction models for circulatory mortality in men and women had optimism adjusted C-statistics and R2 statistics between 0.75–0.77 and 0.33–0.44, respectively. For incident stroke and MI, addition of RV to FRS did not improve model performance in either cohort. However, the simpler RV model performed equally or better than FRS.
Conclusion
RV offers an alternative predictive biomarker to traditional risk-scores for vascular health, without the need for blood sampling or blood pressure measurement. Further work is needed to examine RV in population screening to triage individuals at high-risk."
RV offers an alternative predictive biomarker to traditional risk-scores for vascular health, without the need for blood sampling or blood pressure measurement. Further work is needed to examine RV in population screening to triage individuals at high-risk."
Artificial intelligence-enabled retinal vasculometry for prediction of circulatory mortality, myocardial infarction and stroke (open access)
Figure 1 Fully automated retinal image processing of the vascular tree using artificial intelligence-enabled QUARTZ software.
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