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NCT Number: NCT07628088

AI-THEROSCOPE: AI Detection of Subclinical Atherosclerosis From Retinal Images

Cardiovascular risk scores are widely used for risk stratification but may fail to identify a substantial proportion of individuals with subclinical atherosclerosis who are at increased risk of future cardiovascular events. Vascular ultrasound can directly detect carotid and femoral atherosclerotic plaques but its implementation is limited by the need for trained operators and expert interpretation. The AI-THEROSCOPE study aims to develop and validate an artificial intelligence-based tool capable of detecting subclinical atherosclerosis through the analysis of non-mydriatic retinal fundus images. Participants undergo clinical assessment, laboratory testing, carotid and femoral ultrasound, and retinal fundus photography. The performance of the AI model will be evaluated against vascular ultrasound findings as the reference standard for the presence of subclinical atherosclerosis.

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This study is active but is not currently recruiting participants.

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Key information

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Hospital Universitario Infanta Leonor

Madrid, 28031, Spain

About this study

Cardiovascular disease remains the leading cause of mortality worldwide. Current cardiovascular risk prediction models are useful for population-level risk estimation but may underestimate risk in a substantial proportion of individuals who already have subclinical atherosclerosis. Vascular ultrasound of the carotid and femoral arteries allows direct visualization of atherosclerotic plaques and improves cardiovascular risk stratification, but its widespread use is limited by the requirement for specialized equipment and trained personnel.

Retinal fundus imaging provides a non-invasive assessment of the microvasculature and has emerged as a promising tool for cardiovascular risk evaluation. Recent advances in artificial intelligence and deep learning have demonstrated the ability of retinal image analysis to identify cardiovascular risk factors and predict cardiovascular outcomes.

The AI-THEROSCOPE study is a prospective observational study designed to develop and validate an artificial intelligence model for the detection of subclinical atherosclerosis using non-mydriatic retinal fundus photographs. Adult participants without previous cardiovascular disease undergo standardized clinical evaluation, laboratory testing, carotid and femoral vascular ultrasound, and bilateral retinal fundus photography.

The presence of carotid and/or femoral atherosclerotic plaque assessed by vascular ultrasound serves as the reference standard. Deep learning techniques will be used to train and validate predictive models based on retinal images. Model performance will be evaluated using discrimination metrics including the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, positive predictive value, and negative predictive value.

The ultimate objective of the project is to develop a scalable, non-invasive, and easily deployable tool that may facilitate early detection of subclinical atherosclerosis and improve cardiovascular risk stratification in clinical practice and population screening programs.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Adults aged 18 years or older.
  • No previous established cardiovascular disease.
  • Undergoing cardiovascular risk assessment and carotid and femoral vascular ultrasound.
  • Ability to provide written informed consent.

Exclusion criteria

  • Previous acute coronary syndrome, stroke, or peripheral arterial disease.
  • Previous carotid or femoral vascular surgery or stenting.
  • Previous ophthalmologic surgery.
  • Retinal or ocular diseases that significantly affect retinal vasculature or image quality, including moderate or severe diabetic retinopathy, retinal vascular occlusion, advanced hypertensive retinopathy, exudative age-related macular degeneration, or macular edema.
  • Inability or unwillingness to provide informed consent.

Treatment and study plan

Primary outcomes

  1. Area Under the Receiver Operating Characteristic Curve (AUC) for Detection of Subclinical Atherosclerosis

    Time frame: Baseline

    Diagnostic performance of the artificial intelligence model based on non-mydriatic retinal fundus images for detecting carotid and/or femoral atherosclerotic plaques, using vascular ultrasound as the reference standard.

Sponsors and collaborators

Lead sponsor

Infanta Leonor University Hospital

Other

Registry information

Official study title

Development and Validation of an AI-Based Tool to Detect Subclinical Atherosclerosis Using Non-Mydriatic Retinal Fundus Images: The AI-THEROSCOPE Project

Acronym: Atheroscope

Important dates

Study start
2023
Primary completion
2026
Study completion
2028
First posted
Jun 4, 2026
Registry last updated
Jun 10, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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