Predicting outcomes from coronary OCT images with AI
Optical Coherence Tomography: Prognostic Value and Artificial Intelligence
Radboud University Medical Center · NCT07293858
This project will try to see if details from coronary OCT scans and an AI tool can predict long-term outcomes in people with coronary artery disease.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 1000 (estimated) |
| Sex | All |
| Sponsor | Radboud University Medical Center (other) |
| Locations | 1 site (Nijmegen, Gelderland) |
| Trial ID | NCT07293858 on ClinicalTrials.gov |
What this trial studies
This prospective registry enrolls consecutive patients who undergo intracoronary optical coherence tomography (OCT) as part of routine cardiac catheterization at Radboudumc and participating centers. High-resolution OCT pullbacks and clinical data are collected, and patients are followed for up to 10 years using medical records, questionnaires, and national registries to capture symptoms, medications, hospitalizations, procedures, and major cardiac events. The study will test whether OCT-derived plaque morphology, vulnerable features, or indicators of stent optimization are associated with long-term clinical outcomes. Pseudonymized OCT images will also be used to develop and train an AI algorithm for automated OCT annotation.
Who should consider this trial
Good fit: Ideal candidates are adults with coronary artery disease who undergo intracoronary OCT during routine catheterization at Radboud University Medical Center or a participating site and can provide written informed consent.
Not a fit: Patients who do not undergo OCT, cannot provide informed consent, or cannot be followed (for example lacking valid contact details) are unlikely to benefit from this registry's findings.
Why it matters
Potential benefit: If successful, this work could help clinicians better predict individual risk after coronary imaging and speed up OCT interpretation with AI, potentially informing treatment decisions.
How similar studies have performed: Previous studies have linked certain OCT features to adverse outcomes and early AI tools for OCT annotation have shown promise, but large-scale, long-term validation is still limited.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * All consecutive patients undergoing intracoronary OCT imaging at the Radboud University Medical Center, and any additional centers that may join the study in the future. * OCT performed at the discretion of the treating physician, according to contemporary clinical guidelines. * Written informed consent obtained after the procedure. Exclusion Criteria: * Patients who decline or are unable to provide informed consent. (Only patients who provide consent can be included. * Patients for whom follow-up or data collection is not feasible (e.g., no valid contact details).
Where this trial is running
Nijmegen, Gelderland
- Radboudumc — Nijmegen, Gelderland, Netherlands (RECRUITING)
Study contacts
- Study coordinator: Joske L. van der Zande
- Email: joske.vanderzande@radboudumc.nl
- Phone: 0622997212
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.
Conditions: Coronary Arterial Disease, Optical Coherence Tomography, Artificial Intelligence