Using AI to improve diagnostic testing for coronary artery disease
Coronary Computed Tomographic Angiography to Optimize Diagnostic Yield of Invasive Angiography for Low-risk Patients Screened With Artificial Intelligence
This study is testing if using artificial intelligence can help doctors decide which patients with suspected coronary artery disease should have a less invasive heart scan instead of a more risky procedure.
Quick facts
| Phase | Not applicable |
|---|---|
| Study type | Interventional |
| Enrollment | 252 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | Hamilton Health Sciences Corporation Academic / other |
| Locations | 3 sites (Hamilton, Ontario and 2 other locations) |
| Trial ID | NCT06648239 on ClinicalTrials.gov |
What this trial studies
This study aims to enhance the diagnostic yield of invasive coronary angiography (ICA) by utilizing artificial intelligence (AI) to determine which patients should undergo non-invasive coronary computed tomographic angiography (CCTA) instead. By screening patients referred for elective ICA, the study seeks to identify those who are more likely to benefit from CCTA, thereby reducing unnecessary invasive procedures and associated risks. The approach focuses on optimizing patient outcomes while minimizing costs and complications related to ICA. The study will involve a centralized triage system that employs risk scoring to guide the decision-making process.
Who should consider this trial
Good fit: Ideal candidates for this study are adults aged 18 and older who are referred for non-urgent outpatient invasive coronary angiography with specific indications.
Not a fit: Patients who have had a recent high-quality CCTA, severe renal dysfunction, or a history of significant coronary artery disease may not benefit from this study.
Why it matters
Potential benefit: If successful, this approach could lead to more accurate diagnoses and safer, more cost-effective care for patients with coronary artery disease.
How similar studies have performed: Other studies have shown promise in using AI for diagnostic purposes in cardiology, suggesting that this approach may be effective.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria Patients are eligible if they: 1. are ≥18 years of age; 2. are referred for non-urgent (elective) outpatient ICA; 3. have an indication for ICA that includes 'Rule out CAD', 'Cardiomyopathy', or 'Stable CAD'; and 4. are able to provide informed consent in English. Exclusion Criteria Patients are ineligible if they have: 1. received a prior high-quality coronary computed tomographic angiography (CCTA) within the last 5 years; 2. atrial fibrillation; 3. known severe renal dysfunction (GFR \<35); 4. planned non-coronary cardiac surgery; 5. any prior obstructive CAD, acute coronary syndrome, percutaneous coronary intervention, or coronary artery bypass graft; or 6. known severe coronary artery calcification (calcium score \>1000).
Where this trial is running
Hamilton, Ontario and 2 other locations
- Hamilton General Hospital — Hamilton, Ontario, Canada (Recruiting)
- McMaster University Medical Centre — Hamilton, Ontario, Canada (Not_yet_recruiting)
- St. Catharines Hospital — St. Catharines, Ontario, Canada (Not_yet_recruiting)
Study contacts
- Principal investigator: Jon-David Schwalm, MD, MSc — Hamilton Health Sciences Corporation
- Study coordinator: Jeremy Petch, PhD
- Email: petchj@HHSC.CA
- Phone: 416-476-9039
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.