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Completed

NCT Number: NCT06648239

CCTA to Optimize Diagnostic Yield of Invasive Angiography With AI

Coronary artery disease (CAD) is a leading cause of death. The gold-standard test used to diagnose CAD is invasive coronary angiography (ICA). However, nearly half the patients who receive ICA are found to have no disease or non-significant disease. This means that while they receive a diagnosis, they do not receive any therapeutic benefit. This is concerning because ICA is expensive and it carries a risk to patients. A non-invasive diagnostic test, cardiac computed tomographic angiography (CCTA), has been shown to be as effective as ICA at diagnosing CAD in the right patient population, while being less expensive and less risky for patients. An optimal solution would involve screening to identify which patients are good candidates for CCTA vs. which should receive ICA. This screening tool could be used in a triage pathway to ensure that every patient gets the test that is best for them. The investigators have used Artificial Intelligence (AI) to develop a model for determining which patients should receive ICA vs. which should receive CCTA. The investigators have also developed a triage pathway to direct patients to the most appropriate test. The investigators now plan to evaluate the AI tool combined with the triage pathway through a clinical trial at Hamilton Health Sciences and Niagara Health. This model of care will reduce risk to patients, reduce wait times for ICA and reduce costs to the health care system.

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Key information

Conditions

Coronary Artery Disease Arterial Occlusive Diseases Arteriosclerosis Cardiovascular Diseases Coronary Disease Heart Diseases Myocardial Ischemia Vascular Diseases

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Hamilton General Hospital, Hamilton, Ontario, Canada

Loading trial locations.

Who can participate

Healthy volunteers accepted: Yes

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

Patients are eligible to participate 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. Patients fulfilling any of the following criteria will be ineligible to participate: 1) 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; 6) known severe coronary artery calcification (calcium score >250); or have a body mass index (BMI) exceeding 40.

Treatment and study plan

Usual Care

Other

In the usual care group, patients will proceed directly to ICA following referral from community cardiology, as is the current standard of care. Research staff will screen participants in this group for significant CAD using the decision support tool; however, the tool's recommendations will not affect their care, as all patients in this group will invariably receive ICA.

Centralized triage with risk score-based screening for obstructive CAD

Other

Patients randomized to the intervention will have selected features of their medical history, recorded on their referral form, entered into a decision support tool by research personnel to generate a recommendation of whether they should proceed directly to ICA or whether they should receive CCTA. Patients with recommendations for ICA will proceed directly to ICA. Patients with recommendations for CCTA will be referred to CCTA. Based on the results of the CCTA, recommendations for medical management versus referral for ICA will be made.

Primary outcomes

  1. Rate of normal/non-obstructive CAD diagnosed through ICA

    Time frame: 90 days (after randomization)

    The rate of normal or non-obstructive CAD diagnosed through ICA in patients referred for cardiac investigation. The rate for an arm (control vs experimental) is calculated by dividing the number of patients diagnosed with normal/non-obstructive CAD through ICA by the total patients allocated to the arm.

Secondary outcomes

  1. Quantitative assessment of number of angiograms avoided

    Time frame: 90 days (after randomization)

    Number of angiograms avoided due to CCTA bookings.

  2. Deviation from management recommendations following CCTA (i.e. angiograms performed when not recommended)

    Time frame: 90 days (after randomization)

    Number of angiograms performed when not recommended.

  3. Diagnostic yield of invasive angiography

    Time frame: 90 days (after randomization)

    Diagnostic yield is defined as the proportion of invasive angiograms that identify significant disease (≥70% stenosis) on a major coronary vessel (>2 mm) or >50% stenosis in the left main).

  4. Sex differences in rate of normal/non-obstructive CAD diagnosed through ICA

    Time frame: 90 days (after randomization)

    Difference in the rate of normal/non-obstructive CAD diagnosed through ICA between males and females.

  5. Site differences in rate of normal/non-obstructive CAD diagnosed through ICA

    Time frame: 90 days (after randomization)

    Difference in the rate of normal/non-obstructive CAD diagnosed through ICA between sites.

  6. Budget impact of new strategy for risk stratification of CAD in low-risk patients

    Time frame: 90 days (after randomization)

    Cost of risk stratification of CAD in low risk patients.

  7. Number of low-quality CCTAs

    Time frame: 90 days (after randomization)

    The quality will be graded on a per-patient basis using a three-class system: low quality, denoting an image in which the coronary anatomy cannot be clearly defined, requiring ICA within 90 days for clarification; suboptimal quality, denoting an image in which the coronary anatomy was equivocal for one or more non-prognostic vessels but not requiring ICA based on CCTA findings and clinical presentation; and high quality, denoting an image in which the coronary anatomy could be clearly defined.

Sponsors and collaborators

Lead sponsor

Hamilton Health Sciences Corporation

Other

Collaborators

  • Hamilton Academic Health Sciences Organization
  • Population Health Research Institute

Registry information

Official study title

Coronary Computed Tomographic Angiography to Optimize Diagnostic Yield of Invasive Angiography for Low-risk Patients Screened With Artificial Intelligence

Acronym: CarDIA-AI

Important dates

Study start
2025
Primary completion
2026
Study completion
2026
First posted
Oct 18, 2024
Registry last updated
May 11, 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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