AI Driven National Platform for CT cOronary Angiography for clinicaL and industriaL applicatiOns Registry (APOLLO)

Singapore Health Services (SingHealth)

Status: Enrolling

Conditions: Coronary Artery Disease; CAD; Plaques; Epicardial; Coronary Stenosis

Treatments: Procedure: CTCA

Study type: Observational

Funder types: Other

Identifiers

NCT05509010

APOLLO

Details and patient eligibility

About

The overall aim is to build an AI driven national Platform for CT cOronary angiography for clinicaL and industriaL applicatiOns (APOLLO) for automated anonymization, reporting, Agatston scoring and plaque quantification in CAD. It is a "one-stop" platform spanning diagnosis to clinical management and prognosis, and aid in predicting pharmacotherapy response.

Full description

Coronary artery disease (CAD), a blockage of the blood vessels, affects 6% of the general population and up to 20% of those over 65 years of age. CAD is a leading cause of cardiac mortality in Singapore and worldwide, with 19% of deaths in Singapore due to CAD (MOH website).

Numbers of CAD cases are increasing due to ageing and the higher prevalence of contributary diseases such as diabetes. Computed Tomography Coronary Angiography (CTCA) is the first-line investigation for CAD as indicated by the National Institute for Clinical Excellence (NICE) guidelines. Recent Prospective Multicenter Imaging Study for Evaluation of Chest Pain (PROMISE) and Scottish Computed Tomography of the Heart (SCOT-HEART) trials support CTCA as the dominant means for evaluating coronary anatomy and physiology as it increases diagnostic certainty, improves efficiency of triage to invasive catheterization and reduces radiation exposure when compared to functional stress testing.

Currently, CAD report generation requires 3-6 hours of a CT specialist's time to annotate scans, with inter-observer variability of 20%. In addition, there is no effective singular toolkit to analyse Agatston scores (a measure of calcified CAD), severity of stenosis, and plaque characterisation.

These problems have severely constrained the effectiveness of CTCA as a diagnostic and research tool. The investigators plan to build upon Singapore's competitive advantages in artificial intelligence (AI) to provide a solution to these gaps.

Enrollment: 8,000 estimated patients

Sex: All

Ages: 21 to 80 years old

Volunteers: No Healthy Volunteers

Inclusion criteria

1. Age ≥21 years old
2. Signed informed consent
3. Clinically indicated for evaluation by CTCA

Exclusion criteria

1. Individuals unable to provide informed consent
2. Known complex congenital heart disease
3. Planned invasive angiography for reasons other than CAD
4. Non-cardiac illness with life expectancy < 2 years
5. Pregnancy
6. Concomitant participation in another clinical trial in which subject is subject to investigational drug or device
7. Cardiac event and/or coronary revascularization (percutaneous coronary intervention (PCI) and/or coronary artery bypass grafting (CABG) and/or valvular repair/replacement prior to CTCA
8. Glomerular Filtration Rate ≤ 30mL/min
9. Known allergy to iodinated contrast agent
10. Contraindications to beta blockers or nitroglycerin or adenosine

Trial design

8,000 participants in 2 patient groups

Retrospective

Description:

4000 patients who were clinically evaluated by CTCA from 1 Jan 2007 to 31 Oct 2017.

Treatment:

Procedure: CTCA

Prospective

Description:

4000 patients who are clinically evaluated by CTCA.

Treatment:

Procedure: CTCA