Clinical trial NCT05509010: AI Driven National Platform for CT cOronary Angiography for clinicaL and industriaL applicatiOns Registry
Official title: AI Driven National Platform for CT cOronary Angiography for clinicaL and industriaL applicatiOns Registry (APOLLO)
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: CAD
Coronary Artery Disease
Coronary Stenosis
Plaques; Epicardial
Keywords: CTCA
CT Coronary Angiography
Lead sponsor: National Heart Centre Singapore
Sponsor class: OTHER
Collaborators: name: Agency for Science, Technology and Research
First posted: 2022-08-19
Enrollment: 8000
Sex: ALL
Minimum age (years): 21
Maximum age (years): 80
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: OTHER
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Patients who are clinically evaluated by CTCA

Brief summary: 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.

Detailed 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.

Eligibility criteria: 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

Primary outcomes:
measure: AI precision toolkits: AI stenosis reporting
timeFrame: baseline
measure: AI precision toolkits: Agatston scoring
timeFrame: baseline
measure: AI precision toolkits: Plaque
timeFrame: baseline
measure: AI precision toolkits: EAT analysis
timeFrame: baseline
Secondary outcomes:
measure: AI outcome analysis
timeFrame: one to five years from baseline
measure: AI outcome analysis
timeFrame: one to five years from baseline
measure: AI outcome analysis
timeFrame: one to five years from baseline
Other outcomes:
Locations:
city: Singapore
country: Singapore
facility: National Heart Centre Singapore
city: Singapore
country: Singapore
facility: National University Hospital
city: Singapore
country: Singapore
facility: Tan Tock Seng Hospital
Study officials:
affiliation: National Heart Centre Singapore
name: Liang Zhong
role: PRINCIPAL_INVESTIGATOR
References: