NCT05509010

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

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

• Status: Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 8,000 (estimated)
• Sponsor: National Heart Centre Singapore · Academic / Other
• Sex: All
• Age: 21 Years – 80 Years
• Healthy volunteers: Not accepted

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.

Conditions

• CAD
• Coronary Artery Disease
• Coronary Stenosis
• Plaques; Epicardial

Interventions

Type	Name	Description
PROCEDURE	CTCA	CTCA is performed as part of routine care procedure.

Timeline

• Start date: 2021-10-01
• Primary completion: 2027-12-01
• Completion: 2027-12-01
• First posted: 2022-08-19
• Last updated: 2022-08-19

Locations

3 sites across 1 country: Singapore