CADAPOLLONCT05509010
AI Driven National Platform for CT cOronary Angiography for clinicaL and industriaL applicatiOns Registry
An observational study of CAD and Coronary Artery Disease, run by National Heart Centre Singapore at 3 sites in Singapore.
Trial 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. Read more about this study
- Who is it for?
- Ages 21 to 80 years
- Conditions the study is for
- CAD, Coronary Artery Disease, Coronary Stenosis
- What is being tested?
- CTCA
- Type of treatment
- Surgery or procedure
- How many people
- 8,000 participants
- Where
- 3 sitesSingapore
- Study dates
- 1 Oct 2021to Dec 2027
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 21 to 80 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Patients who are clinically evaluated by CTCA
Who may be able to join
- Age ≥21 years old
- Signed informed consent
- Clinically indicated for evaluation by CTCA
Who cannot join
- Individuals unable to provide informed consent
- Known complex congenital heart disease
- Planned invasive angiography for reasons other than CAD
- Non-cardiac illness with life expectancy < 2 years
- Pregnancy
- Concomitant participation in another clinical trial in which subject is subject to investigational drug or device
Show all 10Show fewer
- 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
- Glomerular Filtration Rate ≤ 30mL/min
- Known allergy to iodinated contrast agent
- Contraindications to beta blockers or nitroglycerin or adenosine
Trial locations and contacts
3 sites in 1 country. Contact the study team or a site near you to ask about taking part.
Dr Lohendran Baskaran contact
Singapore3 sites, 3 recruiting
- Recruiting
National Heart Centre Singapore
Singapore, 169609
Assoc. Prof Zhong Liang, zhong.liang@nhcs.com.sg
Assoc. Prof Zhong Liang
- Recruiting
National University Hospital
Singapore
Associate Professor Mark Chan, mark_chan@nuhs.edu.sg
Associate Professor Mark Chan
- Recruiting
Tan Tock Seng Hospital
Singapore
Dr Yew Min Sen, min_sen_yew@ttsh.com.sg
Dr Yew Min Sen
About this study
Official title: AI Driven National Platform for CT cOronary Angiography for clinicaL and industriaL applicatiOns Registry (APOLLO)
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.
Read the 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
- Being tested
- CTCA
- Keywords
- CTCA, CT Coronary Angiography
- Medical subject headings
- Coronary Artery Disease, Coronary Stenosis, Plaque, Amyloid
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
CTCAProcedure or surgery
CTCA is performed as part of routine care procedure.
| Study group | Role | What they receive |
|---|---|---|
| Retrospective | 4000 patients who were clinically evaluated by CTCA from 1 Jan 2007 to 31 Oct 2017. Receives: Procedure: CTCA | |
| Prospective | 4000 patients who are clinically evaluated by CTCA. Receives: Procedure: CTCA |
What is being measured
The primary outcome is the main question the study is designed to answer.
AI precision toolkits: AI stenosis reporting
Stenosis reporting: Severity of stenosis and accurate anatomical localization of stenosis.
The significance of a stenosis is determined by visual estimation of the maximal grade of luminal narrowing caused by the plaque. As recommended in SCCT guideline (Leipsic et al., 2014) , coronary stenosis can be graded as minimal, mild, moderate, severe and total occluded separately. Following the guideline, a stenosis will be classified as obstructive and non-obstructive. The location of the stenosis uses the SCCT model (Leipsic et al., 2014)
Measured: baseline
AI precision toolkits: Agatston scoring
Agatston scoring: Agatston scoring of calcified plaque. As recommended in SCCT clinical practical guidelines (Leipsic et al., 2014), Agatston scoring programs generally identify pixels that exceed 130 HU as a level corresponding to calcium on a non-contrast study (Agatston et al., 1990) . The reader needs to identify each lesion discrete calcific focus) in each vessel distribution. The summed score for each vessel is generated by the scoring program based on an area-density (Agatston score) (Agatston et al., 1990) measurement of each calcified focus. The total coronary Agatston score is the sum of all calcified lesions in all coronary beds.
Measured: baseline
AI precision toolkits: Plaque
Plaque analysis: Plaque volume, burden, type and anatomical locations. Coronary segmentation and plaque analysis is performed for segments with diameter ≥1.5 mm. Location of plaque uses the SCCT model (Leipsic et al., 2014). For each plaque, the reader marks its start-and end-points, quantifies plaque area,volume and plaque burden, and specifies its type (non-calcified, calcified, or mixed) (Achenbach et al., 2004) . Additionally, non-calcified plaque can be further divided into low attenuation plaque (LAP). A HU <30 will signify LAP and >30 will signify non-LAP.
Measured: baseline
AI precision toolkits: EAT analysis
EAT analysis: Total volume and anatomical locations. EAT and pericardial adipose tissue (PAT) are metabolically active fat surrounding the coronary artery and the heart, being associated with increased risk of cardiovascular disease (Villasante et al, 2019) . EAT can be quantified on non-contrast CT scans. The annotations on the CT scans are obtained by manually drawing the pericardium first to define the region. EAT is identified using the adipose tissue attenuation references between -190 and -30 HU (Oikonomou et al., 2018) . Due to the CT scan noise and changing of attenuation, the HU value of fat can vary, so the final EAT region is verified by an experienced radiologist or cardiologist.
Measured: baseline
Secondary outcomes (3)
AI outcome analysis
- Mortality (All-cause and/or cardiovascular)
Measured: one to five years from baseline
AI outcome analysis
Major-adverse cardiovascular events (myocardial infarction, stroke, heart failure, revascularisation, arrhythmias, etc)
Measured: one to five years from baseline
AI outcome analysis
Re-hospitalisation
Measured: one to five years from baseline
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted19 Aug 2022
- Study start1 Oct 2021
- Primary completionDec 2027 (estimated)
- Study completionDec 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (3)Papers the sponsor has linked to this study.
- Other trials for CADStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Other
- Enrolment
- 8,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- National Heart Centre Singapore
- Sponsor type
- University, hospital or other
- Collaborators
- Agency for Science, Technology and Research
- Responsible party
- Sponsor
- Investigators
- Liang Zhong, Principal investigator, National Heart Centre Singapore
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05509010
- Sponsor's protocol ID
- APOLLO
- Acronym
- APOLLO
- Status last verified
- Aug 2022
- First submitted
- 19 Apr 2022
- Last updated
- 19 Aug 2022
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Leng S, Cheng N, Tan E, Baskaran L, Teo L, Yew MS, Ngiam KY, Huang W, Chai P, Ong CC, Sia CH, Singh M, Loong YT, Raffiee NAS, Wang X, Allen J, Tan SY, Chan M, Lee HK, Zhong L. Deep learning-based quantification of epicardial adipose tissue volume from non-contrast computed tomography images: a multi-centre study. Eur Heart J Digit Health. 2025 Oct 13;6(6):1223-1233. doi: 10.1093/ehjdh/ztaf116. eCollection 2025 Nov.
PubMed 41267847Baskaran L, Leng S, Dutta U, Teo L, Yew MS, Sia CH, Chew NW, Huang W, Lee HK, Vaughan R, Ngiam KY, Lu Z, Wang X, Tan EWP, Cheng NZY, Tan SY, Chan MY, Zhong L; APOLLO investigators. Cohort profile: AI-driven national Platform for CCTA for clinicaL and industriaL applicatiOns (APOLLO). BMJ Open. 2024 Dec 2;14(12):e089047. doi: 10.1136/bmjopen-2024-089047.
PubMed 39622571Wang X, Leng S, Lu Z, Huang S, Lee BH, Baskaran L, Yew MS, Teo L, Chan MY, Ngiam KY, Lee HK, Zhong L, Huang W. Context-aware deep network for coronary artery stenosis classification in coronary CT angiography. Annu Int Conf IEEE Eng Med Biol Soc. 2023 Jul;2023:1-4. doi: 10.1109/EMBC40787.2023.10340650.
PubMed 38083399
Study at a glance
From the registry record, last updated by the sponsor on 19 Aug 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- AI Driven National Platform for CT cOronary Angiography for clinicaL and industriaL applicatiOns Registry (APOLLO)
- ClinicalTrials.gov ID
- NCT05509010
- Acronym / sponsor ID
- APOLLO / APOLLO
- Conditions
- CAD, Coronary Artery Disease, Coronary Stenosis, Plaques; Epicardial
- Keywords
- CTCA, CT Coronary Angiography
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 8,000 participants (estimated)
- Lead sponsor
- National Heart Centre SingaporeUniversity, hospital or other
- Collaborators
- Agency for Science, Technology and Research
- Study start
- 1 Oct 2021 (actual)
- Primary completion
- Dec 2027 (estimated)
- Study completion
- Dec 2027 (estimated)
- First posted
- 19 Aug 2022 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Observational model
- Cohort
- Time perspective
- Other
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Retrospective | – | Procedure: CTCA4000 patients who were clinically evaluated by CTCA from 1 Jan 2007 to 31 Oct 2017. |
| Prospective | – | Procedure: CTCA4000 patients who are clinically evaluated by CTCA. |
Who may qualify
- Ages
- 21 to 80 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Patients who are clinically evaluated by CTCA
Key inclusion criteria (3 listed)
- Age ≥21 years old
- Signed informed consent
- Clinically indicated for evaluation by CTCA
Key exclusion criteria (10 listed)
- Individuals unable to provide informed consent
- Known complex congenital heart disease
- Planned invasive angiography for reasons other than CAD
- Non-cardiac illness with life expectancy < 2 years
- Pregnancy
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| CTCACTCA is performed as part of routine care procedure. | Procedure or surgery | Prospective, Retrospective |
Primary outcome
AI precision toolkits: AI stenosis reporting
Time frame: baseline
Stenosis reporting: Severity of stenosis and accurate anatomical localization of stenosis. The significance of a stenosis is determined by visual estimation of the maximal grade of luminal narrowing caused by the plaque. As recommended in SCCT guideline (Leipsic et al., 2014) , coronary stenosis can be graded as minimal, mild, moderate, severe and total occluded separately. Following the guideline, a stenosis will be classified as obstructive and non-obstructive. The location of the stenosis uses the SCCT model (Leipsic et al., 2014)
AI precision toolkits: Agatston scoring
Time frame: baseline
Agatston scoring: Agatston scoring of calcified plaque. As recommended in SCCT clinical practical guidelines (Leipsic et al., 2014), Agatston scoring programs generally identify pixels that exceed 130 HU as a level corresponding to calcium on a non-contrast study (Agatston et al., 1990) . The reader needs to identify each lesion discrete calcific focus) in each vessel distribution. The summed score for each vessel is generated by the scoring program based on an area-density (Agatston score) (Agatston et al., 1990) measurement of each calcified focus. The total coronary Agatston score is the sum of all calcified lesions in all coronary beds.
AI precision toolkits: Plaque
Time frame: baseline
Plaque analysis: Plaque volume, burden, type and anatomical locations. Coronary segmentation and plaque analysis is performed for segments with diameter ≥1.5 mm. Location of plaque uses the SCCT model (Leipsic et al., 2014). For each plaque, the reader marks its start-and end-points, quantifies plaque area,volume and plaque burden, and specifies its type (non-calcified, calcified, or mixed) (Achenbach et al., 2004) . Additionally, non-calcified plaque can be further divided into low attenuation plaque (LAP). A HU <30 will signify LAP and >30 will signify non-LAP.
AI precision toolkits: EAT analysis
Time frame: baseline
EAT analysis: Total volume and anatomical locations. EAT and pericardial adipose tissue (PAT) are metabolically active fat surrounding the coronary artery and the heart, being associated with increased risk of cardiovascular disease (Villasante et al, 2019) . EAT can be quantified on non-contrast CT scans. The annotations on the CT scans are obtained by manually drawing the pericardium first to define the region. EAT is identified using the adipose tissue attenuation references between -190 and -30 HU (Oikonomou et al., 2018) . Due to the CT scan noise and changing of attenuation, the HU value of fat can vary, so the final EAT region is verified by an experienced radiologist or cardiologist.
3 secondary outcomes
AI outcome analysis
Time frame: one to five years from baseline
AI outcome analysis
Time frame: one to five years from baseline
AI outcome analysis
Time frame: one to five years from baseline
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 19 Aug 2022.
- Derived from this study: PubMed 41267847Leng S, Cheng N, Tan E, Baskaran L, Teo L, Yew MS, Ngiam KY, Huang W, Chai P, Ong CC, Sia CH, Singh M, Loong YT, Raffiee NAS, Wang X, Allen J, Tan SY, Chan M, Lee HK, Zhong L. Deep learning-based quantification of epicardial adipose tissue volume from non-contrast computed tomography images: a multi-centre study. Eur Heart J Digit Health. 2025 Oct 13;6(6):1223-1233. doi: 10.1093/ehjdh/ztaf116. eCollection 2025 Nov.
- Derived from this study: PubMed 39622571Baskaran L, Leng S, Dutta U, Teo L, Yew MS, Sia CH, Chew NW, Huang W, Lee HK, Vaughan R, Ngiam KY, Lu Z, Wang X, Tan EWP, Cheng NZY, Tan SY, Chan MY, Zhong L; APOLLO investigators. Cohort profile: AI-driven national Platform for CCTA for clinicaL and industriaL applicatiOns (APOLLO). BMJ Open. 2024 Dec 2;14(12):e089047. doi: 10.1136/bmjopen-2024-089047.
- Derived from this study: PubMed 38083399Wang X, Leng S, Lu Z, Huang S, Lee BH, Baskaran L, Yew MS, Teo L, Chan MY, Ngiam KY, Lee HK, Zhong L, Huang W. Context-aware deep network for coronary artery stenosis classification in coronary CT angiography. Annu Int Conf IEEE Eng Med Biol Soc. 2023 Jul;2023:1-4. doi: 10.1109/EMBC40787.2023.10340650.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Dr Lohendran Baskaran contact
Liang Zhong principal investigator
National Heart Centre Singapore
3 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of CAD and Coronary Artery Disease, run by National Heart Centre Singapore at 3 sites in Singapore.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 10 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 19 Aug 2022. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 3 sites in Singapore. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Associate Professor Zhong Liang (+65 6704 2237, zhong.liang@nhcs.com.sg), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
AI precision toolkits: AI stenosis reporting (time frame: baseline). The study lists 4 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05509010, which also lists 3 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 19 Aug 2022.