Coronary Artery DiseaseMAPLENCT07832175
AI-CCTA for Predicting Cardiovascular Events in CAD
An observational study of Coronary Artery Disease and Atherosclerotic Cardiovascular Disease, run by Nanjing First Hospital, Nanjing Medical University at 1 site in China.
Trial summary
This multicenter, retrospective registry study aims to evaluate the value of artificial intelligence (AI)-derived coronary CT angiography (CCTA) parameters in predicting long-term cardiovascular events in patients with coronary artery disease (CAD). Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Coronary Artery Disease, Atherosclerotic Cardiovascular Disease
- How many people
- 3,000 participants
- Where
- 1 siteChina
- Study dates
- 1 Jun 2026to Oct 2026
- 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 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: This multicenter retrospective registry evaluates AI-derived CCTA metrics in 3,000 adults with suspected or confirmed CAD undergoing CCTA and ICA within 90 days across six Chinese tertiary centers. Inclusion criteria: age ≥18 years, ≥12 months follow-up. AI platforms will quantify stenosis, high-risk plaque, CT-FFR, and pericoronary FAI. Baseline demographics, cardiovascular risk factors, biomarkers (lipids, hs-CRP, NT-proBNP), and pharmacotherapies will be assessed. The primary endpoint is MACE over a median 2-year follow-up. Secondary objectives include comparing AI diagnostic accuracy against ICA/QFR and assessing the modifying effects of lipid-lowering intensity and antiplatelet regimens on prognostic stratification. This study aims to establish an integrated anatomical-functional-inflammatory framework for personalized CAD management.
Who may be able to join
- Age ≥18 years at the time of index coronary CT angiography (CCTA).
- Clinically suspected or confirmed coronary artery disease (CAD).
- Underwent both CCTA and invasive coronary angiography (ICA) within 90 days.
- Availability of clinical follow-up data for at least 12 months after the index CCTA.
- Sufficient image quality of CCTA and ICA to allow AI-based analysis and quantitative assessment.
- Signed informed consent or waiver of informed consent approved by the Institutional Review Board (IRB).
Who cannot join
- Age <18 years.
- Poor CCTA image quality precluding reliable AI analysis (e.g., severe motion artifacts, inadequate contrast opacification).
- History of prior coronary artery bypass grafting (CABG).
- Follow-up duration <12 months or incomplete follow-up records.
- Known hypersensitivity to iodinated contrast media, hyperthyroidism, severe hepatic or renal dysfunction (eGFR <30 mL/min/1.73m²), or malignancy.
- Pregnancy or lactation at the time of CCTA.
- Incomplete or missing core baseline data (e.g., lack of CCTA/ICA images, key clinical variables, or lipid profiles).
Trial locations and contacts
1 site in 1 country.
China1 site
Nanjing First Hospital, Nanjing Medical University
Nanjing, Jiangsu, 210006
About this study
Official title: Multicenter Al-derived CCTA Parameters for Predicting Long-term Cardiovascular Events in Coronary Artery Disease: A Retrospective Registry Study
This multicenter, retrospective registry study aims to evaluate the value of artificial intelligence (AI)-derived coronary CT angiography (CCTA) parameters in predicting long-term cardiovascular events in patients with coronary artery disease (CAD). We plan to enroll 3,000 patients from five tertiary hospitals who underwent both CCTA and invasive coronary angiography (ICA) within 90 days. Using ICA and quantitative flow ratio (QFR) as reference standards, we will compare the diagnostic performance of different commercial AI software platforms. Furthermore, we will investigate the association between AI-extracted CCTA multidimensional parameters-including high-risk plaque features, CT-derived fractional flow reserve (CT-FFR), and pericoronary fat attenuation index (FAI)-and major adverse cardiac events (MACE) during over one year of follow-up. We will also explore how lipid-lowering therapies, antiplatelet regimens, and inflammatory biomarkers modify these predictive relationships. This study is expected to provide imaging evidence for personalized risk stratification and optimized clinical decision-making in CAD management.
Read the detailed description
Background
Coronary artery disease (CAD) remains the leading cause of global mortality. While coronary computed tomography angiography (CCTA) is a Class I-recommended noninvasive modality for evaluating stable chest pain, its interpretation is often limited by inter-observer variability and physician experience. Although artificial intelligence (AI) assists in automating stenosis quantification and plaque analysis, current evidence lacks large-scale, real-world comparisons between different AI platforms using invasive coronary angiography (ICA) as the gold standard. Additionally, the interplay between CCTA-derived anatomical/functional parameters, systemic inflammation, and pharmacological modifications (e.g., statins, antiplatelet agents) in predicting long-term prognosis remains unclear.
Objectives
This study seeks to: (1) Perform a head-to-head comparison of different commercial AI software in diagnosing obstructive CAD using ICA as the reference; (2) Explore the correlation between AI-derived CCTA parameters (plaque characteristics, CT-FFR, pericoronary fat inflammation) and major adverse cardiac events (MACE); (3) Assess the modifying effects of lipid-lowering intensity, LDL-C attainment, antiplatelet regimens, and inflammatory markers on the prognostic value of CCTA.
Methods
This is a multicenter, retrospective cohort study involving 3,000 patients across five centers (Nanjing First Hospital, The Second Hospital of Jilin University, etc.). Patients aged ≥18 years who underwent CCTA and ICA within 90 days between June 2013 and June 2025 will be screened. CCTA images will be analyzed using commercially available AI platforms (Shukun, United Imaging) to extract parameters including stenosis grading, plaque volume, CT-FFR, and pericoronary fat attenuation index (FAI). Clinical data, laboratory results (lipids, hs-CRP, NT-proBNP), and medication histories will be retrospectively collected. The primary endpoint is MACE (a composite of cardiac death, myocardial infarction, unplanned revascularization, and hospitalization for unstable angina/heart failure). Follow-up duration will be at least one year.
Analysis
Sensitivity, specificity, and AUC will be calculated for AI-CCTA against ICA. Survival analysis (Kaplan-Meier and Cox regression) will be used to identify independent predictors of MACE. Interaction terms will be employed to evaluate the modifying effects of pharmacotherapies. Statistical analysis will be performed by the Department of Biostatistics, Nanjing Medical University.
Significance
By integrating anatomical, functional, and inflammatory dimensions of CCTA with real-world therapeutic data, this study aims to establish a comprehensive risk stratification framework for CAD, potentially guiding precision medicine approaches in clinical practice.
- Being tested
- No intervention
- Medical subject headings
- Coronary Artery Disease, Atherosclerosis
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
No interventionOther
This is an observational study. No specific interventions are administered by the research team. Participants receive standard diagnostic and therapeutic procedures as per routine clinical practice. The study involves retrospective analysis of existing medical records (CCTA and ICA data) to evaluate the association between AI-derived metrics and clinical outcomes.
What is being measured
The primary outcome is the main question the study is designed to answer.
Incidence of Major Adverse Cardiac Events (MACE) at 2 years
MACE is defined as a composite endpoint including cardiac death, recurrent myocardial infarction, unplanned ischemia-driven revascularization (PCI or CABG), and hospitalization for unstable angina or acute heart failure. The incidence will be calculated as the proportion of participants experiencing at least one MACE event within 24 months after the index CCTA examination. All events will be independently adjudicated by two experienced cardiologists based on original medical records.
Measured: 2 years
Secondary outcomes (2)
All-cause Mortality at 2 Years
Defined as death from any cause during the 24-month follow-up period after the index CCTA examination.
Measured: 2 years
Cardiovascular Mortality at 2 Years
Defined as death due to cardiovascular causes, including acute myocardial infarction, worsening heart failure, arrhythmia, or sudden cardiac death, within 24 months after the index CCTA examination.
Measured: 2 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted21 Sep 2026
- Study start1 Jun 2026
- Primary completion31 Aug 2026
- Study completionOct 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Coronary Artery DiseaseStudies 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
- Retrospective
- Enrolment
- 3,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Nanjing First Hospital, Nanjing Medical University
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07832175
- Sponsor's protocol ID
- KY20260604-KS-03
- Acronym
- MAPLE
- Status last verified
- Jun 2026
- First submitted
- 22 Jul 2026
- Last updated
- 21 Sep 2026
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 21 Sep 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Multicenter Al-derived CCTA Parameters for Predicting Long-term Cardiovascular Events in Coronary Artery Disease: A Retrospective Registry Study
- ClinicalTrials.gov ID
- NCT07832175
- Acronym / sponsor ID
- MAPLE / KY20260604-KS-03
- Study type
- Observational
- Recruitment status
- Active, not recruiting
- Enrolment
- 3,000 participants (estimated)
- Lead sponsor
- Nanjing First Hospital, Nanjing Medical UniversityUniversity, hospital or other
- Study start
- 1 Jun 2026 (actual)
- Primary completion
- 31 Aug 2026 (actual)
- Study completion
- Oct 2026 (estimated)
- First posted
- 21 Sep 2026 (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.
This multicenter, retrospective registry study aims to evaluate the value of artificial intelligence (AI)-derived coronary CT angiography (CCTA) parameters in predicting long-term cardiovascular events in patients with coronary artery disease (CAD). We plan to enroll 3,000 patients from five tertiary hospitals who underwent both CCTA and invasive coronary angiography (ICA) within 90 days. Using ICA and quantitative flow ratio (QFR) as reference standards, we will compare the diagnostic performance of different commercial AI software platforms. Furthermore, we will investigate the association between AI-extracted CCTA multidimensional parameters-including high-risk plaque features, CT-derived fractional flow reserve (CT-FFR), and pericoronary fat attenuation index (FAI)-and major adverse cardiac events (MACE) during over one year of follow-up. We will also explore how lipid-lowering therapies, antiplatelet regimens, and inflammatory biomarkers modify these predictive relationships. This study is expected to provide imaging evidence for personalized risk stratification and optimized clinical decision-making in CAD management.
Detailed description
Background
Coronary artery disease (CAD) remains the leading cause of global mortality. While coronary computed tomography angiography (CCTA) is a Class I-recommended noninvasive modality for evaluating stable chest pain, its interpretation is often limited by inter-observer variability and physician experience. Although artificial intelligence (AI) assists in automating stenosis quantification and plaque analysis, current evidence lacks large-scale, real-world comparisons between different AI platforms using invasive coronary angiography (ICA) as the gold standard. Additionally, the interplay between CCTA-derived anatomical/functional parameters, systemic inflammation, and pharmacological modifications (e.g., statins, antiplatelet agents) in predicting long-term prognosis remains unclear.
Objectives
This study seeks to: (1) Perform a head-to-head comparison of different commercial AI software in diagnosing obstructive CAD using ICA as the reference; (2) Explore the correlation between AI-derived CCTA parameters (plaque characteristics, CT-FFR, pericoronary fat inflammation) and major adverse cardiac events (MACE); (3) Assess the modifying effects of lipid-lowering intensity, LDL-C attainment, antiplatelet regimens, and inflammatory markers on the prognostic value of CCTA.
Methods
This is a multicenter, retrospective cohort study involving 3,000 patients across five centers (Nanjing First Hospital, The Second Hospital of Jilin University, etc.). Patients aged ≥18 years who underwent CCTA and ICA within 90 days between June 2013 and June 2025 will be screened. CCTA images will be analyzed using commercially available AI platforms (Shukun, United Imaging) to extract parameters including stenosis grading, plaque volume, CT-FFR, and pericoronary fat attenuation index (FAI). Clinical data, laboratory results (lipids, hs-CRP, NT-proBNP), and medication histories will be retrospectively collected. The primary endpoint is MACE (a composite of cardiac death, myocardial infarction, unplanned revascularization, and hospitalization for unstable angina/heart failure). Follow-up duration will be at least one year.
Analysis
Sensitivity, specificity, and AUC will be calculated for AI-CCTA against ICA. Survival analysis (Kaplan-Meier and Cox regression) will be used to identify independent predictors of MACE. Interaction terms will be employed to evaluate the modifying effects of pharmacotherapies. Statistical analysis will be performed by the Department of Biostatistics, Nanjing Medical University.
Significance
By integrating anatomical, functional, and inflammatory dimensions of CCTA with real-world therapeutic data, this study aims to establish a comprehensive risk stratification framework for CAD, potentially guiding precision medicine approaches in clinical practice.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- This multicenter retrospective registry evaluates AI-derived CCTA metrics in 3,000 adults with suspected or confirmed CAD undergoing CCTA and ICA within 90 days across six Chinese tertiary centers. Inclusion criteria: age ≥18 years, ≥12 months follow-up. AI platforms will quantify stenosis, high-risk plaque, CT-FFR, and pericoronary FAI. Baseline demographics, cardiovascular risk factors, biomarkers (lipids, hs-CRP, NT-proBNP), and pharmacotherapies will be assessed. The primary endpoint is MACE over a median 2-year follow-up. Secondary objectives include comparing AI diagnostic accuracy against ICA/QFR and assessing the modifying effects of lipid-lowering intensity and antiplatelet regimens on prognostic stratification. This study aims to establish an integrated anatomical-functional-inflammatory framework for personalized CAD management.
Key inclusion criteria (6 listed)
- Age ≥18 years at the time of index coronary CT angiography (CCTA).
- Clinically suspected or confirmed coronary artery disease (CAD).
- Underwent both CCTA and invasive coronary angiography (ICA) within 90 days.
- Availability of clinical follow-up data for at least 12 months after the index CCTA.
- Sufficient image quality of CCTA and ICA to allow AI-based analysis and quantitative assessment.
Key exclusion criteria (7 listed)
- Age <18 years.
- Poor CCTA image quality precluding reliable AI analysis (e.g., severe motion artifacts, inadequate contrast opacification).
- History of prior coronary artery bypass grafting (CABG).
- Follow-up duration <12 months or incomplete follow-up records.
- Known hypersensitivity to iodinated contrast media, hyperthyroidism, severe hepatic or renal dysfunction (eGFR <30 mL/min/1.73m²), or malignancy.
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 |
|---|---|---|
| No interventionThis is an observational study. No specific interventions are administered by the research team. Participants receive standard diagnostic and therapeutic procedures as per routine clinical practice. The study involves retrospective analysis of existing medical records (CCTA and ICA data) to evaluate the association between AI-derived metrics and clinical outcomes. | Other | – |
Primary outcome
Incidence of Major Adverse Cardiac Events (MACE) at 2 years
Time frame: 2 years
MACE is defined as a composite endpoint including cardiac death, recurrent myocardial infarction, unplanned ischemia-driven revascularization (PCI or CABG), and hospitalization for unstable angina or acute heart failure. The incidence will be calculated as the proportion of participants experiencing at least one MACE event within 24 months after the index CCTA examination. All events will be independently adjudicated by two experienced cardiologists based on original medical records.
2 secondary outcomes
All-cause Mortality at 2 Years
Time frame: 2 years
Cardiovascular Mortality at 2 Years
Time frame: 2 years
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 21 Sep 2026.
- 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. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Coronary Artery Disease and Atherosclerotic Cardiovascular Disease, run by Nanjing First Hospital, Nanjing Medical University at 1 site in China.
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 6 inclusion and 7 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: under way, not looking for participants, as of the sponsor's last update on 21 Sep 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. 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?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Incidence of Major Adverse Cardiac Events (MACE) at 2 years (time frame: 2 years). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 21 Sep 2026; AzTrials last refreshed its copy on 26 Oct 2026.