Coronary Artery DiseaseAI-CARPETNCT06397820
Relation Between AI-QCA and Cardiac PET
An observational study of Coronary Artery Disease and Coronary Artery Stenosis, run by Chonnam National University Hospital at 1 site in South Korea.
Trial summary
The aim of the study is to evaluate the clinical implications of artificial Intelligence (AI)-assisted quantitative coronary angiography (QCA) and positron emission tomography (PET)-derived myocardial blood flow in clinically indicated patients. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Coronary Artery Disease, Coronary Artery Stenosis
- What is being tested?
- Percutaneous coronary intervention (PCI)
- Type of treatment
- Medical device
- How many people
- 168 participants
- Where
- 1 siteSouth Korea
- Study dates
- 1 Sep 2021to 31 Dec 2024
- Phase
- Observational
- Are there results?
- None posted in the registry
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: Patients with suspected coronary artery disease (CAD) undergoing invasive coronary angiography (CAG) and clinically indicated for cardiac PET assessment.
Who may be able to join
- Subject must be ≥18 years
- Patients suspected with CAD or ischemic heart disease
- Patients undergoing CAG and cardiac PET for evaluation of severity of coronary artery disease
Who cannot join
- Poor imaging quality of CAG and PET which were not available for core-lab analysis
- Chronic total occlusion
- Time interval was more than >3 months between CAG and PET
- History of coronary artery bypass grafting
- History of acute myocardial infarction or recent myocardial infarction
- Heart failure (left ventricular ejection fraction <40%)
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Relation Between Artificial Intelligence (AI)-Assisted Quantitative Coronary Angiography and Positron Emission Tomography-Derived Myocardial Blood Flow
The aim of the study is to evaluate the clinical implications of artificial Intelligence (AI)-assisted quantitative coronary angiography (QCA) and positron emission tomography (PET)-derived myocardial blood flow in clinically indicated patients.
Read the detailed description
Percutaneous coronary angiography (CAG) is a standard method for evaluating coronary artery disease. Traditionally, a reduction in the luminal diameter of the coronary arteries by 50% or more during angiography has been considered a significant stenotic lesion. However, the assessment of coronary artery stenosis is usually based on visual estimation by the operator in daily routine clinical practice, which interferes with the objective evaluation.
Quantitative coronary angiography (QCA) has been developed to overcome this limitation. This technique involves the software-based analysis of coronary images obtained through CAG. The previous study showed that there was low concordance between the QCA and visual estimation of coronary artery stenosis (Kappa=0.63) and a reclassification rate of approximately 20%. Furthermore, visual assessments tended to overestimate the degree of coronary artery stenosis, particularly in complex lesions such as bifurcation lesions.
However, there are some limitations to adopting QCA in our daily routine practice. The QCA cannot analyze coronary images on-site and is not fully automated, requiring manual adjustments by humans. Recent advancements have led to the development of artificial intelligence (AI)-based QCA software, which achieves complete automation in the analysis process and provides real-time objective evaluations of coronary artery stenosis.
This study aims to examine the clinical significance of AI-QCA by assessing the correlation between the degree of coronary stenosis detected by AI-QCA and myocardial blood flow abnormalities observed in 13NH3-Ammonia PET scans in patients with coronary artery disease.
- Conditions
- Coronary Artery Disease, Coronary Artery Stenosis
- Being tested
- Percutaneous coronary intervention (PCI)
- Keywords
- Invasive coronary angiography, Cardaic positron Emission Tomography, Artificial Intelligence, Quantitative Coronary Angiography
- Medical subject headings
- Coronary Artery Disease, Coronary Stenosis
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Percutaneous coronary intervention (PCI)Device
Revascularization by percutaneous coronary intervention for vessels with decreased PET-derived flow indexes
| Study group | Role | What they receive |
|---|---|---|
| Positive for PET-derived indexes | Patients who had decreased stress myocardial blood flow (MBF) or relative flow ratio (RFR) on PET Receives: Device: Percutaneous coronary intervention (PCI) | |
| Negative for PET-derived indexes | Patients who had preserved stress myocardial blood flow (MBF) or relative flow ratio (RFR) on PET |
What is being measured
The primary outcome is the main question the study is designed to answer.
Correlation between diameter stenosis by AI-QCA and PET-driven RFR
Performance of AI-QCA predicting for PET-driven RFR
Measured: Immediate after AI-QCA and PET exams
Correlation between diameter stenosis by AI-QCA and PET-driven stress MBF
Performance of AI-QCA predicting for PET-driven stress MBF
Measured: Immediate after AI-QCA and PET exams
Secondary outcomes (12)
Correlation between diameter stenosis by AI-QCA and PET-driven coronary flow reserve (CFR)
Performance of AI-QCA predicting for PET-driven CFR
Measured: Immediate after AI-QCA and PET exams
Correlation between diameter stenosis by AI-QCA and PET-driven coronary flow capacity (CFC)
Performance of AI-QCA predicting for PET-driven CFC
Measured: Immediate after AI-QCA and PET exams
Correlation between diameter stenosis by AI-QCA and PET-driven semi-quantitative markers of ischemia
Performance of AI-QCA predicting for PET-driven semi-quantitative markers of ischemia
Measured: Immediate after AI-QCA and PET exams
All-cause death
All-cause death
Measured: 1 year after last patient enrollment
Cardiovascular death
Cardiovascular death
Measured: 1 year after last patient enrollment
Myocardial infarction
Any myocardial infarction, defined by Forth Universal definition of myocardial infarction
Measured: 1 year after last patient enrollment
Rate of target lesion revascularization
Target lesion revascularization
Measured: 1 year after last patient enrollment
Rate of target vessel revascularization
Target vessel revascularization
Measured: 1 year after last patient enrollment
Rate of any revascularization
Any revascularization
Measured: 1 year after last patient enrollment
Rate of stent thrombosis
Definite or probable stent thrombosis, defined by ARC II definition
Measured: 1 year after last patient enrollment
Rate of cerebrovascular accident
Cerebrovascular accident
Measured: 1 year after last patient enrollment
Major adverse cerebrocardiovascular event (MACCE)
A composite of death, myocardial infarction, any revascularization, and cerebrovascular accident
Measured: 1 year after last patient enrollment
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted3 May 2024
- Study start1 Sep 2021
- Primary completion31 Jul 2024
- Study completion31 Dec 2024
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
- 168 participants (actual)
Sponsor and investigators
- Lead sponsor
- Chonnam National University Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Seung Hun Lee, Chonnam National University Hospital
- Investigators
- Sang-Geon Cho, MD, PhD, Principal investigator, Chonnam National University HospitalSeung Hun Lee, MD, PhD, Principal investigator, Chonnam National University Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06397820
- Sponsor's protocol ID
- CNUH-AI-CARPET
- Acronym
- AI-CARPET
- Status last verified
- Feb 2025
- First submitted
- 30 Apr 2024
- Last updated
- 24 Feb 2025
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: After publication of main paper, de-identified data will be shared upon reasonable requests after discussion by Executive Committee.
Study at a glance
From the registry record, last updated by the sponsor on 24 Feb 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Relation Between Artificial Intelligence (AI)-Assisted Quantitative Coronary Angiography and Positron Emission Tomography-Derived Myocardial Blood Flow
- ClinicalTrials.gov ID
- NCT06397820
- Acronym / sponsor ID
- AI-CARPET / CNUH-AI-CARPET
- Conditions
- Coronary Artery Disease, Coronary Artery Stenosis
- Keywords
- Invasive coronary angiography, Cardaic positron Emission Tomography, Artificial Intelligence, Quantitative Coronary Angiography
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 168 participants (actual)
- Lead sponsor
- Chonnam National University HospitalUniversity, hospital or other
- Study start
- 1 Sep 2021 (actual)
- Primary completion
- 31 Jul 2024 (actual)
- Study completion
- 31 Dec 2024 (actual)
- First posted
- 3 May 2024 (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 aim of the study is to evaluate the clinical implications of artificial Intelligence (AI)-assisted quantitative coronary angiography (QCA) and positron emission tomography (PET)-derived myocardial blood flow in clinically indicated patients.
Detailed description
Percutaneous coronary angiography (CAG) is a standard method for evaluating coronary artery disease. Traditionally, a reduction in the luminal diameter of the coronary arteries by 50% or more during angiography has been considered a significant stenotic lesion. However, the assessment of coronary artery stenosis is usually based on visual estimation by the operator in daily routine clinical practice, which interferes with the objective evaluation.
Quantitative coronary angiography (QCA) has been developed to overcome this limitation. This technique involves the software-based analysis of coronary images obtained through CAG. The previous study showed that there was low concordance between the QCA and visual estimation of coronary artery stenosis (Kappa=0.63) and a reclassification rate of approximately 20%. Furthermore, visual assessments tended to overestimate the degree of coronary artery stenosis, particularly in complex lesions such as bifurcation lesions.
However, there are some limitations to adopting QCA in our daily routine practice. The QCA cannot analyze coronary images on-site and is not fully automated, requiring manual adjustments by humans. Recent advancements have led to the development of artificial intelligence (AI)-based QCA software, which achieves complete automation in the analysis process and provides real-time objective evaluations of coronary artery stenosis.
This study aims to examine the clinical significance of AI-QCA by assessing the correlation between the degree of coronary stenosis detected by AI-QCA and myocardial blood flow abnormalities observed in 13NH3-Ammonia PET scans in patients with coronary artery disease.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Positive for PET-derived indexes | – | Device: Percutaneous coronary intervention (PCI)Patients who had decreased stress myocardial blood flow (MBF) or relative flow ratio (RFR) on PET |
| Negative for PET-derived indexes | – | –Patients who had preserved stress myocardial blood flow (MBF) or relative flow ratio (RFR) on PET |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Patients with suspected coronary artery disease (CAD) undergoing invasive coronary angiography (CAG) and clinically indicated for cardiac PET assessment.
Key inclusion criteria (3 listed)
- Subject must be ≥18 years
- Patients suspected with CAD or ischemic heart disease
- Patients undergoing CAG and cardiac PET for evaluation of severity of coronary artery disease
Key exclusion criteria (6 listed)
- Poor imaging quality of CAG and PET which were not available for core-lab analysis
- Chronic total occlusion
- Time interval was more than >3 months between CAG and PET
- History of coronary artery bypass grafting
- History of acute myocardial infarction or recent myocardial infarction
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 |
|---|---|---|
| Percutaneous coronary intervention (PCI)Revascularization by percutaneous coronary intervention for vessels with decreased PET-derived flow indexes | Device | Positive for PET-derived indexes |
Primary outcome
Correlation between diameter stenosis by AI-QCA and PET-driven RFR
Time frame: Immediate after AI-QCA and PET exams
Performance of AI-QCA predicting for PET-driven RFR
Correlation between diameter stenosis by AI-QCA and PET-driven stress MBF
Time frame: Immediate after AI-QCA and PET exams
Performance of AI-QCA predicting for PET-driven stress MBF
12 secondary outcomes
Correlation between diameter stenosis by AI-QCA and PET-driven coronary flow reserve (CFR)
Time frame: Immediate after AI-QCA and PET exams
Correlation between diameter stenosis by AI-QCA and PET-driven coronary flow capacity (CFC)
Time frame: Immediate after AI-QCA and PET exams
Correlation between diameter stenosis by AI-QCA and PET-driven semi-quantitative markers of ischemia
Time frame: Immediate after AI-QCA and PET exams
All-cause death
Time frame: 1 year after last patient enrollment
Cardiovascular death
Time frame: 1 year after last patient enrollment
Myocardial infarction
Time frame: 1 year after last patient enrollment
Rate of target lesion revascularization
Time frame: 1 year after last patient enrollment
Rate of target vessel revascularization
Time frame: 1 year after last patient enrollment
Rate of any revascularization
Time frame: 1 year after last patient enrollment
Rate of stent thrombosis
Time frame: 1 year after last patient enrollment
Rate of cerebrovascular accident
Time frame: 1 year after last patient enrollment
Major adverse cerebrocardiovascular event (MACCE)
Time frame: 1 year after last patient enrollment
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 24 Feb 2025.
- Individual participant dataSharing planned: Yes. After publication of main paper, de-identified data will be shared upon reasonable requests after discussion by Executive Committee.
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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.
Sang-Geon Cho, MD, PhD principal investigator
Chonnam National University Hospital
Seung Hun Lee, MD, PhD principal investigator
Chonnam National University Hospital
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 Coronary Artery Stenosis, run by Chonnam National University Hospital at 1 site in South Korea.
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 6 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: finished, as of the sponsor's last update on 24 Feb 2025. 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 South Korea. 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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
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?
Correlation between diameter stenosis by AI-QCA and PET-driven RFR (time frame: Immediate after AI-QCA and PET exams). The study lists 2 primary outcomes in all. 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 24 Feb 2025.