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| Name | Class |
|---|---|
| Science Foundation Ireland | OTHER |
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The goal of this observational study is to learn if AI-assisted cardiac CT imaging can improve cardiovascular risk stratification and prediction of future coronary events in an adult population undergoing clinically indicated cardiac CT.
The main questions it aims to answer are:
Participants will:
The ACTION Registry (Artificial Intelligence-assisted CT for Risk Stratification in Coronary Artery Disease) is a prospective, single-centre, observational patient registry conducted at the Clinical Research Facility, University Hospital Galway.
This registry is designed to systematically collect and integrate multimodal data from adults undergoing clinically indicated cardiac computed tomography (CT) to support advanced cardiovascular risk assessment using artificial intelligence (AI)-based approaches.
Registry Design and Procedures Eligible participants are consecutively enrolled at the time of referral for clinically indicated cardiac CT. Following informed consent, data are collected during a single baseline visit and supplemented by routine clinical data and follow-up information where available.
Registry procedures include:
Data Collection and Registry Variables
The registry captures structured data across the following domains:
All variables are defined in a standardized data dictionary, which specifies:
A comprehensive quality assurance plan is implemented, including:
Data Validation and Entry Controls
Registry operations are governed by standardized procedures covering:
The anticipated sample size is sufficient to support:
Missing or incomplete data may arise due to non-response, unavailable records, or technical limitations. The registry implements the following approach:
Approaches may include:
Data Use and Future Applications
The registry is designed to support:
Ethical and Regulatory Considerations The registry is conducted in accordance with the Declaration of Helsinki and Good Clinical Practice guidelines. Ethical approval will be obtained from the appropriate research ethics committee, and all participants will provide written informed consent prior to inclusion
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| Measure | Description | Time Frame |
|---|---|---|
| Cardiovascular risk stratification using AI-assisted cardiac CT | Assessment of cardiovascular risk based on AI-enhanced cardiac CT imaging, including coronary artery calcium scoring, plaque characterization, and integrated risk prediction using clinical and imaging data. | Baseline |
| Measure | Description | Time Frame |
|---|---|---|
| Correlation between CT-derived plaque characteristics and haematological biomarkers | Association between imaging-derived plaque features and blood biomarkers (e.g., CRP, lipid profile, ApoB/ApoA-1 ratio). | Baseline |
| Concordance between coronary CT angiography (CCTA) and optical coherence tomography (OCT) |
| Measure | Description | Time Frame |
|---|---|---|
| Development of an anonymized multimodal dataset for AI training and validation | Creation of a secure dataset integrating imaging, clinical, biomarker, and lifestyle data for future AI development. | through study completion, up to 10 years |
Inclusion Criteria:
Exclusion Criteria:
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All-comers adult population undergoing clinically indicated cardiac CT in routine clinical care
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Faisal Sharif | Contact | +353 91524222 | faisal.sharif@universityofgalway.ie |
| Name | Affiliation | Role |
|---|---|---|
| Faisal Sharif, MBBS, PhD, FRCPI, FESC, FACC | University of Galway | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Clinical Research Facility | Recruiting | Galway | Ireland |
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| ID | Term |
|---|---|
| D003324 | Coronary Artery Disease |
| D017202 | Myocardial Ischemia |
| ID | Term |
|---|---|
| D003327 | Coronary Disease |
| D006331 | Heart Diseases |
| D002318 | Cardiovascular Diseases |
| D001161 | Arteriosclerosis |
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Agreement between CT-derived plaque characteristics and OCT findings in a subset of participants. |
| Baseline (subset undergoing OCT) |
| Association between lifestyle factors and imaging-derived plaque risk features | ssociation between lifestyle factors (e.g., smoking, diet, occupation) and imaging-derived Parameters. | Baseline |
| Subgroup analyses of cardiovascular risk by demographic and clinical factors | Differences in imaging and risk profiles across subgroups (age, sex, comorbidities, hormonal history). | Baseline |
| Longitudinal changes in plaque composition in patients receiving statin therapy | Evaluation of plaque progression or regression over time in participants on statin treatment. | Baseline, 1 year, and annually up to 5 years |
| Feasibility and utility of CT-derived fractional flow reserve (CT-FFR) and AI-based risk models | Assessment of the applicability and performance of CT-FFR and AI-based models in risk prediction. | Baseline |
| D001157 |
| Arterial Occlusive Diseases |
| D014652 | Vascular Diseases |