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Identifying Coronary Artery Calcification on Non-gated Computed Tomography Scans
Published on: August 28, 2018
Cardiac CT-Detected Vulnerable Plaques and Risk of Future Acute Myocardial Infarction: Predictive Value of CAC Scores
Sefa Erdi Ömür1, Emin Koyun2, Gökhan Cabri1
1Department of Cardiology, Tokat Gaziosmanpaşa University, Tokat - Turquia.
Insights
Combining coronary artery calcium (CAC) scores and inflammatory burden index (IBI) improves prediction of myocardial infarction (MI) risk in patients with coronary artery disease detected by CT angiography.
Area of Science:
- Cardiology
- Radiology
- Biomarkers
Background:
- Computed Tomography (CT) angiography is a standard non-invasive tool for evaluating coronary artery disease.
- Identifying patients at high risk for acute myocardial infarction (MI) remains challenging.
- Systemic inflammation, indicated by the Inflammatory Burden Index (IBI), may contribute to cardiovascular risk.
Purpose of the Study:
- To assess the predictive value of Coronary Artery Calcium (CAC) scores and IBI for MI risk.
- To determine the combined effectiveness of CAC and IBI in risk stratification.
- To identify optimal cut-off values for these markers in predicting MI.
Main Methods:
- Retrospective analysis of 1235 patients undergoing CT angiography for chest pain.
- Follow-up for 3 years to record MI occurrence.
- Categorization into risk models based on CAC and IBI scores.
Main Results:
- Higher CAC and IBI scores were significantly associated with MI occurrence.
- Both CAC and IBI were identified as independent predictors of MI.
- Optimal cut-off values were determined: IBI (128) and CAC (102).
Conclusions:
- The combination of IBI and CAC scores enhances risk stratification for future MI.
- This combined approach aids in identifying 'vulnerable patients' with plaque detected by CT angiography.
- Improved risk assessment can lead to more targeted treatment strategies for high-risk individuals.
Background:
Computed Tomography (CT) angiography is widely used as a basic non-invasive modality to evaluate coronary artery disease. Inflammatory burden index (IBI) is a systemic inflammation indicator reflecting the inflammatory status. It is still difficult to determine the high risk of future acute myocardial infarction (MI) in patients with plaque detected by CT angiography.
Objective:
This study aimed to evaluate the effectiveness of CAC scores and IBI in predicting MI risk among patients undergoing CT angiography for chest pain. We sought to assess the individual and combined predictive value of these indices, determine their optimal cut-off values, and compare MI risk across patient groups with varying CAC and IBI scores. We also aimed to evaluate the potential role of these markers in identifying 'vulnerable patients' at high risk for future cardiovascular events.
Methods:
This retrospective study included 1235 patients who underwent CT angiography due to chest pain and were followed for 3 years (2.8-3.4). Patients were categorized into three models based on their CAC and IBI scores. The primary outcome was the occurrence of MI during the follow-up period. Statistical significance was established at p < 0.05 for all analyses.
Results:
Patients who experienced MI had significantly higher IBI and CAC scores compared to those without MI. Logistic regression analysis identified CAC score and IBI as independent predictors of MI. ROC analysis determined optimal cut-off values for IBI (128) and CAC (102) in predicting MI. Kaplan-Meier analysis revealed a significant gradient in MI risk across the three models, with the highest risk observed in patients with both high IBI and CAC scores.
Conclusion:
The combination of IBI and CAC scores provides improved risk stratification for the prediction of future MI (vulnerable plaque) in patients with plaque detected by CT angiography. This approach may facilitate more specific treatment strategies for high-risk patients.
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