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Identifying Coronary Artery Calcification on Non-gated Computed Tomography Scans
Published on: August 28, 2018
Plaque characteristics and parameters derived from coronary computed tomography angiography for predicting major
Xiyi Huang1,2, Shaomin Yang3, Zaopeng He4
1Department of Clinical Laboratory, Lecong Hospital of Shunde, Foshan, China.
Insights
Coronary computed tomography angiography (CCTA) plaque characteristics predict major adverse cardiovascular events (MACEs) differently in diabetic versus non-diabetic patients. Low-attenuation plaque and coronary artery calcium score predict MACEs in diabetics, while positive remodeling is key in non-diabetics.
Area of Science:
- Cardiology
- Radiology
- Medical Imaging
Background:
- Coronary atherosclerosis is the primary cause of coronary heart disease.
- Diabetic patients have a significantly higher risk of cardiovascular events.
- Coronary computed tomography angiography (CCTA) provides valuable plaque characteristics.
Purpose of the Study:
- To compare the predictive value of CCTA-derived plaque features for major adverse cardiovascular events (MACEs) in patients with and without diabetes.
- To identify specific CCTA parameters that predict MACEs in each group.
- To inform clinical management strategies for cardiovascular risk stratification.
Main Methods:
- Retrospective analysis of 472 coronary artery disease patients (132 diabetic, 340 non-diabetic).
- Collection of clinical and CCTA imaging data, followed by MACEs follow-up.
- Multivariate Cox regression and receiver operating characteristic (ROC) curve analysis to identify predictors and assess predictive value.
Main Results:
- In diabetic patients, coronary artery calcium score (CACS) ≥100 and low-attenuation plaque (LAP) predicted MACEs.
- The combination of CACS and LAP showed predictive value for 1-, 3-, and 5-year MACEs in diabetics.
- In non-diabetic patients, positive remodeling (PR) was a strong predictor of MACEs, with high areas under the curve (AUCs) for 1-, 3-, and 5-year predictions.
Conclusions:
- CCTA plaque characteristics and CT-derived parameters have varying predictive values for MACEs in diabetic and non-diabetic patients.
- CACS and LAP effectively assess MACE risk in diabetic patients.
- PR is a more potent predictor of MACEs in non-diabetic individuals.
Background:
Coronary atherosclerosis is the primary pathological basis of coronary heart disease, and patients with diabetes face an elevated risk of cardiovascular events. The value of plaque characteristics and derived parameters based on coronary computed tomography angiography (CCTA) in predicting major adverse cardiovascular events (MACEs) may differ between patients with and without diabetes. This study aimed to compare the predicative value of plaque features and computed tomography (CT)-derived parameters from CCTA in forecasting MACEs in between patients with and without diabetes, providing a more accurate reference for clinical management.
Methods:
A total of 472 patients with coronary artery disease were retrospectively enrolled, including 132 patients with diabetes and 340 patients without diabetes. Clinical and imaging data were collected, and follow-up was conducted. Multivariate Cox proportional hazards regression was used to identify risk factors, while receiver operating characteristic (ROC) curve analysis assessed the predictive value for MACEs.
Results:
In the diabetic group, the independent predictors of MACEs were coronary artery calcium score (CACS) ≥100 [hazard ratio (HR) =1.98; 95% confidence interval (CI): 1.06-3.72; P=0.033] and the presence of low-attenuation plaque (LAP) (HR =2.13; 95% CI: 1.00-4.53; P=0.049). The combination of CACS and LAP predicted 1-, 3-, and 5-year MACEs, with areas under the curve (AUCs) of 0.649, 0.603, and 0.668, respectively. In the nondiabetic group, positive remodeling (PR) was a strong predictor of MACEs (HR =45.00; 95% CI: 22.69-89.28; P<0.001), with AUCs of 0.792, 0.884, and 0.795 at 1, 3, and 5 years, respectively. Significant differences in baseline characteristics such as hypertension, CT-derived fractional flow reserve ≤0.8, and Coronary Artery Disease Reporting and Data System score ≥3 were observed between the two groups (P<0.05).
Conclusions:
The value of plaque characteristics and CT-derived parameters in predicting MACEs varies between patients with and without diabetes. The combination of CACS and LAP is effective in assessing MACE risk in patients with diabetes, whereas PR is a stronger predictor of MACEs in patients without diabetes.
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