Coronary artery calcification-does it predict the CAD-RADS category?

Area of Science:

• Cardiovascular Imaging
• Radiology
• Preventive Cardiology

Background:

• Coronary artery disease (CAD) is a leading cause of mortality.
• Cardiac-gated computed tomography (CCT) with coronary calcium scores (CCSs) is a validated method for CAD assessment.
• Computed tomography angiography (CTA) is often used for definitive CAD diagnosis but involves radiation and contrast agents.

Purpose of the Study:

• To evaluate the predictive capability of CCSs for coronary artery disease reporting and data system (CAD-RADS) categories.
• To determine if CCSs can obviate the need for CTA in assessing CAD severity.
• To establish cut-off values for CCSs to predict significant CAD (CAD-RADS 3-5).

Main Methods:

• Analysis of CCT and CTA data from 544 patients.
• Calculation of various CCS metrics: number of calcified regions of interest (ROIs), Agatston score, area, volume, and mass.
• Comparison of CCS values across CAD-RADS categories (1-5) using ROC curve analysis and logistic regression.
• Determination of predictive cut-offs for significant CAD.

Main Results:

• CCSs, particularly the number of calcified ROIs, showed significant differences between CAD-RADS categories.
• Established cut-offs for predicting significant CAD (CAD-RADS 3-5) were: 9 ROIs, 128 Agatston score, 44 mm² area, 111 mm³ volume, and 22 mg mass.
• Predictive models achieved 79% accuracy for the most probable CAD-RADS category and 81% for significant/non-significant CAD.

Conclusions:

• CCSs demonstrate significant potential in predicting CAD-RADS categories with approximately 80% accuracy.
• These findings suggest CCSs may help stratify patients and potentially reduce the need for CTA in certain cases.
• Further research into novel calcium indices is warranted to enhance predictive capabilities.