Imaging plaques or imaging fat.

Area of Science:

• Cardiovascular Imaging
• Preventive Cardiology
• Radiology

Background:

• Coronary computed tomography angiography (CCTA) is crucial for non-invasive coronary artery disease (CAD) assessment.
• CCTA provides detailed visualization of coronary anatomy and plaque characteristics.
• It offers prognostic value beyond traditional risk stratification.

Purpose of the Study:

• To review the expanding role of CCTA in preventive cardiology.
• To highlight advancements in CCTA analysis, including AI and body composition.
• To discuss CCTA's utility in risk prediction and therapeutic monitoring.

Main Methods:

• Review of current literature on CCTA applications in CAD.
• Discussion of AI-driven analytics for plaque quantification and functional assessment (FFR-CT).
• Exploration of CCTA-derived adipose tissue metrics (FAI, PCAT) and their prognostic implications.

Main Results:

• CCTA accurately assesses plaque burden, composition, and high-risk features.
• AI enhances automated plaque quantification and FFR-CT integration.
• CCTA-derived adipose tissue metrics predict adverse cardiac events and reflect inflammation.
• Serial CCTA demonstrates therapeutic efficacy in plaque regression and stabilization.

Conclusions:

• CCTA is a pivotal modality in preventive cardiology.
• Integrating CCTA with AI and body composition analysis refines personalized risk prediction.
• CCTA guides preventive strategies and monitors therapeutic interventions.