# Beyond Traditional Risk Calculators: The Expanding Role of Coronary Artery Calcium Scoring in Preventive Cardiology

## TL;DR

Coronary artery calcium (CAC) scoring is a promising tool for assessing heart disease risk, offering better predictions than traditional methods and guiding treatment decisions.

## Contribution

This review highlights CAC's superior risk stratification and explores its expanding role in preventive cardiology, including new AI-based applications.

## Key findings

- CAC scoring provides better prognostic value than traditional risk calculators like Framingham.
- A CAC score of 0 reliably indicates very low cardiovascular risk.
- AI-driven CAC quantification from chest CT scans offers scalable and low-cost implementation.

## Abstract

Coronary artery calcium (CAC) scoring has emerged as an increasingly recognized and guideline-endorsed tool in cardiovascular risk stratification, particularly for asymptomatic individuals at intermediate risk. This narrative review synthesizes data from 109 peer-reviewed studies (2000-2025) to evaluate the current clinical utility, limitations, and future potential of CAC scoring in the primary prevention of atherosclerotic cardiovascular disease (ASCVD). Robust evidence demonstrates that CAC offers superior prognostic value compared to traditional risk estimators such as the Framingham Risk Score and pooled cohort equations, effectively guiding decisions on statin and aspirin therapy. A CAC score of 0 reliably predicts very low event rates and holds potential for de-escalating preventive therapy, yet remains underused. Technological advances, including artificial intelligence (AI)-driven CAC quantification from non-gated chest CT scans, present scalable and low-cost opportunities for broader implementation. However, significant barriers persist, including inconsistent guideline integration, radiation concerns, economic limitations, and the absence of large randomized controlled trials (RCTs) validating outcome benefits. Future research must establish population-specific CAC thresholds, validate AI tools in real-world settings, and generate robust RCT data to confirm clinical impact. Integrating CAC scoring into routine preventive care could redefine personalized cardiovascular risk assessment and close critical gaps in equitable ASCVD prevention.