Cardiovascular disease remains one of the leading causes of death worldwide, making early identification of coronary artery disease (CAD) a critical priority. Among the most valuable tools available today is the coronary artery calcification score, commonly known as the Calcium Score (CAC score). Derived from computed tomography (CT) imaging, this metric provides clinicians with important insights into the burden of atherosclerosis and the likelihood of future cardiovascular events [1].
Today, advances in artificial intelligence are enhancing CAC assessment far beyond traditional calcium quantification. Modern cardiovascular image analysis can detect calcified and non-calcified plaque, evaluate coronary blood flow, and support more personalized prevention strategies.
The coronary artery calcification score is a numerical measure of calcium deposits within the coronary arteries obtained from CT imaging. Calcium accumulation gradually narrows and hardens the arteries, eventually leading to atherosclerosis. Higher CAC scores generally indicate a greater burden of coronary artery disease and a higher risk of adverse cardiovascular events.
Traditionally, CAC scoring has been used to:
The most widely used method is the Agatston Score, which quantifies calcified lesions detected during a non-contrast cardiac CT scan.
The value of the coronary artery calcification score extends beyond a simple number. Much research demonstrates a strong relationship between increasing CAC scores and the presence of confirmed coronary artery disease. Higher scores are associated with increased rates of coronary artery disease, greater need for revascularization procedures, and higher cardiovascular risk.
For patients with stable chest pain, CAC scoring may help identify individuals at lower risk who could potentially avoid invasive diagnostic procedures. This creates opportunities for more efficient patient management while reducing unnecessary interventions.
Nevertheless, despite its clinical value, CAC scoring is not a complete picture of cardiovascular health.
One important challenge is the so-called “zero calcium paradox”. Patients with a CAC score of 0 may still have non-calcified atherosclerotic plaque that cannot be detected through conventional calcium scoring alone. One must remember that the absence of coronary calcification does not necessarily mean the absence of coronary artery disease. [2]
Interestingly, this limitation has stimulated the development of advanced AI-driven cardiovascular imaging solutions capable of detecting additional markers of cardiac disease risk.
The next generation of cardiovascular image analysis extends far beyond the calculation of a coronary artery calcification score.
Advanced AI solutions are now capable of identifying:
This broader approach enables a more comprehensive understanding of cardiovascular risk and cardiac disease in an individual patient. Remember: many patients remain asymptomatic until the disease has progressed to an advanced stage. And for some, a myocardial infarction is the first clinical manifestation.
BRIGHTER imaging Platform is an advanced environment designed for reviewing and analyzing CT and coronary CT angiography studies using artificial intelligence.
The platform integrates specialized algorithms that support:
By combining multiple AI-powered analyses within a single workflow, BRIGHTER helps clinicians extract more value from medical images and gain a broader understanding of cardiovascular risk. This approach supports earlier detection, improved risk stratification, and more personalized patient management.
Preventive cardiology increasingly relies on imaging biomarkers to identify patients before symptoms become severe.
The coronary artery calcification score remains one of the most established predictors of future cardiovascular risk. However, when combined with advanced AI analysis, plaque characterization, and functional assessment, it becomes part of a much richer clinical picture.
As cardiovascular imaging continues to evolve, clinicians will be able to move beyond simple calcium quantification toward comprehensive, patient-specific risk assessment.
The coronary artery calcification score has become an essential tool for evaluating cardiovascular risk and supporting clinical decision-making. While traditional CAC assessment remains highly valuable, artificial intelligence is helping healthcare providers move beyond calcium alone.
With solutions such as BRIGHTER, clinicians can combine Calcium Score calculation, plaque detection, blood flow simulation, and advanced cardiovascular image analysis into a single diagnostic workflow. The result is a more complete understanding of coronary artery disease and an opportunity to improve prevention, reduce unnecessary procedures, and support better patient outcomes.
What is a coronary artery calcification score?
A coronary artery calcification score, also known as a Calcium Score or CAC score, is a measurement of calcium deposits in the coronary arteries obtained from CT imaging. It helps estimate the burden of atherosclerosis and cardiovascular risk.
Is a CAC score of zero always good news?
Not necessarily. A CAC score of zero is associated with lower cardiovascular risk, but it does not completely exclude the presence of non-calcified plaque or coronary artery disease.
How does AI improve Calcium Score assessment?
AI can automate calcium detection, plaque segmentation, risk categorization, and image analysis, enabling faster and more consistent results while reducing manual workload.
Can Calcium Score be estimated from a chest CT scan?
Yes. Advanced AI solutions integrated into platforms such as BRIGHTER can estimate Calcium Score from routine chest CT examinations, expanding opportunities for opportunistic cardiovascular screening.
What additional information can be obtained beyond CAC scoring?
Modern AI-powered cardiovascular analysis can evaluate non-calcified plaque, high-risk plaque characteristics, pericoronary adipose tissue, and coronary blood flow, providing a more comprehensive assessment of cardiovascular risk.
Who can benefit from coronary artery calcification scoring?
CAC scoring may benefit individuals with cardiovascular risk factors, patients with stable chest pain, and those who may require more precise cardiovascular risk stratification to guide prevention and treatment strategies.
REFERENCES:
[1] https://graylight-imaging.com/blog/automating-coronary-artery-calcium-scoring-with-ai/
[2] The latest comparison of CAC and SIS suggests that SIS identifies a higher cardiovascular risk burden than CAC, particularly in individuals who have no detectable coronary calcium (CAC = 0): Khan, N.A., Wesbey III, G., Cobb, G. et al. Using AI-Quantitative CT to evaluate the relationship between coronary artery calcium and segment involvement scores in quantifying coronary plaque burden. Int J Cardiovasc Imaging 42, 49–59 (2026). https://doi.org/10.1007/s10554-025-03569-6
