Written by Dr. Christopher Maroules, Director of Cardiac Imaging at SimonMed, this article was originally published in American Journal of Managed Care on March 2, 2026, and is republished here with permission.
AI-enabled coronary CT angiography reveals total plaque burden beyond calcium scores, improving risk prediction and personalizing cardiovascular prevention.
For decades, cardiovascular prevention has relied heavily on population-based risk scores, and many patients recognize the coronary calcium score. Although calcium scoring remains a valuable screening tool, it tells only part of the story. Many high-risk plaques are noncalcified and therefore invisible to calcium scoring alone, yet they’re strongly associated with future adverse cardiovascular events.1,2
Today, total plaque burden and high-risk plaque features derived from coronary CT angiography (CCTA) have been shown to provide incremental prognostic information, independently predicting future cardiovascular events even after adjustment for traditional risk factors. These advances in CCTA, combined with artificial intelligence (AI)–powered plaque analysis, are allowing us to move beyond risk estimation and toward true personalization of heart care.
Seeing what calcium scores can’t
A calcium score measures calcified plaque, acting essentially as the “scar tissue” of coronary artery disease. However, noncalcified plaque is a critical determinant of risk that calcium scoring alone cannot detect; patients with higher noncalcified plaque burden have more than 2.5 times the risk of major adverse cardiovascular events compared with those with lower burden.3
CCTA with AI plaque analysis changes this paradigm. Using advanced algorithms, AI can quantify total plaque burden, characterize plaque composition, and identify high-risk features within the coronary arteries with high agreement compared with invasive reference standards.⁴ Comparisons of AI-enabled CCTA plaque quantification to intravascular ultrasound have demonstrated strong agreement in diagnostic performance for plaque volume assessment and characterization.4
Instead of asking, “Is there calcium?” we can now ask, “How much plaque is there, what kind is it, and how aggressive should prevention be?”
Evidence that prevention works better when it’s precise
This personalized approach matters. Findings from large clinical studies have shown that patients undergoing CCTA with detailed plaque assessment experience up to a 41% lower risk of heart attack or cardiac death compared with standard evaluation.5 In a registry containing over 6500 patients undergoing AI-quantitative CCTA, prediction of major cardiovascular events improved from 62% to 75% when plaque quantification was added to risk models.6 The reason is simple: when clinicians can see disease earlier and more clearly, they act sooner and more effectively.
AI plaque analysis helps answer critical questions:
- Who needs aggressive cholesterol-lowering therapy?
- Who may benefit from closer follow-up or lifestyle intervention?
- Who can be reassured and avoid unnecessary testing?
From imaging to actionable prevention
The true power of AI-enabled CCTA lies not just in diagnosis but in decision-making. Results directly inform personalized prevention plans: tailored medications, nutrition and exercise strategies, and monitoring pathways aligned with each patient’s actual disease burden, not just their risk factors. AI-informed risk stratification has been shown to be cost-effective while improving patient outcomes, emphasizing the clinical value of moving beyond the solitary prognostic power of risk scores. By providing precise measures of plaque burden and composition, these insights allow clinicians to refine prevention strategies in ways that traditional risk scores just cannot capture in isolation.
As a cardiovascular imager, I see this shift daily: imaging evolving from a snapshot in time to a roadmap for prevention.
Looking ahead
As AI tools become more integrated in practice, insurance coverage and accessibility are gradually expanding and enabling broader adoption of precision imaging for heart health. Heart disease remains the leading cause of death—but it is also one of the most preventable. During Heart Month and beyond, CCTA with AI plaque analysis represents a meaningful step forward: earlier detection, smarter prevention, and care that is truly individualized.
Because when it comes to heart health, what we don’t see can matter just as much as what we do.
Learn more about CCTA with AI Plaque analysis >>
References
- Feuchtner GM, Lacaita PG, Bax JJ, et al. AI-quantitative CT coronary plaque features associate with a higher relative risk in women: CONFIRM2 registry. Circ Cardiovasc Imaging. 2025;18(6):e018235. doi:10.1161/circimaging.125.018235
- Dahdal J, Jukema RA, Maaniitty T, et al. CCTA-derived coronary plaque burden offers enhanced prognostic value over CAC scoring in suspected CAD patients. Eur Heart J Cardiovasc Imaging. 2025;26(6):945-954. doi:10.1093/ehjci/jeaf093
- Bell JS, Weir-McCall J, Nicol E, Lip GYH, Nørgaard BL, Fairbairn TA. Plaque quantification from coronary computed tomography angiography in predicting cardiovascular events: a systematic review and meta-analysis. J Cardiovasc Comput Tomogr. 2025;19(4):423-432. doi:10.1016/j.jcct.2025.05.003
- Ihdayhid AR, Tzimas G, Peterson K, et al. Diagnostic performance of AI-enabled plaque quantification from coronary CT angiography compared with intravascular ultrasound. Radiol Cardiothorac Imaging. 2024;6(6)::e230312. doi:10.1148/ryct.230312
- Coronary CT Angiography (CCTA) trial suggests lowered risk of death from coronary artery disease. Society of Cardiovascular Computed Tomography. Published 2025. Accessed February 5, 2026. https://scct.org/news/418009/Coronary-CT-Angiography-CCTA-Trial-Suggests-Lowered-risk-of-Death-from-Coronary-Artery-Disease.htm
- Coronary CT angiography evaluation for clinical outcomes: an international multicenter registry (CONFIRM2). Clinicaltrials.gov. Updated November 26, 2026. Accessed February 5, 2026. https://clinicaltrials.gov/study/NCT04279496
