冠状动脉钙化扫描如何改变心脏病预防与医疗支付现状

— The guidelines have finally caught up to the evidence supporting coronary artery calcium scans

by Arthur Agatston, MD, and Oren Mechanic, MD, MPH

October 25, 2026 • 3 min read

We are currently in a "golden age of medical science," yet in a "dark age of healthcare delivery." An important illustration is the diagnosis and treatment of America's number one cause of death and disability, coronary artery disease. More than 800,000 Americans suffer a heart attack each year. The great majority of these events are preventable. The coronary artery calcium score (CAC) is a simple 10-minute scan that can identify the presence and amount of coronary atherosclerosis many years before it causes a heart attack. It costs about $100 and uses a fraction of the radiation of a standard chest CT.

In March 2026, after more than three decades of accumulated evidence, the American College of Cardiology (ACC) and American Heart Association (AHA) finally gave CAC a central role in their national guidelines for the prevention of coronary artery disease. The CAC scan, which detects calcified plaque in the arteries, is recommended for adults with borderline or intermediate risk of coronary disease for whom the decision to start preventive therapy such as statin drugs remains uncertain.

For decades, doctors have relied on risk calculators built around age, sex, serum cholesterol, diabetes status, blood pressure, and smoking to estimate who might have a heart attack. The calculators estimate probability, not the actual presence of coronary atherosclerosis. In contrast, a CAC scan detects the disease itself. This is important because a patient with a borderline or low cholesterol may already have extensive plaque, while another with a high cholesterol may have none. A calcium score of zero re-classifies risk downward and thereby can avoid unnecessary pharmacologic treatment, such as statins. A score above 100 identifies patients who may benefit from pharmacologic and aggressive lifestyle intervention.

An excellent illustration of the role of CAC scanning is Rob*, a 52-year-old patient we saw recently. He exercises regularly, eats well, and has borderline high cholesterol. He has a family history of heart disease but no other known cardiac risk factors. The standard risk calculator places him in a low risk category, and he would prefer to defer treatment.

His CAC score, however, tells a different story. It is 220, indicating a substantial atherosclerotic plaque burden for a man his age. Genetics account for roughly half of cardiovascular risk, but the risk calculators do not include genetics. The scan demonstrated that drug treatment gives Rob his best chance of preventing a future heart attack.

Despite mountains of evidence proving its superiority over conventional risk factors for predicting heart attacks, CAC scanning has been included only peripherally in national guidelines for the past 35 years. Why?

Part of the delay is structural. Clinical decision support tools were built to modify population-average risk factors, not to incorporate individualized imaging. Guideline committees move cautiously, as they should, and prevention is harder to standardize than intervention. Cardiologists and primary care doctors, constrained by what insurers will cover, are left offering the test mainly to patients who can pay cash out of pocket.

With the updated ACC/AHA guideline, heart attack prevention is finally aligning around a simple principle: when possible, measure the disease.

Artificial intelligence (AI) is also changing the economics of prevention. Millions of Americans already undergo chest CT scans for other reasons, yet the cardiovascular information visible on those scans is often ignored. AI can identify coronary and vascular calcification opportunistically, standardize reporting, and flag patients who should receive formal preventive evaluation. That's especially important for patients least able to pay cash for elective testing.

AI-CAC is now being used to measure soft plaque, an important precursor to hard plaque seen on traditional calcium scores. Used responsibly, AI-enabled CAC analysis could help move heart disease prevention to the population health level.

Heart attacks are largely preventable, and we have had the means to find the disease and treat it in time for more than a generation. What we have lacked is a payment system that spends $100 to avoid a $50,000 emergency.

The story of CAC isn't so unique. It is the story of how a low-cost, low-risk, well-studied tool can sit at the edge of clinical practice for decades because the systems around it -- the guidelines, the reimbursement codes, the habits of practice -- were not built to absorb it.

The evidence has been strong for years, and the guidelines have finally caught up.

*Patient's name changed for confidentiality.