Heart disease often builds up quietly over time. Many people feel healthy until a serious event such as a heart attack or stroke occurs.
This is why early detection is so important. The sooner doctors can identify risk, the more they can do to prevent damage.
A new study from Mayo Clinic suggests that we may already have more information than we realize.
By using artificial intelligence, researchers have found a way to improve heart risk prediction using a test that many patients already receive.
The study was presented at the 2026 American College of Cardiology Scientific Session and published in the American Journal of Preventive Cardiology. It followed nearly 12,000 adults over 16 years, giving researchers a long-term view of how heart disease develops.
The researchers focused on coronary artery calcium scans. These scans are used to detect calcium buildup in the heart’s arteries, which is a known sign of heart disease. Doctors often use this information along with other factors, such as age, blood pressure, and cholesterol, to estimate a person’s risk.
In this study, AI was used to analyze the same scans in a new way. It measured the amount of fat surrounding the heart. This fat has been linked to inflammation and heart problems, but it has not been widely used in routine care because it was difficult to measure.
The findings showed that people with higher levels of this heart fat were more likely to develop cardiovascular disease. This remained true even when other risk factors were considered. In other words, the fat measurement provided new and independent information.
Around 10% of participants developed heart disease during the study. Those with the most heart fat had the highest risk. Importantly, this was seen even in people who had low calcium scores, which are usually considered reassuring.
When the fat measurement was added to existing tools, such as the PREVENT equation and calcium scoring, the ability to predict future heart problems improved. This was especially helpful for people whose risk was unclear based on standard methods.
This approach has several advantages. It does not require new tests or extra time for patients. The information comes from scans that are already part of routine care. This makes it easier to apply in real-world settings.
However, there are still questions to answer. More studies are needed to understand how doctors should use this information in practice. It is also important to study different populations to ensure the results apply broadly.
Despite these limitations, the study highlights the growing role of AI in medicine. It shows how technology can help doctors find hidden patterns and improve decision-making.
From a clinical perspective, this research supports a move toward more personalized healthcare. Instead of relying only on general risk factors, doctors can use more detailed information to guide treatment.
In conclusion, this study suggests that important clues about heart health may already exist in routine scans. With the help of AI, these clues can be revealed and used to improve prevention. This could help many people avoid serious heart problems in the future.
If you care about heart health, please read studies about how eating eggs can help reduce heart disease risk, and herbal supplements could harm your heart rhythm.
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