In his new book, Super Agers: An Evidence Based Approach to Longevity, renowned cardiologist Eric Topol highlights a revolutionary development in heart disease prevention: the use of AI to predict an individual’s risk of a fatal heart attack years before symptoms occur. As Dr. Topol notes, AI-enhanced imaging of the fat surrounding the coronary arteries now enables doctors to see inflammation, the previously invisible underlying driver of heart attacks and stroke.
Topol predicts American cardiologists will soon use these AI tools to identify high-risk individuals long before conventional methods detect disease, potentially saving tens of thousands of lives.
How radical is this development? Just consider. For decades, our approach to coronary artery disease (CAD) has revolved around identifying and treating blockages in coronary arteries — visible obstructions to blood flow, such as plaque. But recent advances in medical research and technology are driving a fundamental reassessment of this approach. We now know that the initial driver of heart attacks and strokes is not plaque alone but rather plaque in combination with inflammation of the coronary arteries. And new anti-inflammatory drugs provide a proven treatment for the condition.
Despite this understanding, “the cardiovascular community has not moved on to change practice, acknowledging our ability to detect inflammation and to do something about it,” writes Topol.
Mostly that’s because we have lacked the technology to diagnose and quantify inflammation in the coronary arteries.
That’s finally beginning to change. As Topol points out, thanks to breakthroughs in AI that enable the visualization of inflammation on standard CT scans, and significant new regulatory changes, the U.S. is on the cusp of integrating the diagnosis of coronary inflammation into routine clinical practice.
If the approach is eventually widely adopted, as Topol foresees, the result will be a sea-change in cardiovascular medicine, enhancing not only patient outcomes but how we diagnose and manage CAD.
Inflammation: The invisible driver of heart disease
Cardiologists have long understood that coronary inflammation is a key driver of both plaque formation and instability leading to blockages and heart attacks. Yet our diagnostic tools have focused only on identifying obstructions rather than the underlying inflammation. And for good reason. Traditional stress tests and nuclear imaging are great when it comes to assessing arterial blockages but cannot measure the inflammatory response behind the physical symptoms.
An important example of this limitation turned up in a major study in The Lancet. Researchers examined cardiac CT scans from 40,000 patients and found that only one-third of cardiac events over the next seven years happened to those with obstructive CAD.
In other words, two-thirds of patients were sent home believing they were at low risk for a heart attack, only to suffer one in the next few years.
The study highlights the vast unmet need for diagnostic tools to detect silent coronary inflammation, which precedes the development of obstructive CAD.
Technological breakthroughs: AI and cardiac inflammation
The Lancet study took advantage of pioneering research by a team of cardiologists from the University of Oxford. In 2017, Charalambos Antoniades, Professor of Cardiovascular Medicine at Oxford, introduced the Fat Attenuation Index (FAI), a method for detecting coronary inflammation in cardiac CT scans by analyzing the perivascular fat that surrounds arteries. Subsequent research — including the aforementioned Lancet study — has provided definitive proof that the FAI Score can accurately predict patient risk up to a decade in advance.
The practical application of this knowledge is just beginning. Several AI solutions visualize plaque on CT scans – but none yet approved by the FDA can visualize inflammation, which would enable a far more complete view of arterial plaque burden than was previously possible. Research by the Oxford team led to the development of the world’s first AI capable of visualizing coronary inflammation. Already approved for use in the UK, EU, and Australia, this technology is currently awaiting FDA clearance in the United States.
Regulatory changes clear the way for clinical adoption
Along with advances in technology, widespread clinical adoption is supported by the development of new regulatory and reimbursement frameworks. Two recent policy changes in the U.S. have set the foundation for integrating AI-powered inflammation analysis into routine practice:
The American Medical Association released a new Category 3 CPT code for billing and reimbursement: Beginning in 2026, this code will allow providers to bill for the use of AI in analyzing cardiac CT scans for the presence of coronary inflammation, ensuring that hospitals and clinics have financial incentives to adopt the technology.
Also beginning in 2026, the Centers for Medicare & Medicaid Services (CMS) will nearly double current reimbursement for cardiac CT scans. That will enable healthcare providers to prioritize CT-based diagnostics over traditional stress tests, which have shown significant limitations in predicting cardiovascular risk.
Together, these regulatory changes are already accelerating the transition toward inflammation-focused diagnostics, ensuring that more patients benefit from the new AI analysis of CT imaging.
A new standard in cardiovascular care
These changes have profound implications. The primary reason heart disease remains the leading global killer is our inability to identify high-risk individuals before they suffer major cardiac events. Now, with the ability to measure coronary inflammation through AI-enhanced CT scans and to more accurately determine a person’s risk of heart attack, we can intervene earlier and more effectively. This represents a tremendous shift in how we detect and prevent heart attacks.
Now, patients can receive earlier interventions and improved prevention, reducing the risk of sudden cardiac events. Physicians finally have a tool that goes beyond detecting blockages to assess the full spectrum of heart disease risk. And our healthcare system can dramatically reduce the financial burden of cardiovascular disease by proactively preventing major acute cardiovascular events.
What once seemed like a theoretical concept — that coronary inflammation could be visualized and measured — has now become a key to driving preventive care. With clinically proven AI-powered diagnostics and expanded reimbursement policies, cardiovascular medicine is entering a new era.
The next challenge is to ensure these innovations are rapidly adopted and made available to the millions of patients who can benefit from them.
Author bio:
Frank Cheng is CEO of Caristo Diagnostics. Over the last 20 years he has led multiple digital health companies. Frank previously led two venture-backed companies as CEO and held executive positions with GE, Roche, Hillrom, and Stereotaxis. Prior to Caristo, he was President and Chief Commercial Officer of a diagnostic company with autonomous AI technology that was FDA-cleared, Medicare-reimbursed, supported by a new Category 1 CPT code, and adopted around the world.
Image: Magicmine, Getty Images
