Your Coronary Artery Disease Workup Could Be Sending Patients to Unnecessary Angiography. Here’s What AI Changes.
Heart disease remains the leading cause of death in the U.S., but coronary artery disease care loses ground long before a heart attack happens.
Too often, clinicians rely on tests that send patients toward invasive procedures before they fully understand who needs them, and Washington State has already shown the cost of that approach: more than 800 unnecessary coronary angiography procedures in a single year, at a cost of more than $12 million.
Dr. Suresh K. Mukherji, MD, MBA, FACR, who moderated the session, put the technology shift in plain terms: cardiac imaging has moved from slow, indirect views of disease to fast scans that can show the heart, the coronary arteries, blood flow, and plaque itself.
He said that when CT and AI work together, clinicians can measure anatomy and function directly instead of relying only on older, more invasive tests. That matters because it opens the door to earlier answers, fewer complications, and a better match between the test and the patient.
Dr. Ahmad M. Slim, MD, FACC, chief medical officer of Pulse Health Heart Institute in the Puget Sound region and associate professor of medicine at the University of Washington, explained that clinicians used to focus mainly on blockages that caused symptoms.
Today, better cardiac CT can show plaque that may trigger a heart attack even when a vessel does not look severely blocked. That shift matters because a test that only looks for stenosis can miss the patients who need earlier treatment.
AI changes the speed and precision of that work. Dr. Slim described AI coronary plaque analysis as a way to review plaque segment by segment in a fraction of the time it once took expert readers. He said the platform helps clinicians identify vulnerable plaque, assess risk at the patient level, and guide treatment changes.
In the examples he shared, the output changed medical management in more than half of cases. He also noted that the approach aligns with current cardiology guidance and pairs well with FFR-CT, a CT-based test that estimates whether a blockage limits blood flow.
The conversation also focused on value. Dr. Allen J. Taylor, MD, FACC, FAHA, chairman of cardiology at MedStar Heart and Vascular Institute, who oversees MedStar Georgetown University Hospital and MedStar Washington Hospital Center, said the goal is not to screen everyone. It is to replace older tests in symptomatic patients with a better diagnostic path.
He pointed to evidence that cardiac CT can reduce downstream testing and, in the right setting, improve outcomes. Dr. Slim added that the newer approach can lower radiation compared with older nuclear testing and reduce invasive procedures that carry complication risk.
For Washington, the case goes beyond clinical accuracy. The speakers tied modern CAD diagnosis to affordability, less variation, and better access.
Rural communities and patients in eastern Washington often face more barriers to specialty care, while current risk models can miss important differences in groups such as South Asian, Filipino, American Indian, and Alaska Native patients. Better imaging and AI-assisted analysis can bring more complete care closer to home and help clinicians act sooner with more confidence.
Missed the session? Watch the full recording here.