AI-powered CCTA plaque analysis advances personalized preventive cardiology
Artificial intelligence (AI) is rapidly expanding the clinical value of coronary CT angiography (CCTA), enabling physicians to quantify coronary plaque, assess lesion characteristics and better personalize treatment strategies for heart patients.
Speaking at SCCT2026, the Society of Cardiovascular Computed Tomography (SCCT) annual meeting, Matthew Budoff, MD, a professor of medicine at the David Geffen School of Medicine at UCLA, endowed chair of preventive cardiology at Harbor-UCLA Medical Center and former SCCT president, said AI-powered plaque analysis is transforming information already captured in routine CT scans into actionable clinical insights.
"These scans already exist," Budoff explained. "We can take existing data and now get a lot more information."
He said AI can quantify non-calcified plaque volume, identify low-attenuation or vulnerable plaque, and measure plaque and stenosis length—measurements that were previously too time-consuming for routine clinical practice.
Manually performing these detailed plaque measurements for research studies has historically taken three to five hours per patient, he added, but AI now performs those analyses automatically, providing clinicians with objective, reproducible measurements that improve risk assessment and patient management.
The technology also supports a shift toward individualized preventive cardiology. Rather than relying solely on population-based treatment recommendations, physicians can monitor a patient's plaque burden over time to determine whether therapies are effectively slowing or reversing disease progression.
"If your plaque goes from 142 down to 100, I pat you on the back and say we're on the right track," Budoff said. Conversely, increasing plaque volume despite acceptable cholesterol levels may prompt clinicians to intensify medical therapy.
FFR-CT and FAI offers additional details on patient risk
AI plaque analysis complements another major advancement in cardiac CT: fractional flow reserve derived from CT (FFR-CT). While plaque analysis focuses on prevention, FFR-CT helps determine whether coronary blockages are physiologically significant in symptomatic patients. Budoff said combining anatomic and functional information allows cardiologists to better plan interventions and prepare for complex procedures before patients enter the catheterization laboratory.
The growing clinical evidence supporting these technologies has also translated into broader reimbursement. Budoff noted that most major insurers now cover both AI plaque analysis and FFR-CT, aided by new Category I CPT codes that took effect this year.
Looking ahead, Budoff expects AI to unlock additional information from routine CT examinations beyond the coronary arteries. Existing CT scans can already be used to evaluate bone density, liver fat, epicardial fat and other markers of overall health without additional radiation exposure.
He also highlighted the emerging role of fat attenuation index (FAI) imaging, which measures coronary inflammation. FAI is already being incorporated into clinical trials evaluating new anti-inflammatory therapies for coronary artery disease and could become another important component of personalized cardiovascular risk assessment.
Budoff believes CCTA will continue expanding its role over the next decade, driven by advances in scanner technology, including photon-counting CT, and increasingly sophisticated AI applications.
"I honestly think it'll be the predominant diagnostic test," he said, predicting CT angiography will become the first-line imaging test for most patients with chest pain. He said it could ultimately play a central role in preventive cardiology as evidence from ongoing clinical trials continues to accumulate. He said trials to keep a close eye on include SCOT Heart II, Dane Heart II and Transform.
Dave Fornell has covered healthcare for more than 17 years, with a focus in cardiology and radiology. Fornell is a 5-time winner of a Jesse H. Neal Award, the most prestigious editorial honors in the field of specialized journalism. The wins included best technical content, best use of social media and best COVID-19 coverage. Fornell was also a three-time Neal finalist for best range of work by a single author. He produces more than 100 editorial videos each year, most of them interviews with key opinion leaders in medicine. He also writes technical articles, covers key trends, conducts video hospital site visits, and is very involved with social media. E-mail: [email protected]