A promising area of artificial intelligence (AI) in radiology is its use to opportunistically screen patients for various diseases through computed tomography (CT) scans they receive for unrelated reasons.
Researchers at Brigham and Women’s University recently conducted a study using AI to screen CT scans for signs of heart disease in patients with elevated inflammation levels. This screening of over 2,000 patients revealed that more than 50% had detectable coronary calcium, indicating early coronary artery disease (CAD).
Many patients undergo chest CT scans for issues like pneumonia or lung cancer, not cardiac disease. However, these scans often reveal coronary calcifications incidentally, an indicator of CAD that may go unreported or ignored. AI can retrospectively analyze these scans, identifying high-risk patients for follow-up before any symptoms appear.
“We’re finding that applying AI to non-cardiac CTs makes it possible to detect coronary calcifications in patients who would otherwise go unnoticed,” stated a lead researcher involved in the study.
The AI technology can now analyze images and quantify calcified plaque in coronary arteries, even when the scan’s original intent is different.
A team, including experts in cardiac imaging and rheumatology, presented their findings at the Society of Cardiovascular Computed Tomography (SCCT) 2024. They showed that 50% of patients with autoimmune diseases like lupus and rheumatoid arthritis had elevated calcified plaque, significantly increasing their risk of heart attacks.
This opportunistic screening is especially relevant for patients with inflammatory conditions, as inflammation accelerates plaque formation and increases the risk of plaque rupture, which can cause heart attacks. Inflammation is a potent risk factor for heart disease, providing valuable data for preventive strategies.
The study adds to evidence linking inflammation to cardiovascular health, making AI screening a powerful tool for early intervention. With early detection of calcifications, physicians can intensify treatments like lowering LDL cholesterol or managing inflammation with drugs like colchicine.
The future of AI in cardiovascular imaging is promising. Experts envision AI integrated into electronic medical records (EMR), flagging high-risk patients previously overlooked. Many believe CT screenings will become a key tool for preventive care, enabling drug treatments years before symptoms appear.
“AI’s ability to screen millions of chest CTs and find hidden coronary disease could revolutionize preventive cardiology,” said the researcher. This advancement supports population health efforts by moving beyond traditional risk factors to direct diagnostic insights.
As AI improves cardiovascular disease detection, it leads to earlier interventions and better patient outcomes. “This technology not only identifies disease but also fosters proactive behaviors to mitigate risks,” the researcher added.
With growing interest, AI-driven opportunistic screening may soon become widespread, helping reduce the global burden of cardiovascular disease. Economically, these screenings offer value, as health systems can screen patients without extra resources for dedicated programs, generating ROI through increased cardiology program participation. Although reimbursement isn’t available yet for AI screenings, health systems can benefit from additional testing and treatment.
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