Elucid Secures Broad Reimbursement for its Quantitative Coronary Plaque Analysis

Elucid’s Plaque-IQ coronary plaque analysis has received a new Category I Current Procedural Terminology (CPT) designation, alongside increasingly widespread coverage and reimbursement from both public and private payers.

Quantitative coronary plaque analysis, such as Elucid’s Plaque-IQ, is now reportable under Category I CPT code 75577, with a national average payment amount of $1,012 for use in imaging centers and physician offices. For hospital outpatient settings, the 2026 Outpatient Prospective Payment System (OPPS) rate has been set at $951. The CPT code 75577 establishment by the American Medical Association (AMA) provides a standardized code descriptor for quantitative assessment of coronary atherosclerotic plaque using coronary computed tomography angiography (CCTA).

This designation is complemented by a coverage decision by Aetna to immediately begin covering plaque analysis. Aetna’s decision follows similar coverage decisions by Humana, Cigna, and UnitedHealthcare, all aligned with guidelines issued in July 2025 by radiology benefit manager Evicore. Collectively, more than 70% of covered Americans now have health coverage policies in place for coronary plaque analysis.

“Plaque analysis is quickly becoming an essential tool in my overall patient diagnosis and management, and its adoption will only accelerate as coverage continues to expand,” said Victor Marinescu, M.D., a cardiologist at Midwest Cardiovascular Institute in Naperville, Ill. “I’m particularly intrigued by Elucid‘s histology-based technology and Plaque-IQ’s ability to identify lipid rich necrotic core (LRNC). This additional insight is influencing my diagnostic decisions and shaping how I manage patient care.”

While other plaque analysis technologies are validated against a human eye, Elucid’s Plaque-IQ is reportedly the only plaque analysis technology validated in objective ground truth histology, the gold standard for plaque characterization. Powered by CT-Virtual Histology (CT-VH), Plaque-IQ noninvasively quantifies and classifies coronary plaque and its components—including LRNC—providing insights into high-risk plaque features associated with heart attack and stroke, measuring true disease rather than directional proxies.^1,2

This approach is designed to help physicians prioritize and personalize treatment based on actual coronary artery disease rather than population-based risk estimates.

“Elucid has long been committed to advancing clinically meaningful imaging analytics that support physician decision-making,” Elucid CEO Kelly Huang, Ph.D., stated. “The scope, scale and speed of these reimbursement changes are unprecedented, and highlight the clinical value that CT-derived coronary plaque analysis brings to physicians and their patients. These advances reinforce our belief that Plaque-IQ helps physicians make patient-specific decisions around medical management and intervention.”

Elucid is a Boston-based artificial intelligence medical technology company developing technology designed to provide physicians with a more precise view of atherosclerosis (coronary and carotid plaque buildup), the root cause of cardiovascular disease. The company’s Plaque-IQ image analysis software helps physicians prioritize and personalize treatment based on actual disease, rather than population-based risk of disease. Plaque-IQ includes the only U.S. Food and Drug Administration-cleared computed tomography angiography (CTA) algorithm that objectively quantifies plaque morphology validated against ground truth histology. Plaque-IQ equips physicians with critical information regarding the type and amount of plaque in arteries that can lead to heart attack and stroke. Elucid’s FFRCT product, which is currently under development, is derived from Elucid’s plaque algorithm, resulting in concordance between plaque and FFRCT. FFRCT helps physicians identify coronary blockages and the extent of a patient’s ischemia non-invasively.

References
¹ https://www.ahajournals.org/doi/10.1161/01.ATV.20.5.1262
² https://pubmed.ncbi.nlm.nih.gov/39600843/