Recent developments in reimbursement and insurer coverage for plaque analysis in the US are a step towards the evaluative method becoming a standardised approach to determine an individual’s risk of coronary artery disease (CAD), according to Elucid’s CEO.
On 9 January, quantitative coronary plaque analysis for evaluating coronary atherosclerotic plaque buildup, as facilitated by software such as Elucid’s Plaque-IQ, became reportable under a new reimbursement code.
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Cleared by US Food and Drug Administration (FDA) in October 2024, the Boston-based company’s Plaque-IQ is an artificial intelligence (AI)-based software specifically designed to quantify lipid-rich necrotic core (LRNC) build-up in the carotid arteries following coronary computed tomography angiography (CCTA) for the production of 3D images of the heart’s blood vessels. LRNC is a high-risk plaque that research has strongly linked with the risk of ischemic stroke or heart attack due to arterial rupture.
The American Medical Association’s (AMA) Category I CPT code 75577 for plaque analysis means the analytic method is covered with a national average payment amount of $1,012 for use in imaging centres and physician offices and $951 in hospital outpatient settings.
With this change, plaque analysis is now formally recognised, widely accepted, and reimbursable by insurers in the US, including Medicare.
According to Elucid CEO Kelly Huang, with US healthcare insurers including UnitedHealthcare, Humana and Aetna recently moving to cover plaque analysis, 70% of Americans are now covered for the diagnostic modality.
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By GlobalDataHuang told Medical Device Network: “We now expect [with plaque analysis gaining a CPT code] that adoption will dramatically change, because now a doctor can provide this function and not have to worry about losing money.”
Huang noted that today, individuals still have to present with a symptom to get insurance reimbursement for plaque analysis.
In 2025, the Lancet Commission called for a reframing of existing interventional approaches to CAD, expressing a need for practitioners to manage patients not only through their exhibited symptoms, but by attaining a better understanding of the plaque build-up in their coronary arteries.
Huang continued: “The American College of Cardiology has also begun to outline recommendations of how to manage patients based upon plaque results.
“My expectation is that while plaque analysis hasn’t formally changed medical guidelines yet, in time, it will.”
To spread awareness of Plaque-IQ, Elucid is working with medical societies in an effort to support a change in CAD treatment guidelines.
Huang continued: “Medical guidelines will help that diffusion of knowledge as well. Ultimately, our belief is that in the next five years, coronary plaque analysis will be a screening method, much like colonoscopies or mammograms, to prevent disease.”
With such a shift, Huang foresees that patients will be to get an evaluation for plaque and be prescribed a statin, to “drop it” and ensure that their plaque buildup doesn’t progress.
“With such evaluative measure in place, patients won’t have to get to a point where they’re experiencing symptoms like chest pain and have to think about undertaking a procedure to open up a vessel with a catheter; that’s very late in the game to start talking to a cardiologist,” he concluded.
Other companies using AI in a similar way to evaluate cardiovascular risk include HeartFlow. The company went public in August 2025 with the completion of a $364m initial public offering (IPO), resulting in a $2.2bn valuation. In September 2025, the company gained FDA clearance for the latest version of its Heartflow Plaque Analysis platform.
Meanwhile, AccuLine shared results from an Israel-based clinical trial for its CORA system for CAD evaluation on 28 January and is now planning to initiate a larger US-based trial to support a market clearance with the FDA. CORA is a non-invasive point-of-care diagnostic that uses electrodes to capture the electrical cardiac activity (ECG), oxygen saturation, and respiratory phase of suspected CAD patients in under four minutes. These readings are then processed with AI to stratify an individual’s risk of developing CAD.
AI is having a profound impact in the healthcare space, particularly around imaging and diagnostic protocols. GlobalData analysis forecasts that AI in healthcare will reach a $19bn valuation by 2027.
