How Is Cleerly Improving AI Heart Scan Analysis for Coronary Plaque Detection?

Why Are Hospitals Paying Attention to AI Coronary CTA Software Like Cleerly in 2026?

Cleerly and the Next Phase of AI in Cardiac Imaging

Cleerly is building a clear case for why artificial intelligence belongs in modern heart care. The company develops AI diagnostic software that analyzes heart scans, with a focus on coronary computed tomography angiography, or CCTA. This matters because CCTA gives clinicians a detailed view of the coronary arteries, and that view can help detect plaque, narrowing, and early signs of disease before a cardiac event occurs.

At its core, Cleerly’s software is designed to do something simple but valuable: help clinicians read complex heart scans with more consistency, more detail, and better clinical context. That is a meaningful goal in cardiology, where small differences in interpretation can affect whether a patient is reassured, sent for more testing, or moved toward treatment.

The company says its system has been trained on more than 10 million scans from 40,000 patients. That scale is important. In medical imaging, performance depends heavily on data quality, diversity, and repeated exposure to real-world variation. A large training base can help an AI system identify subtle patterns that may be missed in routine review, especially when clinicians work under time pressure or must interpret scans with borderline findings.

Why Cleerly’s Approach Stands Out

Traditional cardiac risk assessment often depends on symptoms, family history, cholesterol levels, blood pressure, and broad clinical scoring models. Those tools still matter, but they do not always tell the full story. Many patients who later suffer heart attacks were not flagged as high-risk by standard screening methods. The reason is straightforward: risk factors estimate probability, but imaging can show the disease itself.

That is where Cleerly fits. Rather than relying only on external indicators, its software analyzes the actual images from a CCTA scan to measure plaque burden and characterize plaque type in the coronary arteries. This matters because not all plaque carries the same level of concern. A more precise plaque assessment can give physicians a better sense of who may need closer follow-up, medication changes, or additional testing.

The value becomes even clearer when looking at how scans are interpreted without AI support. Human readers are skilled, but variability is common in imaging. Some clinicians may overcall disease severity. Others may miss early but relevant features. In one trial cited by the company, Cleerly’s technology identified 53% fewer significant stenoses than clinical professionals reading without AI assistance. That suggests the software may reduce overestimation of abnormal narrowing and, in turn, reduce unnecessary downstream testing.

That point deserves attention. In cardiovascular care, overtesting carries real costs:

• It can increase patient anxiety.
• It can lead to additional imaging or invasive procedures.
• It can raise healthcare spending without improving outcomes.
• It can place strain on specialists and hospital systems.

If software helps clinicians avoid false alarms while still identifying meaningful disease, its impact extends beyond diagnosis. It can improve care pathways, resource use, and patient experience.

The Clinical Need Is Larger Than Many Realize

One of the strongest arguments for advanced cardiac imaging is that traditional screening can miss a large number of people who are still at risk. The source content notes that 70% of heart attack patients are classified as “low-risk” by traditional approaches that assess symptoms or common risk factors alone. Whether the exact proportion varies by study population, the broader point remains highly relevant: symptoms and standard risk scoring do not catch every dangerous case.

AI does not replace clinical judgment, but it can strengthen it. When paired with CCTA, software like Cleerly can give physicians a more direct look at coronary disease. That creates a practical advantage in cases where symptoms are vague, risk scores appear modest, or disease is present before major obstruction develops.

A simple example helps. Consider a patient with intermittent chest discomfort who does not fit the usual high-risk profile. A conventional workup may classify that person as relatively safe. A CCTA scan reviewed with AI, however, may detect plaque characteristics that suggest early coronary disease. That added detail can change how the clinician thinks about prevention, medication, and follow-up.

Why 2026 Matters

Cleerly’s market position gained more support with a major reimbursement development. The American Medical Association issued a new Category I CPT code for AI coronary plaque analysis, effective in January 2026. In healthcare, coding is more than administration. It affects billing, reimbursement, adoption, and the willingness of providers to integrate a technology into routine care.

A Category I CPT code signals that the procedure has moved beyond experimental interest into a more established clinical and commercial category. It reflects a stronger evidence base and gives providers a clearer path to payment discussions with insurers. That does not mean immediate universal coverage, but it does improve the foundation for broader access.

For Cleerly, this matters for three reasons:

• It supports provider adoption by making workflow integration easier to justify.
• It improves the commercial case for hospitals and imaging centers.
• It increases the likelihood that more patients will gain access through insurance over time.

In health-tech markets, reimbursement often separates promising tools from durable businesses. Many products show technical value. Far fewer reach routine use without a viable payment pathway. Cleerly now has a stronger argument on that front.

Business Momentum and Investor Signal

The company also completed a Series C extension in December 2024, bringing that round to $106M. In the context of medical AI, that level of funding suggests investors see more than a niche software play. They likely see a platform with relevance across cardiology, imaging workflows, preventive care, and value-based healthcare.

Capital matters in this sector because clinical AI is expensive to build and scale. Companies need funding for:

• Product development.
• Regulatory work.
• Clinical validation.
• Provider partnerships.
• Sales cycles that can take months or years.
• Integration with hospital systems and imaging infrastructure.

A well-funded company can do more than market its product. It can build evidence, support implementation, and stay competitive as standards rise.

Cleerly Within the Wider AI Diagnostics Market

Cleerly is not operating in isolation. It sits within the broader AI diagnostics trend, especially in medical imaging. This is one of the few areas where AI has shown repeated practical value because imaging data is structured, visual, and well suited to pattern recognition.

The FDA has approved more than 1,400 AI-enabled medical devices, and most relate to radiology. That detail is important because it shows where AI is already gaining traction in real clinical settings. Imaging gives AI a natural use case: large data volumes, recurring interpretation tasks, and the need for consistency.

The market numbers also point in the same direction. The AI medical imaging market is estimated at $1.67B today and is projected to reach $12.69B by 2033. Even if estimates differ across research firms, the growth trend is clear. Providers want better tools. Payers want more efficient care. Patients want earlier detection and fewer unnecessary procedures.

Cleerly’s advantage is that it focuses on a high-cost, high-impact clinical area. Cardiovascular disease remains one of the largest causes of illness, death, and healthcare spending worldwide. A tool that helps detect disease earlier, classify it more precisely, and reduce avoidable testing addresses a problem that hospitals and insurers already care about.

The Competitive Landscape

The wider imaging AI field includes companies working in other high-need areas, which reinforces the size of the opportunity.

Spectral AI develops wound imaging technology. A recent study found that its DeepView system identified non-healing tissue more than twice as effectively as burn physicians. That highlights a broader pattern in medical AI: software can add value where image interpretation is complex and treatment decisions carry high stakes.

Lunit focuses on AI for cancer detection. The company has reported that its technology can help identify breast cancer at an earlier stage in a meaningful share of patients, and its revenue grew at a compound annual growth rate of 173% from 2019 to 2025. That kind of commercial performance shows that imaging AI can move from technical promise to real business traction when evidence, workflow fit, and demand align.

These companies are not direct copies of Cleerly, but they prove that the market is rewarding software that improves image-based decision-making. Cleerly’s place in cardiology gives it a distinct lane within that pattern.

What Makes Cleerly Relevant to Hospitals and Health Systems
For decision-makers in healthcare, the question is rarely whether AI sounds useful. The real question is whether it improves outcomes, fits workflow, and supports financial logic. Cleerly appears relevant because it addresses all three.

From a hospital or imaging center perspective, the appeal includes:

• Better consistency in scan interpretation.
• More detailed plaque analysis from existing CCTA images.
• Potential reduction in unnecessary follow-up testing.
• Stronger support for preventive cardiology decisions.
• A clearer reimbursement path after the new CPT code.

For clinicians, the practical value is not about replacing expertise. It is about adding a layer of structured analysis that supports decision-making. That is often where the best medical AI products succeed. They do not try to remove the physician from the process. They make the physician’s process more informed and more repeatable.

Risks and Limits to Watch

A strong article should not treat every health-tech company as a certainty. Cleerly has momentum, but the path ahead still depends on execution.

Key issues to watch include:

• How broadly insurers reimburse for AI coronary plaque analysis.
• Whether hospitals adopt the software at scale.
• How well the technology performs across different populations and practice settings.
• Whether clinicians trust and use the outputs in routine care.
• How competitors respond in cardiac imaging and adjacent diagnostic categories.

Medical AI also faces a higher standard than many software markets because the stakes are clinical. Accuracy, transparency, validation, and workflow fit matter more than branding alone. In a YMYL category like heart health, trust is earned through evidence and outcomes.

Why Cleerly Deserves Attention Now

Cleerly stands out because it sits at the intersection of three powerful trends: preventive cardiology, AI-enabled imaging, and reimbursement-backed clinical software. It is tackling a problem that is both common and costly. It uses a modality that physicians already know. It offers a use case that is easy to understand: better interpretation of heart scans, with more insight into plaque and stenosis.

That combination gives the company a practical market story. It is not selling a vague AI concept. It is offering a targeted diagnostic tool with a specific clinical purpose and a growing evidence base.

For readers tracking healthcare innovation, Cleerly is worth watching not simply because it uses AI, but because it applies AI in a setting where better analysis can change real decisions. In a crowded digital health market, that distinction matters. The most durable companies are often the ones that solve a concrete clinical problem, fit into existing care pathways, and gain support from both evidence and reimbursement. Cleerly is moving in that direction.