RapidAI Outperforms Viz.ai in Detecting Medium Vessel Occlusions in Stroke Study

A newly released study presented at the European Stroke Organisation Conference (ESOC) has found that RapidAI's deep algorithms outperforms Viz.ai in identifying medium vessel occlusions (MeVOs) in stroke patients. Using real-world data from more than 1,500 cases, researchers concluded that RapidAI detected 33% more MeVOs than Viz.ai when using CT perfusion imaging alone—highlighting major differences in clinical accuracy between the two platforms.

The findings underscore the critical role advanced AI tools play in stroke diagnosis and treatment. As Harmeet Sachdev, MD, lead investigator and neurologist, explained:

“CT Perfusion is a powerful tool, but its full value is only realized when paired with high-performing software, especially in complex cases with smaller occlusions like MeVOs.”

Study Details and Key Findings

The study analyzed 1,591 consecutive stroke cases at a comprehensive stroke center. Of the 1,122 cases deemed eligible, RapidAI successfully identified 93% of MeVOs (109 cases) using CT perfusion alone. By comparison, Viz.ai identified just 70% (82 cases).

This 33% performance gap is particularly significant because MeVOs—blockages in smaller arteries like the M2/M3 segments of the middle cerebral artery, or the A1/A2 and P1/P2 segments of the anterior and posterior cerebral arteries—are notoriously difficult to detect but can cause substantial brain damage if missed or misdiagnosed.

Dr. Sachdev added that the new data echoes what was seen in the earlier DUEL study, which compared performance in large vessel occlusions: “The story the data tells is clear: not all imaging tools are equally equipped to interpret complex stroke cases.”

Why It Matters

Unlike large vessel occlusions, MeVOs involve smaller—but still critical—arteries in the brain. These occlusions are harder to spot and often require more sophisticated imaging interpretation. Missing a MeVO can result in treatment delays during the most time-sensitive window of a stroke event.

RapidAI’s detection advantage is attributed to its “clinically deep” algorithms, which integrate validated perfusion imaging with decision support tailored for stroke care.

“These real-world clinical findings validate what sets RapidAI apart,” said David Stoffel, MD, chief business officer at RapidAI. “Deeper clinical algorithms that not only detect more but empower providers with greater clarity and confidence.”

Validation from Clinical Trials

RapidAI’s software has previously been validated in several landmark stroke trials, including DEFUSE 2, SWIFT PRIME, EXTEND-IA, and DEFUSE 3, all of which established the accuracy of perfusion imaging in assessing stroke severity. The company’s Rapid CT and MR perfusion platforms are the only imaging tools demonstrated to predict subsequent infarct volume based on initial scans.

RapidAI is also currently the only FDA-approved perfusion software for selecting patients for mechanical thrombectomy, a critical stroke intervention that depends on accurate identification of affected brain tissue.

Learn more about RapidAI here.

About the Study

The new study, titled “AI Detection of Medium Vessel Occlusions: Evaluating Performance of RapidAI vs Viz.ai CT Perfusion in 1,591 Consecutive Code Strokes”, was presented as a late-breaking abstract at ESOC 2025. The data further supports RapidAI’s position as a leader in neurovascular imaging and AI-enabled clinical decision support.

What This Means

For patients experiencing a stroke, every minute between onset and treatment can mean the difference between recovery and long-term disability—or even life and death. Medium vessel occlusions (MeVOs), though smaller than major strokes, can still result in serious brain damage if not identified and treated quickly. The challenge is that these occlusions are harder to detect, and many AI tools fail to catch them consistently.

This study shows that RapidAI’s software is significantly better equipped to recognize these subtle but dangerous blockages in real time. That means more patients could receive timely interventions—like thrombectomy or other targeted treatments—before irreversible damage occurs.

In practical terms, hospitals using less accurate imaging tools may be missing critical cases entirely. That can lead to delayed care, worse outcomes, and unnecessary risk for patients whose strokes are already difficult to diagnose. RapidAI’s advantage in MeVO detection isn’t just a technical win—it represents a meaningful step toward faster, more equitable stroke care for patients who might otherwise be overlooked.

As stroke care continues to evolve, the ability to detect more cases—accurately and early—will shape how hospitals triage patients, allocate resources, and ultimately, save lives.

Editor’s Note: This article was created by Alicia Shapiro, CMO of AiNews.com, with writing, image, and idea-generation support from ChatGPT, an AI assistant. However, the final perspective and editorial choices are solely Alicia Shapiro’s. Special thanks to ChatGPT for assistance with research and editorial support in crafting this article.