What the Avicenna.AI Pulmonary Embolism Evidence Review Reports
Avicenna.AI published on June 3, 2026 a review of six peer-reviewed studies covering AI detection of pulmonary embolism on CT pulmonary angiography. The company reports that in a real-world study of 1,204 examinations, clot-positive cases not reported at first read fell from 15.6 percent to 3.8 percent, with per-case sensitivity of 93.9 percent and specificity of 94.8 percent. It reports time from scan to specialist consult falling from 241 minutes to 6.7 minutes at one US referral centre, scan-to-alert time falling from 318 minutes to 5.47 minutes in a follow-up at the same institution, and in-hospital deaths falling from 8.4 percent among 113 patients before deployment to 2.2 percent among 45 patients after. In a reader study of 207 examinations, radiology residents reached 92.5 percent sensitivity with the tool against 81.7 percent without it. Avicenna.AI describes the product, CINA-PE, as a CE marked Class IIb decision-support tool with FDA 510(k) clearance K210237. This site's own FDA device records list K210237 as a 510(k) clearance decided on May 19, 2021 under the applicant name Avicenna.Ai, recorded there with the device name CINA CHEST.
Why the Avicenna.AI Clot Detection Evidence Matters to Radiology Buyers
Publishing six studies with confidence intervals, rather than one percentage on a slide, is the behaviour a cautious buyer should reward, and the sensitivity figures hold up across several CT vendors and scanner models. The weakest numbers in the set are the mortality ones, because 113 patients before and 45 after is a small single-site comparison where staffing, triage habits and case mix all changed at the same time as the software. The time-to-consult drop from four hours to minutes is the result most likely to repeat elsewhere, since a faster alert does not depend on the model being clever, only on it firing.
Where the Avicenna.AI Update Comes From
Avicenna.AI is the original record behind this update. It tells us what the company published. This brief adds the market context and the method we would use to test the development against other evidence.
How We Would Research the Avicenna.AI Pulmonary Embolism Studies
The source gives us the starting point. This is how we would build the next layer of research around it.
- We would start by reading the two mortality papers in full to see what else changed at that hospital when the tool went live.
- Then we would check which of the six studies were funded or co-authored by Avicenna.AI and which were independent.
- We would ask Avicenna.AI to reconcile its own CINA-PE label for K210237 with the CINA CHEST device name on that clearance record.