CINA-iPE

K233968

Avicenna.AI · cleared 2024-03-13 · product code QAS · Radiology

Premarket evidence — what FDA accepted

Device typesamd

source quote (p.3)

“CINA-iPE is a radiological computer-aided triage and notification software indicated for use in patients undergoing contrast-enhanced CT scans (not dedicated CTPA protocol) for other clinical indications than pulmonary embolism suspicion, including at least a part of the lung.”

Algorithmartificial intelligence algorithm

source quote (p.3)

“CINA-IPE uses an artificial intelligence algorithm to analyze images and highlight cases with detected incidental PE on a standalone application in parallel to the ongoing standard of care image interpretation.”

Adaptive (vs locked)FDA source did not state this

PCCPNo

source quote (p.1)

“Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device" (https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download).”

Cybersecurity addressedNo

Validation studies (1)

Retrospective clinical

n=381 cases

endpoints: evaluate the software's performance in identifying incidental pulmonary embolisms (iPE)

standards: DICOM (Digital Imaging and Communications in Medicine) – Developed by the American College of Radiology and the National Electrical Manufacturers Association. NEMA PS 3.1 - 3.20.

Reported performance (8 observations)

sensitivity87.8CI 95%CI: 82.2% - 92.2%

source quote (p.7)

“As a primary endpoint, the global Sensitivity and Specificity were found to be 87.8% [95%CI: 82.2% - 92.2%] and 92.0% [95%CI: 87.3% - 95.4%], respectively.”

specificity92CI 95%CI: 87.3% - 95.4%

source quote (p.7)

“As a primary endpoint, the global Sensitivity and Specificity were found to be 87.8% [95%CI: 82.2% - 92.2%] and 92.0% [95%CI: 87.3% - 95.4%], respectively.”

sensitivityas written: “Sensitivity for Main arterial segment”96.3CI [87.5% - 99.6%]

source quote (p.7)

“Main (N = 55) 96.3% [87.5% - 99.6%]”

sensitivityas written: “Sensitivity for Interlobar arterial segment”94.5CI [86.6% - 98.5%]

source quote (p.7)

“Interlobar (N = 73) 94.5% [86.6% - 98.5%]”

sensitivityas written: “Sensitivity for Lobar arterial segment”92.9CI [87.0% - 96.7%]

source quote (p.7)

“Lobar (N = 127) 92.9% [87.0% - 96.7%]”

sensitivityas written: “Sensitivity for Segmental arterial segment”88.3CI [82.6% - 92.6%]

source quote (p.7)

“Segmental (N = 179) 88.3% [82.6% - 92.6%]”

time_to_resultas written: “Mean Time-to-Notification (All cases)”1.5CI [1.4 - 1.5]

source quote (p.8)

“The mean [95% CI] time-to-notification for all included cases (n = 381) was estimated to be 1.5 [95% CI: 1.4 – 1.5] minutes for CINA-iPE.”

time_to_resultas written: “Mean Time-to-Notification (True Positive cases)”1.5CI [1.4 - 1.6]

source quote (p.8)

“When taking into account only true positive cases (n = 159), the mean [95% CI] time-to-notification was 1.5 [95% CI: 1.4 – 1.6] minutes for CINA-iPE”

Each value carries its own analysis unit and task — never compare or pool across devices. Source: 510(k) summary PDF.

Predicate network

Postmarket — what happened after clearance

recalls in product code, 24mo

MAUDE reports in code, 12mo

—

vs code's own 3-yr baseline

drift signals on this device

Recall and MAUDE counts are product-code-level (reports aren't reliably attributable to one device). Signals are descriptive observables with sources — never a judgment that the device is unsafe or drifting. Snapshot 2026-07-08.

Reimbursement — how devices like this got paid

Not yet tracked — no payment pathway indexed for this clearance (the reimbursement corpus is a growing seed set).