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”
Algorithmdeep learning algorithms
source quote (p.5)
“To identify the suspected presence of pulmonary embolisms, the device uses a deep learning model trained end-to-end on 5,429 cases acquired from US and France, representing a distribution of PE sizes, locations and acquisition protocols, including multiple scanner models from Siemens, Philips, GE and Canon/Toshiba.”
Adaptive (vs locked)FDA source did not state this
PCCPNo
Cybersecurity addressedFDA source did not state this

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 (Main)”96.3CI [87.5% - 99.6%]
source quote (p.7)
“Table 1: Stratified statistical analysis (Sensitivity [95%CI]) regarding arterial segments. Main (N = 55) 96.3% [87.5% - 99.6%]”
sensitivityas written: “Sensitivity (Interlobar)”94.5CI [86.6% - 98.5%]
source quote (p.7)
“Table 1: Stratified statistical analysis (Sensitivity [95%CI]) regarding arterial segments. Interlobar (N = 73) 94.5% [86.6% - 98.5%]”
sensitivityas written: “Sensitivity (Lobar)”92.9CI [87.0% - 96.7%]
source quote (p.7)
“Table 1: Stratified statistical analysis (Sensitivity [95%CI]) regarding arterial segments. Lobar (N = 127) 92.9% [87.0% - 96.7%]”
sensitivityas written: “Sensitivity (Segmental)”88.3CI [82.6% - 92.6%]
source quote (p.7)
“Table 1: Stratified statistical analysis (Sensitivity [95%CI]) regarding arterial segments. Segmental (N = 179) 88.3% [82.6% - 92.6%]”
time_to_resultas written: “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: “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

0
recalls in product code, 24mo
0
MAUDE reports in code, 12mo
—
vs code's own 3-yr baseline
0
drift signals on this device

Recall and MAUDE counts are product-code-level (reports aren't reliably attributable to one device); a recall is shown as device-attributed only when the recall record itself lists this clearance number. 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).

Applicable FDA guidance — what the submission is measured against

FDA guidance documents and guiding principles applicable to 510(k) AI/ML devices in the Radiology panel. A curated reference index, not legal or regulatory advice — each item states its own status, and a draft is never binding.

Applicability is derived from the device's FDA advisory panel and pathway — cross-cutting guidances apply to every AI/ML device; panel-specific ones are flagged. Titles, dates, and links verified against fda.gov as of July 2026.

Constat Precedent · public FDA/CMS data · descriptive decision-support, not regulatory or reimbursement advice. Share this page: constat.dev/precedent/device/K233968