CINA-CSpine
K240942Avicenna.AI · cleared 2024-09-12 · product code QAS · Radiology
Premarket evidence — what FDA accepted
Device typesamd
source quote (p.4)
“CINA-CSpine is a radiological computer aided triage and notification software indicated for use in the analysis of cervical spine CT images.”
Algorithmdeep learning algorithm
source quote (p.4)
“CINA-CSpine uses an artificial intelligence algorithm to analyze images and highlight cases with detected findings on a standalone application in parallel to the ongoing standard of care image interpretation. To identify the suspected presence of cervical fractures, the device uses a deep learning model trained end-to-end on 1,338 cases acquired from US and France, representing a distribution of fracture presentations, locations and acquisition protocols, including multiple scanner models from Siemens, Philips, GE and Canon/Toshiba.”
Adaptive (vs locked)FDA source did not state this
PCCPFDA source did not state this
Cybersecurity addressedFDA source did not state this
Validation studies (1)
Retrospective clinical
n=328 cases
endpoints: evaluate the software's performance (Sensitivity and Specificity) in detecting cervical spine (CSpine) fractures
Reported performance (4 observations)
sensitivity0.903CI 84.5% - 94.5%
source quote (p.8)
“As a primary endpoint, the global Sensitivity and Specificity were found to be 90.3% [95%CI: 84.5% - 94.5%] and 91.9% [95%CI: 86.8% - 95.5%], respectively.”
specificity0.919CI 86.8% - 95.5%
source quote (p.8)
“As a primary endpoint, the global Sensitivity and Specificity were found to be 90.3% [95%CI: 84.5% - 94.5%] and 91.9% [95%CI: 86.8% - 95.5%], respectively.”
time_to_resultas written: “mean time-to-notification for all included cases”2.9CI 2.7 - 3.0
source quote (p.8)
“The mean [95% Cl] time-to-notification for all included cases (n = 328) was estimated to be 2.9 [95% CI: 2.7 - 3.0] minutes for CINA-CSpine.”
time_to_resultas written: “mean time-to-notification for true positive cases”2.8CI 2.6 - 3.0
source quote (p.8)
“When taking into account only true positive cases (n = 140), the mean [95% CI] time-to-notification was 2.8 [95%CI: 2.6 - 3.0] minutes for CINA-CSpine”
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). 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).