CINA

K221716

AVICENNA.AI · cleared 2022-11-22 · product code QAS · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.5)
“Cina is a radiological computer-assisted triage and notification software device.”
Algorithmartificial intelligence algorithm
source quote (p.5)
“Cina uses an artificial intelligence algorithm to analyze images and highlight cases with detected (1) ICH or (2) LVO on a standalone Web application in parallel to the ongoing standard of care image interpretation.”
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=1,290 cases · 3 site(s)

endpoints: software's performance in 1) non-contrast CT (NCCT) head images pertaining to patient with suspected intracranial hemorrhage (ICH) findings and 2) CT angiography (CTA) head series pertaining to patient with suspected large vessel occlusion (LVO) findings; Sensitivity; Specificity; time-to-notification; overall agreement (accuracy); Positive predictive value; Negative predictive value

Reported performance (10 observations)

sensitivity0.914CI 95% CI: 87.2% – 94.5%
source quote (p.9)
“Sensitivity and Specificity for the "ICH” prioritization and triage application are 91.4% (95% CI: 87.2% – 94.5%) and 97.5% (95% CI: 95.8% – 98.6%), respectively.”
specificity0.975CI 95% CI: 95.8% – 98.6%
source quote (p.9)
“Sensitivity and Specificity for the "ICH” prioritization and triage application are 91.4% (95% CI: 87.2% – 94.5%) and 97.5% (95% CI: 95.8% – 98.6%), respectively.”
aurocas written: “auc”0.94
source quote (p.9)
“The ROC curve shows an AUC of 0.94, which is also the same as for the predicate device.”
sensitivityas written: “Sensitivity (LVO)”0.979CI 95% CI: 94.6% – 99.4%
source quote (p.9)
“Regarding the “LVO” prioritization and triage application, Sensitivity and Specificity of 97.9% (95% CI: 94.6% – 99.4%) and 97.6% (95% CI: 95.1% – 99%), respectively are observed.”
specificityas written: “Specificity (LVO)”0.976CI 95% CI: 95.1% – 99%
source quote (p.9)
“Regarding the “LVO” prioritization and triage application, Sensitivity and Specificity of 97.9% (95% CI: 94.6% – 99.4%) and 97.6% (95% CI: 95.1% – 99%), respectively are observed.”
aurocas written: “AUC (LVO)”0.98
source quote (p.9)
“The ROC curve shows an AUC of 0.98, which is also the same as for the predicate device.”
accuracyas written: “Accuracy (ICH)”0.956
source quote (p.9)
“The results of the standalone assessment study demonstrated an overall agreement (accuracy) of 95.6% and 97.7% for the “ICH" and "LVO" tested cases, respectively, when compared to the ground truth (operators' visual assessments).”
accuracyas written: “Accuracy (LVO)”0.977
source quote (p.9)
“The results of the standalone assessment study demonstrated an overall agreement (accuracy) of 95.6% and 97.7% for the “ICH" and "LVO" tested cases, respectively, when compared to the ground truth (operators' visual assessments).”
time_to_resultas written: “Mean time-to-notification (ICH)”13.2CI ± 2.9 seconds
source quote (p.10)
“Specifically, the Cina's "ICH” triage mean ± SD "time-to-notification” is estimated to 13.2 ± 2.9 seconds.”
time_to_resultas written: “Mean time-to-notification (LVO)”25.8CI ± 7.0 seconds
source quote (p.10)
“Regarding Cina - LVO triage application, the mean ± SD "time-to-notification” is estimated to 25.8 ± 7.0 seconds.”

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
4
drift signals on this device
  • re_clearance

    The FDA AI/ML device list shows a newer 510(k) K240942 (decision 2024-09-12) from Avicenna.AI for a matching device line ("CINA-CSpine") — a new clearance for the same line is a change event.

    first seen 2026-07-08 · k_number:K240942

  • re_clearance

    The FDA AI/ML device list shows a newer 510(k) K240612 (decision 2024-05-31) from Avicenna.AI for a matching device line ("CINA-VCF") — a new clearance for the same line is a change event.

    first seen 2026-07-08 · k_number:K240612

  • re_clearance

    The FDA AI/ML device list shows a newer 510(k) K233342 (decision 2024-03-15) from Avicenna.AI for a matching device line ("CINA-ASPECTS") — a new clearance for the same line is a change event.

    first seen 2026-07-08 · k_number:K233342

  • re_clearance

    The FDA AI/ML device list shows a newer 510(k) K233968 (decision 2024-03-13) from Avicenna.AI for a matching device line ("CINA-iPE") — a new clearance for the same line is a change event.

    first seen 2026-07-08 · k_number:K233968

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/K221716