syngo.CT Brain Hemorrhage

K232431

Siemens Medical Solutions USA, Inc. · cleared 2024-03-22 · product code QAS · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.5)
“The subject device syngo.CT Brain Hemorrhage is an image-processing software that uses an artificial intelligence algorithm to support qualified clinicians in the analysis and prioritization of non-contrast head CT images. It is a notification-only processing application that algorithmically identifies findings suspicious of acute intracranial hemorrhage (ICH) and acute subarachnoid hemorrhage (SAH). The output is intended for informational purposes only and is not intended for diagnostic use. The device does not alter the original medical image and is not intended to be used as a standalone diagnostic device.”
Algorithmartificial intelligence algorithm
source quote (p.5)
“The subject device syngo.CT Brain Hemorrhage is an image-processing software that uses an artificial intelligence algorithm to support qualified clinicians in the analysis and prioritization of non-contrast head CT images.”
Adaptive (vs locked)FDA source did not state this
PCCPFDA source did not state this
Cybersecurity addressedFDA source did not state this

Validation studies (2)

Retrospective clinical

n=900 cases · 5 site(s)

endpoints: triage of intracranial hemorrhage; triage of subarachnoid hemorrhage

Bench

sample size not stated

Reported performance (4 observations)

sensitivity95CI 95% CI: 92.5%-96.7%
source quote (p.7)
“For the triage of intracranial hemorrhage, the sensitivity was 95.0% (95% CI: 92.5%-96.7%)”
specificity93.1CI 95% CI: 90.5%-95.1%
source quote (p.7)
“and the specificity was 93.1% (95% CI: 90.5%-95.1%).”
sensitivityas written: “sensitivity for subarachnoid hemorrhage”86.1CI 95% CI: 81.1%-90.0%
source quote (p.7)
“For the triage of subarachnoid hemorrhage, the sensitivity was 86.1% (95% CI: 81.1%-90.0%)”
specificityas written: “specificity for subarachnoid hemorrhage”85.2CI 95% CI: 82.3%-87.7%
source quote (p.7)
“and the specificity was 85.2% (95% CI: 82.3%-87.7%).”

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/K232431