StrokeSENS LVO

K212261

Circle Neurovascular Imaging, Inc · cleared 2021-10-14 · product code QAS · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.4)
“StrokeSENS LVO is a radiological computer-aided triage and notification (CADt) software indicated for use in the analysis of CTA head images.”
Algorithmmachine learning software algorithm, a binary classifier, providing a binary output of either positive or negative for suspected LVO, based on a pre-defined threshold
source quote (p.5)
“StrokeSENS LVO uses a software algorithm based on machine learning to identify suspected LVO findings. The Processing Engine consists of a software algorithm (a sequence of instructions/operations) that is responsible for analyzing contrast-enhanced CT (CTA) image data of the head to identify characteristics that are consistent with LVO. The software algorithm is a binary classifier, providing a binary output of either positive or negative for suspected LVO, based on a pre-defined threshold.”
Adaptive (vs locked)No
source quote (p.9)
“Algorithms are static and locked. Algorithms are not dynamic or learning while in the market.”
PCCPFDA source did not state this
Cybersecurity addressedYes
source quote (p.10)
“Verification and validation testing were conducted to ensure specifications and performance of the device and were performed per the FDA Guidance documents “Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices" and "Content of Premarket Submission for Management of Cybersecurity in Medical Devices".”

Validation studies (1)

Retrospective clinical

n=400 cases

endpoints: sensitivity; specificity; time to notify

standards: ISO 13485:2016, IEC 62304:2015, IEC 62366:2015, ISO 14971:2019, NEMA 3.1-3.20 (2011)

Reported performance (2 observations)

sensitivity0.894CI [85.3%, 93.5%]
source quote (p.10)
“The device achieved a mean sensitivity of 89.4% CI = [85.3%, 93.5%]”
specificity0.874CI [82.6%, 92.2%]
source quote (p.10)
“and mean specificity of 87.4% CI = [82.6%, 92.2%] for the binary LVO detection task on the test set (N=400, LVO=217, Non-LVO=183).”

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/K212261