Vascular Assist Occlusion Triage (VAOT) (v1.0)

K260729

GuideAI Health · cleared 2026-06-18 · product code QAS · Radiology

FDA 510(k) summary for Vascular Assist Occlusion Triage (VAOT) (v1.0) (K260729)

Constat organizes this clearance into predicate context, validation evidence, reported performance, postmarket signals, and reimbursement links. Each extracted claim stays tied to the public FDA source; missing fields remain explicitly unstated.

Validation studies
1
Cited predicates
1
Performance observations
3
Product code
QAS
Official FDA 510(k) database record ↗FDA 510(k) source PDF ↗

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.6)
“VAOT is radiological computer-assisted triage and notification software indicated for use in the analysis of CTA studies of adult patients. The software uses machine-learning techniques to automatically analyze CTA studies and to alert the PACS/RIS workstation once images with features suggestive of arterial occlusion are identified.”
Algorithmmachine-learning techniques, deep neural networks
source quote (p.6)
“The software uses machine-learning techniques to automatically analyze CTA studies and to alert the PACS/RIS workstation once images with features suggestive of arterial occlusion are identified. The VAOT cloud receives the DICOM image(s) and determines whether a possible occlusion should be flagged using an image-processing pipeline consisting of several deep neural networks.”
Adaptive (vs locked)FDA source did not state this
PCCPNo
Cybersecurity addressedYes
source quote (p.13)
“GuideAI conducted a cybersecurity risk assessment and testing in accordance 2025 FDA Guidance “Cybersecurity in Medical Devices: Quality System Considerations and Content of Premarket Submissions".”

Validation studies (1)

Retrospective clinical

n=317 cases

endpoints: sensitivity; specificity; time-to-notification

standards: 2023 FDA Guidance “Content of Premarket Submissions for Device Software Functions”, 2025 FDA Guidance “Cybersecurity in Medical Devices: Quality System Considerations and Content of Premarket Submissions”

Reported performance (3 observations)

sensitivity0.915CI 95% CI: 0.862, 0.953
source quote (p.12)
“Sensitivity was 0.915 (95% CI: 0.862, 0.953)”
specificity0.901CI 95% CI: 0.842, 0.944
source quote (p.12)
“specificity was 0.901 (95% CI: 0.842, 0.944).”
time_to_resultas written: “time-to-notification”stated without value
source quote (p.12)
“VAOT met the secondary endpoint of time-to-notification less than 5 minutes.”

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

Not yet tracked — the weekly postmarket refresh hasn't snapshotted this device.

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.

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Constat Precedent · public FDA/CMS data · descriptive decision-support, not regulatory or reimbursement advice. Share this page: constat.dev/precedent/device/K260729