HALO

K200873

NICo-Lab B.V. · cleared 2020-11-20 · product code QAS · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.3)
“HALO is a notification only cloud-based image processing software application using artificial intelligence algorithms to analyze patient imaging data in parallel to the standard of care imaging interpretation.”
AlgorithmArtificial intelligence algorithm with database of images
source quote (p.6)
“Artificial intelligence algorithm with database of images”
Adaptive (vs locked)FDA source did not state this
PCCPNo
Cybersecurity addressedYes
source quote (p.7)
“Non-Clinical software testing has been performed in accordance with the ... “Content of Premarket Submissions for Management of Cybersecurity in Medical Devices” (issued October 2, 2014, document number 1825).”

Validation studies (1)

Retrospective clinical

n=364 patients

endpoints: sensitivity for LVO detection; specificity for LVO detection; area under the curve (AUC); median notification time for the detected LVO cases

standards: Guidance for Industry and FDA Staff – Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices, Content of Premarket Submissions for Management of Cybersecurity in Medical Devices

Reported performance (4 observations)

sensitivity0.911CI 95% CI, 86.0%-94.8%
source quote (p.7)
“sensitivity and specificity for LVO detection of respectively 91.1% (95% CI, 86.0%-94.8%)”
specificity0.87CI 95% CI, 81.2%-91.5%
source quote (p.7)
“and 87.0% (95% CI, 81.2%-91.5%).”
aurocas written: “auc”0.97
source quote (p.7)
“The area under the curve (AUC) is 0.97.”
time_to_resultas written: “median notification time”stated without valueCI minimum of 3:47 and maximal 7:12
source quote (p.7)
“For the secondary endpoints the median notification time for the detected LVO cases was 4 minutes 31 seconds, with a minimum of 3:47 and maximal 7:12.”

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/K200873