Brain WMH

K251527

Quantib BV · cleared 2025-09-25 · product code QIH · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.6)
“Brain WMH is a software as a medical device (SaMD) that provides automatic quantification of white matter hyperintensities (WMHs) based on magnetic resonance (MR) images to assist trained medical professionals.”
Algorithmartificial intelligence-based algorithm
source quote (p.6)
“Brain WMH employs an updated artificial intelligence-based algorithm for WMH segmentation, whereas the predicate device uses a different machine learning approach.”
Adaptive (vs locked)No
PCCPNo
Cybersecurity addressedNo

Validation studies (2)

Bench

sample size not stated

standards: ISO 14971:2019 – Medical Devices – Application of Risk Management to Medical Devices (#5-125), IEC 62304:2015 – Medical Device Software – Software Life Cycles Processes (#13-79), NEMA PS3 – Digital Imaging and Communications in Medicine (DICOM) Set (#12-300), Guidance for Industry and FDA Staff: Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices (May, 2005), Guidance for Industry and FDA Staff: Software as a Medical Devices (SaMD): Clinical Evaluation (December 2017)

Standalone

n=90 patients

Reported performance (2 observations)

diceas written: “Dice coefficient”0.58CI ± 0.21
source quote (p.8)
“The standalone performance of Brain WMH segmentation, as measured by Dice coefficient (0.58 ± 0.21) was higher than the standalone performance of the predicate device and fell within the range of interobserver variability.”
accuracyas written: “WMH labeling accuracy (longitudinal validation)”97.1
source quote (p.8)
“The longitudinal validation demonstrated high accuracy in WMH labeling across scans acquired from the same patient (97.1% correctly labelled).”

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
3
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/K251527