VUNO Med-DeepBrain

K231398

VUNO Inc. · cleared 2023-10-04 · product code QIH · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.6)
“The VUNO Med-DeepBrain is intended for automatic labeling, quantification and visualization of segmentable brain structures from a set of MR images. The software is intended to automate the current manual process of identifying, labeling and quantifying segmentable brain structures identified on MR images.”
Algorithmdeep learning model
source quote (p.9)
“Mainly the algorithm used for the segmentation is different. The predicate device used a machine learning technique while the subject device is built upon a deep learning model.”
Adaptive (vs locked)FDA source did not state this
PCCPNo
Cybersecurity addressedYes
source quote (p.9)
“VUNO Med-DeepBrain is a cyber device and the risks associated with cybersecurity are identified and addressed. The device meets the requirement under the FDA Guidance, “Content of Premarket Submissions for Management of Cybersecurity in Medical Devices: Guidance for Industry and Food and Drug Administration Staff (October 2, 2014)".”

Validation studies (1)

Bench

sample size not stated

endpoints: Segmentation accuracy (Dice Similarity Coefficient); Test-retest reproducibility (intraclass correlation coefficient); Volume errors

Reported performance (1 observation)

diceas written: “Dice Similarity Coefficient (DSC) score for brain regions”stated without value
source quote (p.9)
“The acceptance criteria are an average DSC score of 0.80 in brain regions and White Matter Hyperintensities(WMH) regions as referred to in the literature. Whole brain regions including cortical and subcortical as well as WMH regions exceeded the criteria.”

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/K231398