PeekMed web

K252452

Peek Health, S.A. · cleared 2025-11-12 · product code QIH · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.6)
“PeekMed web is a system designed to help healthcare professionals carry out pre-operative planning for several surgical procedures, based on their imported patients' imaging studies. Experience in usage and a clinical assessment are necessary for the proper use of the system in the revision and approval of the output of the planning. The multi-platform system works with a database of digital representations related to surgical materials supplied by their manufacturers. As the PeekMed web is capable of representing medical images in a 2D or 3D environment, performing relevant measurements on those images, and also capable of adding templates, it can then provide a total overview of the surgery. Being software, it does not interact with any part of the body of the user and/or patient.”
AlgorithmML models for segmentation, landmarking, classification, and detection
source quote (p.15)
“ML models incorporated into the PeekMed web were also developed, trained, tested, and externally validated for their performance according to the internal procedures. ... External validation is performed by sample size with a total unique dataset, for Segmentation ML model: 672; Landmarking ML model: 561; Classification ML model: 367; and Detection ML model: 198.”
Adaptive (vs locked)FDA source did not state this
PCCPFDA source did not state this
Cybersecurity addressedFDA source did not state this

Validation studies (1)

Retrospective clinical

n=672 cases

endpoints: DICE; HD-95; STD DICE; Precision; Recall; MRE; STD MRE; Accuracy; F1 score; MAP

Reported performance (4 observations)

diceas written: “DICE”stated without value
source quote (p.16)
“DICE is no less than 90%”
diceas written: “STD DICE”stated without value
source quote (p.16)
“STD DICE is between +/- 10%”
accuracyas written: “Accuracy”stated without value
source quote (p.16)
“Accuracy is no less than 90%”
f1as written: “F1 score”stated without value
source quote (p.16)
“F1 score is no less than 90%”

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
1
drift signals on this device
  • re_clearance

    The FDA AI/ML device list shows a newer 510(k) K252856 (decision 2025-12-22) from Peek Health, S.A. for a matching device line ("PeekMed web") — a new clearance for the same line is a change event.

    first seen 2026-07-08 · k_number:K252856

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/K252452