TraumaCad Neo (1.1)

K243810

Brainlab Ltd. · cleared 2025-06-04 · product code QIH · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.4)
“TraumaCad Neo is indicated for assisting healthcare professionals to analyze orthopedic conditions and to plan orthopedic procedures by overlaying on relevant radiological images visual information such as measurements and prosthesis templates. Clinical judgment and experience are required to properly use the software. The software is not intended for primary radiological image interpretation or radiological appraisal. Device is not intended for use on mobile phones.”
AlgorithmAI/ML based algorithm
source quote (p.10)
“The AI/ML models incorporated into the TraumaCad Neo 1.1 were trained, tested and validated for their performance, by qualified personnel, based on predefined protocols and criteria.”
Adaptive (vs locked)No
source quote (p.10)
“The mentioned Al/ML models are non-adaptive, i.e. do not learn from data once initially trained.”
PCCPFDA source did not state this
Cybersecurity addressedFDA source did not state this

Validation studies (1)

Retrospective clinical

n=349 images

endpoints: implant presence detection accuracy; 2D landmark detection accuracy

Reported performance (2 observations)

accuracyas written: “Implant presence detection accuracy”0.99
source quote (p.11)
“The results showed that 99% of the time the machine learning algorithm was able to correctly determine the implant presence”
accuracyas written: “Landmark detection accuracy (within 4mm distance)”0.92
source quote (p.11)
“and 92% of the landmarks were successfully detected automatically within 4mm distance from their corresponding ground-truth landmark annotations.”

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/K243810