SMART PCFD

K250023

Disior Ltd · cleared 2025-09-29 · product code QIH · Radiology

FDA 510(k) summary for SMART PCFD (K250023)

Constat organizes this clearance into predicate context, validation evidence, reported performance, postmarket signals, and reimbursement links. Each extracted claim stays tied to the public FDA source; missing fields remain explicitly unstated.

Validation studies
2
Cited predicates
2
Performance observations
2
Product code
QIH
Official FDA 510(k) database record ↗FDA 510(k) source PDF ↗

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.4)
“SMART PCFD software includes AI-powered algorithms and is intended to be used to support orthopedic healthcare professionals in the diagnosis and surgical planning of Progressive Collapsing Foot Deformity (PCFD) in a hospital or clinic environment. The medical image modality intended to be used in the software is weight-bearing CT (WBCT).”
AlgorithmAI-powered algorithms for bone and metal identification, using machine learning derived outputs.
source quote (p.4)
“SMART PCFD software includes AI-powered algorithms and is intended to be used to support orthopedic healthcare professionals in the diagnosis and surgical planning of Progressive Collapsing Foot Deformity (PCFD) in a hospital or clinic environment. The AI algorithm for bone identification was developed using 145 CT image studies and metal identification was developed using 130 CT image studies.”
Adaptive (vs locked)FDA source did not state this
PCCPNo
Cybersecurity addressedNo

Validation studies (2)

Standalone

n=82 images

endpoints: correctly identified bones of foot and ankle; correctly identified existence of metal

Bench

sample size not stated

endpoints: estimated correction for angular measurements; estimated correction for distance measurements

Reported performance (2 observations)

sensitivity1
source quote (p.6)
“The existence of metal was identified correctly for 98.8% of the images (specificity 98%, sensitivity 100%).”
specificity0.98
source quote (p.6)
“The existence of metal was identified correctly for 98.8% of the images (specificity 98%, sensitivity 100%).”

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

1
recalls in product code, 24mo
4
MAUDE reports in code, 12mo
—
vs code's own 3-yr baseline
1
drift signals on this device
  • recall_reason_pattern

    Software/algorithm-related recall in product code QIH (PIE Medical Imaging B.V., initiated 2026-05-07): "User measurement value reported by diagnostic bioimaging software intended to measure/visualize cardiovascular structures may be larger (0.8% to 34.4%) than the actual anatomical d" Recalling firm is another firm in the same product code.

    first seen 2026-08-26 · recall res_event_number:98930

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 2026-08-26.

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.

Related FDA clearances

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Constat Precedent · public FDA/CMS data · descriptive decision-support, not regulatory or reimbursement advice. Share this page: constat.dev/precedent/device/K250023