FractureDetect (FX)

K193417

Imagen Technologies, Inc. · cleared 2020-07-30 · product code QBS · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.8)
“The subject device is a software-only device, therefore; electrical safety and EMC testing is not applicable.”
Algorithmindustry-standard deep learning algorithms for computer vision
source quote (p.5)
“FX was developed using robust scientific principles and industry-standard deep learning algorithms for computer vision.”
Adaptive (vs locked)FDA source did not state this
PCCPFDA source did not state this
Cybersecurity addressedFDA source did not state this

Validation studies (2)

Bench

n=11,970 images

endpoints: sensitivity; specificity; Area Under the Curve (AUC) of the Receiver Operating Characteristic (ROC)

Reader study (MRMC)

n=175 cases

endpoints: diagnostic accuracy of readers aided by FX; Reader sensitivity; Reader specificity

Reported performance (3 observations)

sensitivity0.951CI 0.940, 0.960
source quote (p.8)
“The results of standalone testing demonstrated that FX detects fractures of the musculoskeletal system in radiographs with high sensitivity (0.951; 95% Wilson's Confidence Interval (CI): 0.940, 0.960)”
specificity0.893CI 0.886, 0.898
source quote (p.8)
“high specificity (0.893; 95% Wilson's CI: 0.886, 0.898)”
aurocas written: “auc”0.982CI 0.9790, 0.9850
source quote (p.8)
“and high Area Under the Curve (AUC) of the Receiver Operating Characteristic (ROC) (0.982; 95% Bootstrap CI: 0.9790, 0.9850).”

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
0
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/K193417