MammoScreen® (4)

K243679

Therapixel · cleared 2025-07-03 · product code QDQ · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.7)
“MammoScreen is a software-only device.”
Algorithmdeep learning modules
source quote (p.8)
“The system includes ‘deep learning' modules for the detection of suspicious calcifications and soft tissue lesions.”
Adaptive (vs locked)FDA source did not state this
PCCPYes
source quote (p.1)
“FDA's substantial equivalence determination also included the review and clearance of your Predetermined Change Control Plan (PCCP).”
Cybersecurity addressedFDA source did not state this

Validation studies (2)

Standalone

n=1,475 patients

endpoints: Non-inferiority in standalone cancer detection performance compared to the previous version of MammoScreen; AUC at the mammogram level; AUC at the breast level; AUC LROC at the finding level

standards: IEC 62304:2006/A1:2016- Medical device software - Software life-cycle processes, IEC 62366-1:2015+AMD1:2020- Medical devices - Application of usability engineering to medical devices.

Reader study (MRMC)

sample size not stated

endpoints: determine whether the radiologist's performance when using MammoScreen is superior to unaided radiologist performance for interpretation of mammograms.

Reported performance (3 observations)

aurocas written: “auc”0.894CI 0.870, 0.919
source quote (p.9)
“AUC at the mammogram level MS4: 0.894 (0.870, 0.919), MS2: 0.867 (0.839, 0.896), Δ: 0.027 (0.002, 0.052), p<0.0001”
aurocas written: “AUC at the breast level”0.919CI 0.897, 0.941
source quote (p.9)
“AUC at the breast level: MS4: 0.919 (0.897, 0.941), MS2: 0.895 (0.871, 0.920), Δ: 0.023 (0.002, 0.045), p<0.0001”
aurocas written: “AUC LROC at the finding level”0.891CI 0.862, 0.921
source quote (p.9)
“AUC LROC at the finding level: MS4: 0.891 (0.862, 0.921), MS2: 0.837 (0.797, 0.877), Δ: 0.055 (0.032, 0.077), p<0.0001”

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
1
drift signals on this device
  • re_clearance

    The FDA AI/ML device list shows a newer 510(k) K243685 (decision 2025-08-22) from Therapixel for a matching device line ("MammoScreen BD") — a new clearance for the same line is a change event.

    first seen 2026-07-08 · k_number:K243685

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/K243679